WorldWideScience

Sample records for complex agent networks

  1. Behavior of Self-Motivated Agents in Complex Networks

    CERN Document Server

    Kim, Sundong

    2016-01-01

    Traditional evolutionary game theory describes how certain strategy spreads throughout the system where individual player imitates the most successful strategy among its neighborhood. Accordingly, player doesn't have own authority to change their state. However in the human society, peoples do not just follow strategies of other people, they choose their own strategy. In order to see the decision of each agent in timely basis and differentiate between network structures, we conducted multi-agent based modeling and simulation. In this paper, agent can decide its own strategy by payoff comparison and we name this agent as "Self-motivated agent". To explain the behavior of self-motivated agent, prisoner's dilemma game with cooperator, defector, loner and punisher are considered as an illustrative example. We performed simulation by differentiating participation rate, mutation rate and the degree of network, and found the special coexisting conditions.

  2. A multi-agent genetic algorithm for community detection in complex networks

    Science.gov (United States)

    Li, Zhangtao; Liu, Jing

    2016-05-01

    Complex networks are popularly used to represent a lot of practical systems in the domains of biology and sociology, and the structure of community is one of the most important network attributes which has received an enormous amount of attention. Community detection is the process of discovering the community structure hidden in complex networks, and modularity Q is one of the best known quality functions measuring the quality of communities of networks. In this paper, a multi-agent genetic algorithm, named as MAGA-Net, is proposed to optimize modularity value for the community detection. An agent, coded by a division of a network, represents a candidate solution. All agents live in a lattice-like environment, with each agent fixed on a lattice point. A series of operators are designed, namely split and merging based neighborhood competition operator, hybrid neighborhood crossover, adaptive mutation and self-learning operator, to increase modularity value. In the experiments, the performance of MAGA-Net is validated on both well-known real-world benchmark networks and large-scale synthetic LFR networks with 5000 nodes. The systematic comparisons with GA-Net and Meme-Net show that MAGA-Net outperforms these two algorithms, and can detect communities with high speed, accuracy and stability.

  3. Complex Agent Networks explaining the HIV epidemic among homosexual men in Amsterdam

    CERN Document Server

    Mei, Shan; Quax, Rick; van de Vijver, David; Zhu, Yifan

    2008-01-01

    Simulating the evolution of the Human Immunodeficiency Virus (HIV) epidemic requires a detailed description of the population network, especially for small populations in which individuals can be represented in detail and accuracy. In this paper, we introduce the concept of a Complex Agent Network(CAN) to model the HIV epidemics by combining agent-based modelling and complex networks, in which agents represent individuals that have sexual interactions. The applicability of CANs is demonstrated by constructing and executing a detailed HIV epidemic model for men who have sex with men (MSM) in Amsterdam, including a distinction between steady and casual relationships. We focus on MSM contacts because they play an important role in HIV epidemics and have been tracked in Amsterdam for a long time. Our experiments show good correspondence between the historical data of the Amsterdam cohort and the simulation results.

  4. The Evolution of ICT Markets: An Agent-Based Model on Complex Networks

    Science.gov (United States)

    Zhao, Liangjie; Wu, Bangtao; Chen, Zhong; Li, Li

    Information and communication technology (ICT) products exhibit positive network effects.The dynamic process of ICT markets evolution has two intrinsic characteristics: (1) customers are influenced by each others’ purchasing decision; (2) customers are intelligent agents with bounded rationality.Guided by complex systems theory, we construct an agent-based model and simulate on complex networks to examine how the evolution can arise from the interaction of customers, which occur when they make expectations about the future installed base of a product by the fraction of neighbors who are using the same product in his personal network.We demonstrate that network effects play an important role in the evolution of markets share, which make even an inferior product can dominate the whole market.We also find that the intensity of customers’ communication can influence whether the best initial strategy for firms is to improve product quality or expand their installed base.

  5. Automation of multi-agent control for complex dynamic systems in heterogeneous computational network

    Science.gov (United States)

    Oparin, Gennady; Feoktistov, Alexander; Bogdanova, Vera; Sidorov, Ivan

    2017-01-01

    The rapid progress of high-performance computing entails new challenges related to solving large scientific problems for various subject domains in a heterogeneous distributed computing environment (e.g., a network, Grid system, or Cloud infrastructure). The specialists in the field of parallel and distributed computing give the special attention to a scalability of applications for problem solving. An effective management of the scalable application in the heterogeneous distributed computing environment is still a non-trivial issue. Control systems that operate in networks, especially relate to this issue. We propose a new approach to the multi-agent management for the scalable applications in the heterogeneous computational network. The fundamentals of our approach are the integrated use of conceptual programming, simulation modeling, network monitoring, multi-agent management, and service-oriented programming. We developed a special framework for an automation of the problem solving. Advantages of the proposed approach are demonstrated on the parametric synthesis example of the static linear regulator for complex dynamic systems. Benefits of the scalable application for solving this problem include automation of the multi-agent control for the systems in a parallel mode with various degrees of its detailed elaboration.

  6. Distributed optimization-based control of multi-agent networks in complex environments

    CERN Document Server

    Zhu, Minghui

    2015-01-01

    This book offers a concise and in-depth exposition of specific algorithmic solutions for distributed optimization based control of multi-agent networks and their performance analysis. It synthesizes and analyzes distributed strategies for three collaborative tasks: distributed cooperative optimization, mobile sensor deployment and multi-vehicle formation control. The book integrates miscellaneous ideas and tools from dynamic systems, control theory, graph theory, optimization, game theory and Markov chains to address the particular challenges introduced by such complexities in the environment as topological dynamics, environmental uncertainties, and potential cyber-attack by human adversaries. The book is written for first- or second-year graduate students in a variety of engineering disciplines, including control, robotics, decision-making, optimization and algorithms and with backgrounds in aerospace engineering, computer science, electrical engineering, mechanical engineering and operations research. Resea...

  7. Complex Networks

    CERN Document Server

    Evsukoff, Alexandre; González, Marta

    2013-01-01

    In the last decade we have seen the emergence of a new inter-disciplinary field focusing on the understanding of networks which are dynamic, large, open, and have a structure sometimes called random-biased. The field of Complex Networks is helping us better understand many complex phenomena such as the spread of  deseases, protein interactions, social relationships, to name but a few. Studies in Complex Networks are gaining attention due to some major scientific breakthroughs proposed by network scientists helping us understand and model interactions contained in large datasets. In fact, if we could point to one event leading to the widespread use of complex network analysis is the availability of online databases. Theories of Random Graphs from Erdös and Rényi from the late 1950s led us to believe that most networks had random characteristics. The work on large online datasets told us otherwise. Starting with the work of Barabási and Albert as well as Watts and Strogatz in the late 1990s, we now know th...

  8. Decentralized network management based on mobile agent

    Institute of Scientific and Technical Information of China (English)

    李锋; 冯珊

    2004-01-01

    The mobile agent technology can be employed effectively for the decentralized management of complex networks. We show how the integration of mobile agent with legacy management protocol, such as simple network management protocol (SNMP), leads to decentralized management architecture. HostWatcher is a framework that allows mobile agents to roam network, collect and process data, and perform certain adaptive actions. A prototype system is built and a quantitative analysis underlines the benefits in respect to reducing network load.

  9. Modeling the Internet of Things, Self-Organizing and Other Complex Adaptive Communication Networks: A Cognitive Agent-Based Computing Approach.

    Science.gov (United States)

    Laghari, Samreen; Niazi, Muaz A

    2016-01-01

    Computer Networks have a tendency to grow at an unprecedented scale. Modern networks involve not only computers but also a wide variety of other interconnected devices ranging from mobile phones to other household items fitted with sensors. This vision of the "Internet of Things" (IoT) implies an inherent difficulty in modeling problems. It is practically impossible to implement and test all scenarios for large-scale and complex adaptive communication networks as part of Complex Adaptive Communication Networks and Environments (CACOONS). The goal of this study is to explore the use of Agent-based Modeling as part of the Cognitive Agent-based Computing (CABC) framework to model a Complex communication network problem. We use Exploratory Agent-based Modeling (EABM), as part of the CABC framework, to develop an autonomous multi-agent architecture for managing carbon footprint in a corporate network. To evaluate the application of complexity in practical scenarios, we have also introduced a company-defined computer usage policy. The conducted experiments demonstrated two important results: Primarily CABC-based modeling approach such as using Agent-based Modeling can be an effective approach to modeling complex problems in the domain of IoT. Secondly, the specific problem of managing the Carbon footprint can be solved using a multiagent system approach.

  10. Modeling the Internet of Things, Self-Organizing and Other Complex Adaptive Communication Networks: A Cognitive Agent-Based Computing Approach.

    Directory of Open Access Journals (Sweden)

    Samreen Laghari

    Full Text Available Computer Networks have a tendency to grow at an unprecedented scale. Modern networks involve not only computers but also a wide variety of other interconnected devices ranging from mobile phones to other household items fitted with sensors. This vision of the "Internet of Things" (IoT implies an inherent difficulty in modeling problems.It is practically impossible to implement and test all scenarios for large-scale and complex adaptive communication networks as part of Complex Adaptive Communication Networks and Environments (CACOONS. The goal of this study is to explore the use of Agent-based Modeling as part of the Cognitive Agent-based Computing (CABC framework to model a Complex communication network problem.We use Exploratory Agent-based Modeling (EABM, as part of the CABC framework, to develop an autonomous multi-agent architecture for managing carbon footprint in a corporate network. To evaluate the application of complexity in practical scenarios, we have also introduced a company-defined computer usage policy.The conducted experiments demonstrated two important results: Primarily CABC-based modeling approach such as using Agent-based Modeling can be an effective approach to modeling complex problems in the domain of IoT. Secondly, the specific problem of managing the Carbon footprint can be solved using a multiagent system approach.

  11. Cooperation Networks: Endogeneity and Complexity

    CERN Document Server

    Angus, S

    2006-01-01

    Insights from the Complex Systems literature are employed to develop a computational model of truly endogenous strategic network formation. Artificial Adaptive Agents, implemented as Finite State Automata (FSA), play a modified two-player IPD game with an option to further develop the interaction space as part of their strategy. Several insights result from this minor modification: first, I find that network formation is a necessary condition for cooperation to be sustainable but that both the frequency of interaction and the degree to which edge formation impacts agent mixing are both necessary conditions for cooperative networks. Second, within the FSA-modified IPD frame-work, a rich ecology of agents and network topologies is observed and described. Third, the system dynamics are investigated and reveal that initially simple dynamics with small interaction length between agents gives way to complex, a-periodic dynamics with self-organized critical properties when interaction lengths are increased by a sing...

  12. Complex networks and computing

    Institute of Scientific and Technical Information of China (English)

    Shuigeng ZHOU; Zhongzhi ZHANG

    2009-01-01

    @@ Nowadays complex networks are pervasive in various areas of science and technology. Popular examples of complex networks include the Internet, social networks of collaboration, citations and co-authoring, as well as biological networks such as gene and protein interactions and others. Complex networks research spans across mathematics, computer science, engineering, biology and the social sciences. Even in computer science area, increasing problems are either found to be related to complex networks or studied from the perspective of complex networks, such as searching on Web and P2P networks, routing in sensor networks, language processing, software engineering etc. The interaction and mergence of complex networks and computing is inspiring new chances and challenges in computer science.

  13. Epidemic spreading in complex networks

    Institute of Scientific and Technical Information of China (English)

    Jie ZHOU; Zong-hua LIU

    2008-01-01

    The study of epidemic spreading in complex networks is currently a hot topic and a large body of results have been achieved.In this paper,we briefly review our contributions to this field,which includes the underlying mechanism of rumor propagation,the epidemic spreading in community networks,the influence of varying topology,and the influence of mobility of agents.Also,some future directions are pointed out.

  14. Emergent Complex Network Geometry

    CERN Document Server

    Wu, Zhihao; Rahmede, Christoph; Bianconi, Ginestra

    2014-01-01

    Networks are mathematical structures that are universally used to describe a large variety of complex systems such as the brain or the Internet. Characterizing the geometrical properties of these networks has become increasingly relevant for routing problems, inference and data mining. In real growing networks, topological, structural and geometrical properties emerge spontaneously from their dynamical rules. Nevertheless we still miss a model in which networks develop an emergent complex geometry. Here we show that a single two parameter network model, the growing geometrical network, can generate complex network geometries with non-trivial distribution of curvatures, combining exponential growth and small-world properties with finite spectral dimensionality. In one limit, the non-equilibrium dynamical rules of these networks can generate scale-free networks with clustering and communities, in another limit planar random geometries with non-trivial modularity. Finally we find that these properties of the geo...

  15. Network Complexity of Foodwebs

    CERN Document Server

    Standish, Russell K

    2010-01-01

    In previous work, I have developed an information theoretic complexity measure of networks. When applied to several real world food webs, there is a distinct difference in complexity between the real food web, and randomised control networks obtained by shuffling the network links. One hypothesis is that this complexity surplus represents information captured by the evolutionary process that generated the network. In this paper, I test this idea by applying the same complexity measure to several well-known artificial life models that exhibit ecological networks: Tierra, EcoLab and Webworld. Contrary to what was found in real networks, the artificial life generated foodwebs had little information difference between itself and randomly shuffled versions.

  16. Symmetry in Complex Networks

    Directory of Open Access Journals (Sweden)

    Angel Garrido

    2011-01-01

    Full Text Available In this paper, we analyze a few interrelated concepts about graphs, such as their degree, entropy, or their symmetry/asymmetry levels. These concepts prove useful in the study of different types of Systems, and particularly, in the analysis of Complex Networks. A System can be defined as any set of components functioning together as a whole. A systemic point of view allows us to isolate a part of the world, and so, we can focus on those aspects that interact more closely than others. Network Science analyzes the interconnections among diverse networks from different domains: physics, engineering, biology, semantics, and so on. Current developments in the quantitative analysis of Complex Networks, based on graph theory, have been rapidly translated to studies of brain network organization. The brain's systems have complex network features—such as the small-world topology, highly connected hubs and modularity. These networks are not random. The topology of many different networks shows striking similarities, such as the scale-free structure, with the degree distribution following a Power Law. How can very different systems have the same underlying topological features? Modeling and characterizing these networks, looking for their governing laws, are the current lines of research. So, we will dedicate this Special Issue paper to show measures of symmetry in Complex Networks, and highlight their close relation with measures of information and entropy.

  17. Transportation dynamics on networks of mobile agents

    CERN Document Server

    Yang, Han-Xin; Xie, Yan-Bo; Lai, Ying-Cheng; Wang, Bing-Hong

    2011-01-01

    Most existing works on transportation dynamics focus on networks of a fixed structure, but networks whose nodes are mobile have become widespread, such as cell-phone networks. We introduce a model to explore the basic physics of transportation on mobile networks. Of particular interest are the dependence of the throughput on the speed of agent movement and communication range. Our computations reveal a hierarchical dependence for the former while, for the latter, we find an algebraic power law between the throughput and the communication range with an exponent determined by the speed. We develop a physical theory based on the Fokker-Planck equation to explain these phenomena. Our findings provide insights into complex transportation dynamics arising commonly in natural and engineering systems.

  18. Copper complexes as therapeutic agents.

    Science.gov (United States)

    Duncan, Clare; White, Anthony R

    2012-02-01

    The importance of transition metals in biological processes has been well established. Copper (Cu) is a transition metal that can exist in oxidised and reduced states. This allows it to participate in redox and catalytic chemistry, making it a suitable cofactor for a diverse range of enzymes and molecules. Cu deficiency or toxicity is implicated in a variety of pathological conditions; therefore inorganic complexes of Cu have been investigated for their therapeutic and diagnostic potential. These Cu complexes have been shown to be effective in cancer treatment due to their cytotoxic action on tumour cells. Alternatively, Cu complexes can also modulate Cu homeostasis in the brain, resulting in protective effects in several models of neurodegeneration. In other diseases such as coronary heart disease and skin disease, the success of Cu complexes as potential therapeutics will most likely be due to their ability to increase SOD activity, leading to relief of oxidative stress. This review seeks to provide a broad insight into some of the diverse actions of Cu complexes and demonstrate the strong future for these compounds as potential therapeutic agents.

  19. Optimal Network Design for Consensus Formation: Wisdom of Networked Agents

    Directory of Open Access Journals (Sweden)

    Eugene S. Kitamura

    2014-08-01

    Full Text Available The wisdom of crowds refers to the phenomenon in which the collective knowledge of a community is greater than the knowledge of any individual. This paper proposes a network design for the fastest and slowest consensus formation under average node degree restrictions, which is one aspect of the wisdom of crowds concept. Consensus and synchronization problems are closely related to variety of issues such as collective behavior in nature, the interaction among agents as a matter of the robot control, and building efficient wireless sensor networks. However, designing networks with desirable properties is complex and it may pose a multi-constraint and multi-criterion optimization problem. For the purpose of realizing such efficient network topology, this paper presents an optimization approach to design networks for better consensus formation by focusing on the eigenvalue spectral of Laplacian matrix. In both the fastest and slowest networks presented, consensus is formed among local structures first, then on a global scale. This suggests that both local and global topology influence the networks dynamics. These findings are useful for those who seek to manage efficient consensus and synchronization in a setting that can be modeled as a multi-agent system.

  20. Wealth dynamics on complex networks

    Science.gov (United States)

    Garlaschelli, Diego; Loffredo, Maria I.

    2004-07-01

    We study a model of wealth dynamics (Physica A 282 (2000) 536) which mimics transactions among economic agents. The outcomes of the model are shown to depend strongly on the topological properties of the underlying transaction network. The extreme cases of a fully connected and a fully disconnected network yield power-law and log-normal forms of the wealth distribution, respectively. We perform numerical simulations in order to test the model on more complex network topologies. We show that the mixed form of most empirical distributions (displaying a non-smooth transition from a log-normal to a power-law form) can be traced back to a heterogeneous topology with varying link density, which on the other hand is a recently observed property of real networks.

  1. Mobile Agents in Networking and Distributed Computing

    CERN Document Server

    Cao, Jiannong

    2012-01-01

    The book focuses on mobile agents, which are computer programs that can autonomously migrate between network sites. This text introduces the concepts and principles of mobile agents, provides an overview of mobile agent technology, and focuses on applications in networking and distributed computing.

  2. Synchronization in complex networks

    Energy Technology Data Exchange (ETDEWEB)

    Arenas, A.; Diaz-Guilera, A.; Moreno, Y.; Zhou, C.; Kurths, J.

    2007-12-12

    Synchronization processes in populations of locally interacting elements are in the focus of intense research in physical, biological, chemical, technological and social systems. The many efforts devoted to understand synchronization phenomena in natural systems take now advantage of the recent theory of complex networks. In this review, we report the advances in the comprehension of synchronization phenomena when oscillating elements are constrained to interact in a complex network topology. We also overview the new emergent features coming out from the interplay between the structure and the function of the underlying pattern of connections. Extensive numerical work as well as analytical approaches to the problem are presented. Finally, we review several applications of synchronization in complex networks to different disciplines: biological systems and neuroscience, engineering and computer science, and economy and social sciences.

  3. Complex Semantic Networks

    Science.gov (United States)

    Teixeira, G. M.; Aguiar, M. S. F.; Carvalho, C. F.; Dantas, D. R.; Cunha, M. V.; Morais, J. H. M.; Pereira, H. B. B.; Miranda, J. G. V.

    Verbal language is a dynamic mental process. Ideas emerge by means of the selection of words from subjective and individual characteristics throughout the oral discourse. The goal of this work is to characterize the complex network of word associations that emerge from an oral discourse from a discourse topic. Because of that, concepts of associative incidence and fidelity have been elaborated and represented the probability of occurrence of pairs of words in the same sentence in the whole oral discourse. Semantic network of words associations were constructed, where the words are represented as nodes and the edges are created when the incidence-fidelity index between pairs of words exceeds a numerical limit (0.001). Twelve oral discourses were studied. The networks generated from these oral discourses present a typical behavior of complex networks and their indices were calculated and their topologies characterized. The indices of these networks obtained from each incidence-fidelity limit exhibit a critical value in which the semantic network has maximum conceptual information and minimum residual associations. Semantic networks generated by this incidence-fidelity limit depict a pattern of hierarchical classes that represent the different contexts used in the oral discourse.

  4. Advances in network complexity

    CERN Document Server

    Dehmer, Matthias; Emmert-Streib, Frank

    2013-01-01

    A well-balanced overview of mathematical approaches to describe complex systems, ranging from chemical reactions to gene regulation networks, from ecological systems to examples from social sciences. Matthias Dehmer and Abbe Mowshowitz, a well-known pioneer in the field, co-edit this volume and are careful to include not only classical but also non-classical approaches so as to ensure topicality. Overall, a valuable addition to the literature and a must-have for anyone dealing with complex systems.

  5. Sensitivity of Complex Networks

    CERN Document Server

    Angulo, Marco Tulio; Liu, Yang-Yu; Barabási, Albert-László

    2016-01-01

    The sensitivity (i.e. dynamic response) of complex networked systems has not been well understood, making difficult to predict whether new macroscopic dynamic behavior will emerge even if we know exactly how individual nodes behave and how they are coupled. Here we build a framework to quantify the sensitivity of complex networked system of coupled dynamic units. We characterize necessary and sufficient conditions for the emergence of new macroscopic dynamic behavior in the thermodynamic limit. We prove that these conditions are satisfied only for architectures with power-law degree distributions. Surprisingly, we find that highly connected nodes (i.e. hubs) only dominate the sensitivity of the network up to certain critical frequency.

  6. Complexity of Public Transport Networks

    Institute of Scientific and Technical Information of China (English)

    LU Huapu; SHI Ye

    2007-01-01

    The theory of complex networks was used to classify public transport networks into public transportation route networks, public transportation transfer networks, and bus station networks. The practical significance of the network parameters was then analyzed. The public transport networks in Langfang, Jining, and Dalian were then chosen as specific research cases. The results show that the public transportation networks have the characteristics of complex networks. In addition, the urban transportation network parameters all significantly affect the accessibility, convenience, and terrorist security capability of the urban public transportation network. The results link the findings with the actual situations to explore means to solve transportation system problems.

  7. Consensus in Directed Networks of Agents With Nonlinear Dynamics

    NARCIS (Netherlands)

    Yu, Wenwu; Chen, Guanrong; Cao, Ming; Qu, Z.

    2011-01-01

    This technical note studies the consensus problem for cooperative agents with nonlinear dynamics in a directed network. Both local and global consensus are defined and investigated. Techniques for studying the synchronization in such complex networks are exploited to establish various sufficient con

  8. Agent-based modeling and network dynamics

    CERN Document Server

    Namatame, Akira

    2016-01-01

    The book integrates agent-based modeling and network science. It is divided into three parts, namely, foundations, primary dynamics on and of social networks, and applications. The book begins with the network origin of agent-based models, known as cellular automata, and introduce a number of classic models, such as Schelling’s segregation model and Axelrod’s spatial game. The essence of the foundation part is the network-based agent-based models in which agents follow network-based decision rules. Under the influence of the substantial progress in network science in late 1990s, these models have been extended from using lattices into using small-world networks, scale-free networks, etc. The book also shows that the modern network science mainly driven by game-theorists and sociophysicists has inspired agent-based social scientists to develop alternative formation algorithms, known as agent-based social networks. The book reviews a number of pioneering and representative models in this family. Upon the gi...

  9. Multi-agent and complex systems

    CERN Document Server

    Ren, Fenghui; Fujita, Katsuhide; Zhang, Minjie; Ito, Takayuki

    2017-01-01

    This book provides a description of advanced multi-agent and artificial intelligence technologies for the modeling and simulation of complex systems, as well as an overview of the latest scientific efforts in this field. A complex system features a large number of interacting components, whose aggregate activities are nonlinear and self-organized. A multi-agent system is a group or society of agents which interact with others cooperatively and/or competitively in order to reach their individual or common goals. Multi-agent systems are suitable for modeling and simulation of complex systems, which is difficult to accomplish using traditional computational approaches.

  10. Complex networks analysis in socioeconomic models

    CERN Document Server

    Varela, Luis M; Ausloos, Marcel; Carrete, Jesus

    2014-01-01

    This chapter aims at reviewing complex networks models and methods that were either developed for or applied to socioeconomic issues, and pertinent to the theme of New Economic Geography. After an introduction to the foundations of the field of complex networks, the present summary adds insights on the statistical mechanical approach, and on the most relevant computational aspects for the treatment of these systems. As the most frequently used model for interacting agent-based systems, a brief description of the statistical mechanics of the classical Ising model on regular lattices, together with recent extensions of the same model on small-world Watts-Strogatz and scale-free Albert-Barabasi complex networks is included. Other sections of the chapter are devoted to applications of complex networks to economics, finance, spreading of innovations, and regional trade and developments. The chapter also reviews results involving applications of complex networks to other relevant socioeconomic issues, including res...

  11. Recent Advances in Complex Networks

    Institute of Scientific and Technical Information of China (English)

    2002-01-01

    Dramatic advances in the field of complex networks have been witnessed in the past few years. This paper reviews some important results in this direction of rapidly evolving research, with emphasis on the relationship between the dynamics and the topology of complex networks. Basic quantities and typical examples of various complex networks are described. Robustness of connectivity and epidemic dynamics in complex networks are evaluated.

  12. Articulation Points in Complex Networks

    CERN Document Server

    Tian, Liang; Shi, Da-Ning; Liu, Yang-Yu

    2016-01-01

    An articulation point in a network is a node whose removal disconnects the network. Those nodes play key roles in ensuring connectivity of many real-world networks, from infrastructure networks to protein interaction networks and terrorist communication networks. Despite their fundamental importance, a general framework of studying articulation points in complex networks is lacking. Here we develop analytical tools to study key issues pertinent to articulation points, e.g. the expected number of them and the network vulnerability against their removal, in an arbitrary complex network. We find that a greedy articulation point removal process provides us a novel perspective on the organizational principles of complex networks. Moreover, this process is associated with two fundamentally different types of percolation transitions with a rich phase diagram. Our results shed light on the design of more resilient infrastructure networks and the effective destruction of terrorist communication networks.

  13. Articulation points in complex networks

    Science.gov (United States)

    Tian, Liang; Bashan, Amir; Shi, Da-Ning; Liu, Yang-Yu

    2017-01-01

    An articulation point in a network is a node whose removal disconnects the network. Those nodes play key roles in ensuring connectivity of many real-world networks, from infrastructure networks to protein interaction networks and terrorist communication networks. Despite their fundamental importance, a general framework of studying articulation points in complex networks is lacking. Here we develop analytical tools to study key issues pertinent to articulation points, such as the expected number of them and the network vulnerability against their removal, in an arbitrary complex network. We find that a greedy articulation point removal process provides us a different perspective on the organizational principles of complex networks. Moreover, this process results in a rich phase diagram with two fundamentally different types of percolation transitions. Our results shed light on the design of more resilient infrastructure networks and the effective destruction of terrorist communication networks.

  14. Articulation points in complex networks

    Science.gov (United States)

    Tian, Liang; Bashan, Amir; Shi, Da-Ning; Liu, Yang-Yu

    2017-01-01

    An articulation point in a network is a node whose removal disconnects the network. Those nodes play key roles in ensuring connectivity of many real-world networks, from infrastructure networks to protein interaction networks and terrorist communication networks. Despite their fundamental importance, a general framework of studying articulation points in complex networks is lacking. Here we develop analytical tools to study key issues pertinent to articulation points, such as the expected number of them and the network vulnerability against their removal, in an arbitrary complex network. We find that a greedy articulation point removal process provides us a different perspective on the organizational principles of complex networks. Moreover, this process results in a rich phase diagram with two fundamentally different types of percolation transitions. Our results shed light on the design of more resilient infrastructure networks and the effective destruction of terrorist communication networks. PMID:28139697

  15. Correlation dimension of complex networks

    CERN Document Server

    Lacasa, Lucas

    2012-01-01

    We propose a new measure to characterize the dimension of complex networks based on the ergodic theory of dynamical systems. This measure is derived from the correlation sum of a trajectory generated by a random walker navigating the network, and extends the classical Grassberger-Procaccia algorithm to the context of complex networks. The method is validated with reliable results for both synthetic networks and real-world networks such as the world air-transportation network or urban networks, and provides a computationally fast way for estimating the dimensionality of networks which only relies on the local information provided by the walkers.

  16. SYNCHRONIZATION IN COMPLEX DYNAMICAL NETWORKS

    Institute of Scientific and Technical Information of China (English)

    WANG Xiaofan; CHEN Guanrong

    2003-01-01

    In the past few years, the discovery of small-world and scale-free properties of many natural and artificial complex networks has stimulated increasing interest in further studying the underlying organizing principles of various complex networks. This has led to significant advances in understanding the relationship between the topology and the dynamics of such complex networks. This paper reviews some recent research works on the synchronization phenomenon in various dynamical networks with small-world and scalefree connections.

  17. Applying Web Services with Mobile Agents for Computer Network Management

    Directory of Open Access Journals (Sweden)

    Mydhili K.Nair

    2011-03-01

    Full Text Available The exponential rise in complexity of the underlying network elements of a computer network makes itsManagement an intricate, multifaceted and complex problem to solve. With every passing decade, newtechnologies are developed to ease this problem of Network Management. The last decade of the premillenniumera saw the peak of CORBA and Mobile Agent Based implementations, while the first decadeof post millennium saw the emergence of Web Services. All of these technologies evolved as independent,self-contained implementation streams. There is a genuine dearth in finding authentic research outcomeswhere quantifiable, measureable benefits of convergence of these technologies applied to NetworkManagement are put forth. This paper aims to fill this research gap. Here we put forth the experimentalresults obtained of a framework we developed in-house for Network Management that combined twoseemingly divergent distributed computing technologies, namely, Web Services and Mobile Agents.

  18. Modelling cooperative agents in infrastructure networks

    NARCIS (Netherlands)

    Ligtvoet, A.; Chappin, E.J.L.; Stikkelman, R.M.

    2010-01-01

    This paper describes the translation of concepts of cooperation into an agent-based model of an industrial network. It first addresses the concept of cooperation and how this could be captured as heuristical rules within agents. Then it describes tests using these heuristics in an abstract model of

  19. Structural complexity of quantum networks

    Energy Technology Data Exchange (ETDEWEB)

    Siomau, Michael [Physics Department, Jazan University, P.O.Box 114, 45142 Jazan (Saudi Arabia); Network Dynamics, Max Planck Institute for Dynamics and Self-Organization (MPIDS), 37077 Göttingen (Germany)

    2016-06-10

    Quantum network is a set of nodes connected with channels, through which the nodes communicate photons and classical information. Classical structural complexity of a quantum network may be defined through its physical structure, i.e. mutual position of nodes and channels connecting them. We show here that the classical structural complexity of a quantum network does not restrict the structural complexity of entanglement graphs, which may be created in the quantum network with local operations and classical communication. We show, in particular, that 1D quantum network can simulate both simple entanglement graphs such as lattices and random graphs and complex small-world graphs.

  20. Collaborative learning agents supporting service network management

    NARCIS (Netherlands)

    Mulder, W.; Meijer, G.R.; Adriaans, P.W.

    2008-01-01

    Service oriented systems need to be maintained to keep the requested level of service. This is challenge in large grid- and saas based networks that are managed by numerous entities. This paper is about supporting multi agent systems that operate in the network and support its management by learning

  1. Collaborative learning agents supporting service network management

    NARCIS (Netherlands)

    Mulder, W.; Meijer, G.R.; Adriaans, P.W.

    2008-01-01

    Service oriented systems need to be maintained to keep the requested level of service. This is challenge in large grid- and saas based networks that are managed by numerous entities. This paper is about supporting multi agent systems that operate in the network and support its management by learning

  2. Synchronization in Triangled Complex Networks

    Institute of Scientific and Technical Information of China (English)

    LU Xin-Biao; LI Xiang; WANG Xiao-Fan

    2006-01-01

    Using a tunable clustering coefficient model withoutchanging the degree distribution, we investigate the effect of clustering coefficient on synchronization of networks with both unweighted and weighted couplings. For several typical categories of complex networks, the more triangles are in the networks, the worse the synchronizability of the networks is.

  3. Complex networks analysis of language complexity

    CERN Document Server

    Amancio, Diego R; Oliveira, Osvaldo N; Costa, Luciano da F; 10.1209/0295-5075/100/58002

    2013-01-01

    Methods from statistical physics, such as those involving complex networks, have been increasingly used in quantitative analysis of linguistic phenomena. In this paper, we represented pieces of text with different levels of simplification in co-occurrence networks and found that topological regularity correlated negatively with textual complexity. Furthermore, in less complex texts the distance between concepts, represented as nodes, tended to decrease. The complex networks metrics were treated with multivariate pattern recognition techniques, which allowed us to distinguish between original texts and their simplified versions. For each original text, two simplified versions were generated manually with increasing number of simplification operations. As expected, distinction was easier for the strongly simplified versions, where the most relevant metrics were node strength, shortest paths and diversity. Also, the discrimination of complex texts was improved with higher hierarchical network metrics, thus point...

  4. Multi-Agent Reinforcement Learning and Adaptive Neural Networks.

    Science.gov (United States)

    2007-11-02

    learning method. The objective was to study the utility of reinforcement learning as an approach to complex decentralized control problems. The major...accomplishment was a detailed study of multi-agent reinforcement learning applied to a large-scale decentralized stochastic control problem. This study...included a very successful demonstration that a multi-agent reinforcement learning system using neural networks could learn high-performance

  5. Network Management using Multi-Agents System

    Directory of Open Access Journals (Sweden)

    Nestor DUQUE

    2013-07-01

    Full Text Available This paper aims to present a multiagent system for network management. The models developed for the proposed system defines certain intelligent agents interact to achieve the objectives and requirements of the multiagent organization.These agents have the property of being adaptive, acquire knowledge and skills to make decisions according to the actual state of the network that is represented in the information base, MIB, SNMP devices. The ideal state of the network policy is defined by the end user entered, which contain the value that should have performance variables and other parameters such as the frequency with which these variables should be monitored.. An agent based architecture increase the integration, adaptability, cooperation, autonomy and the efficient operation in heterogeneous environment in the network supervision. 

  6. Network Management using Multi-Agents System

    Directory of Open Access Journals (Sweden)

    Gustavo ISAZA

    2012-12-01

    Full Text Available This paper aims to present a multiagent system for network management. The models developed for the proposed system defines certain intelligent agents interact to achieve the objectives and requirements of the multiagent organization.These agents have the property of being adaptive, acquire knowledge and skills to make decisions according to the actual state of the network that is represented in the information base, MIB, SNMP devices. The ideal state of the network policy is defined by the end user entered, which contain the value that should have performance variables and other parameters such as the frequency with which these variables should be monitored.. An agent based architecture increase the integration, adaptability, cooperation, autonomy and the efficient operation in heterogeneous environment in the network supervision. 

  7. Fault Reconnaissance Agent for Sensor Networks

    Directory of Open Access Journals (Sweden)

    Elhadi M. Shakshuki

    2010-01-01

    Full Text Available One of the key prerequisite for a scalable, effective and efficient sensor network is the utilization of low-cost, low-overhead and high-resilient fault-inference techniques. To this end, we propose an intelligent agent system with a problem solving capability to address the issue of fault inference in sensor network environments. The intelligent agent system is designed and implemented at base-station side. The core of the agent system – problem solver – implements a fault-detection inference engine which harnesses Expectation Maximization (EM algorithm to estimate fault probabilities of sensor nodes. To validate the correctness and effectiveness of the intelligent agent system, a set of experiments in a wireless sensor testbed are conducted. The experimental results show that our intelligent agent system is able to precisely estimate the fault probability of sensor nodes.

  8. Graph distance for complex networks

    Science.gov (United States)

    Shimada, Yutaka; Hirata, Yoshito; Ikeguchi, Tohru; Aihara, Kazuyuki

    2016-10-01

    Networks are widely used as a tool for describing diverse real complex systems and have been successfully applied to many fields. The distance between networks is one of the most fundamental concepts for properly classifying real networks, detecting temporal changes in network structures, and effectively predicting their temporal evolution. However, this distance has rarely been discussed in the theory of complex networks. Here, we propose a graph distance between networks based on a Laplacian matrix that reflects the structural and dynamical properties of networked dynamical systems. Our results indicate that the Laplacian-based graph distance effectively quantifies the structural difference between complex networks. We further show that our approach successfully elucidates the temporal properties underlying temporal networks observed in the context of face-to-face human interactions.

  9. Complex networks theory for analyzing metabolic networks

    Institute of Scientific and Technical Information of China (English)

    ZHAO Jing; YU Hong; LUO Jianhua; CAO Z.W.; LI Yixue

    2006-01-01

    One of the main tasks of post-genomic informatics is to systematically investigate all molecules and their interactions within a living cell so as to understand how these molecules and the interactions between them relate to the function of the organism,while networks are appropriate abstract description of all kinds of interactions. In the past few years, great achievement has been made in developing theory of complex networks for revealing the organizing principles that govern the formation and evolution of various complex biological, technological and social networks. This paper reviews the accomplishments in constructing genome-based metabolic networks and describes how the theory of complex networks is applied to analyze metabolic networks.

  10. Statistical mechanics of complex networks

    CERN Document Server

    Rubi, Miguel; Diaz-Guilera, Albert

    2003-01-01

    Networks can provide a useful model and graphic image useful for the description of a wide variety of web-like structures in the physical and man-made realms, e.g. protein networks, food webs and the Internet. The contributions gathered in the present volume provide both an introduction to, and an overview of, the multifaceted phenomenology of complex networks. Statistical Mechanics of Complex Networks also provides a state-of-the-art picture of current theoretical methods and approaches.

  11. Three Types of Network Complexity Pyramid

    Institute of Scientific and Technical Information of China (English)

    FANG; Jin-qing; LI; Yong; LIU; Qiang

    2012-01-01

    <正>Exploring the complexity and diversity of complex networks have been very challenging issues in network science and engineering. Among them exploring the network complexity pyramids (NCP) are one of important expressions in network complexity. So far as we have proposed the three types of the network complexity pyramid (NCP). The first type of NCP is the network model complexity pyramid with

  12. Competitive Dynamics on Complex Networks

    CERN Document Server

    Zhao, Jiuhua; Wang, Xiaofan

    2014-01-01

    We consider a dynamical network model in which two competitors have fixed and different states, and each normal agent adjusts its state according to a distributed consensus protocol. The state of each normal agent converges to a steady value which is a convex combination of the competitors' states, and is independent of the initial states of agents. This implies that the competition result is fully determined by the network structure and positions of competitors in the network. We compute an Influence Matrix (IM) in which each element characterizing the influence of an agent on another agent in the network. We use the IM to predict the bias of each normal agent and thus predict which competitor will win. Furthermore, we compare the IM criterion with seven node centrality measures to predict the winner. We find that the competitor with higher Katz Centrality in an undirected network or higher PageRank in a directed network is much more likely to be the winner. These findings may shed new light on the role of n...

  13. Epidemic dynamics on complex networks

    Institute of Scientific and Technical Information of China (English)

    ZHOU Tao; FU Zhongqian; WANG Binghong

    2006-01-01

    Recently, motivated by the pioneer work in revealing the small-world effect and scale-free property of various real-life networks, many scientists devote themselves to studying complex networks. One of the ultimate goals is to understand how the topological structures affect the dynamics upon networks. In this paper, we give a brief review on the studies of epidemic dynamics on complex networks, including the description of classical epidemic models, the epidemic spread on small-world and scale-free networks, and network immunization. Finally, perspectives and some interesting problems are proposed.

  14. Complex Dynamics in Communication Networks

    CERN Document Server

    Kocarev, Ljupco

    2005-01-01

    Computer and communication networks are among society's most important infrastructures. The internet, in particular, is a giant global network of networks without central control or administration. It is a paradigm of a complex system, where complexity may arise from different sources: topological structure, network evolution, connection and node diversity, or dynamical evolution. The present volume is the first book entirely devoted to the new and emerging field of nonlinear dynamics of TCP/IP networks. It addresses both scientists and engineers working in the general field of communication networks.

  15. Using Mobile Agents and Overlay Networks to Secure Electrical Networks

    Energy Technology Data Exchange (ETDEWEB)

    Dawes, Neal A.; Prosser, Bryan J.; Fulp, Errin W.; McKinnon, Archibald D.

    2013-02-11

    ABSTRACT The use of wandering, mobile agents can provide a robust approach for managing, monitoring, and securing electrical distribution networks. However, the topological structure of electrical networks can affect system performance. For example, if the multi-agent system relies on a regular inspection rate (on average, points of interest are inspected with equal frequency), then locations that are not well connected will on average be inspected less frequently. This paper discusses creation and use of overlay networks that create a virtual grid graph can provide faster coverage and a more uniform average agent sampling rate. Using overlays agents wander a virtual neighborhood consisting of only points of interest that are interconnected in a regular fashion (each point has the same number of neighbors). Experimental results will show that an overlay can often provide better network coverage and a more uniform inspection rate, which can improve cyber security by providing a faster detection of threats.

  16. Wireless network topology for monitoring mobile agents

    Science.gov (United States)

    Fraser, Matthew J.; James, Daniel A.; Thiel, David V.

    2005-02-01

    A wireless network of multiple sensor nodes for monitoring large numbers of mobile agents is described and investigated. Wireless monitoring provides time critical information from a number of data sources allowing near real-time analysis of the collected data. The developed wireless network provides a moderate data rate, is able to support many wireless nodes and is a low power solution. Novel network structures have been developed to satisfy all of these requirements. This paper evaluates a number of currently available wireless communication protocols, concluding that a Bluetooth wireless network satisfies the above criteria. To support a large number of devices, topologies using inter-piconet and piconet sharing methods have been developed. These network structures are outlined in detail and have been developed with the current Bluetooth hardware limitations in mind. The proposed wireless networks have been developed to be implemented with current Bluetooth hardware. A summary of network performance is included for each developed network structure, and from these figures an appropriate network structure has been chosen that satisfies the requirements of a wireless sensor network for monitoring mobile agents.

  17. Reconfigurable networking for coordinated multi-agent sensing and communications.

    Science.gov (United States)

    Sutton, Jeffrey P; Jamieson, Ian M D

    2002-12-01

    An implementation of a neurally-inspired system comprised of multiple mobile sensor-effector agents is described. Each agent has features of a complex neural network that is able to communicate and adjust its behavior depending upon a variety of parameters, including changes in the environment and the behavior of other agents. The system as a whole spatiotemporally reconfigures itself to perform coordinated behaviors not obtainable with single agents. Transient clustering of agents into functional subsystems to perform specific tasks generates a "system of systems" architecture. The interesting findings of this dynamic platform show that (a) the formation and dissolution of functional subsystems is a local phenomenon without the need for global control and (b) minimal intermittent communication among the agents can yield large-scale, coordinated, goal-driven behavior under a wide range of conditions.

  18. Organophosphate Nerve Agent Detection with Europium Complexes

    OpenAIRE

    Schwierking, Jake R.; Laird W. Menzel; E. Roland Menzel

    2004-01-01

    We explore the detection of paraoxon, a model compound for nonvolatile organophosphate nerve agents such as VX. The detection utilizes europium complexes with 1,10 phenanthroline and thenoyltrifluoroacetone as sensitizing ligands. Both europium luminescence quenching and luminescence enhancement modalities are involved in the detection, which is simple, rapid, and sensitive. It is adaptable as well to the more volatile fluorophosphate nerve agents. It involves nothing more than visual lumines...

  19. NETWORK MANAGEMENT WITH SECURED MOBILE AGENT

    Institute of Scientific and Technical Information of China (English)

    迈克尔; 徐良贤

    2002-01-01

    Network management scheme must consider security challenges for the Mobile Agent paradigm to be accepted in the Internet computing world. Techniques to provide security solutions have been proposed and some have achieved good results. For example, it is possible to launch a code with a guarantee that it cannot attack the hosting sites. The main problem remaining, however, is protecting the mobile code against malicious service providers, the host problem. This paper proposed a Mobile Agent management scheme in a hierarchical level that provides to user a reliable and flexible global access to internet/network information services. We further described a protection mechanism to Mobile Agents against malicious hosts. As an effort to address host problems we first identify the kinds of attack that may be performed by malicious hosts, and propose a mechanism to prevent these attacks. At each agent host we introduce a trusted third party entity on each server called Secure Service Station (SSS) to carry out security actions.

  20. Complex systems and networks dynamics, controls and applications

    CERN Document Server

    Yu, Xinghuo; Chen, Guanrong; Yu, Wenwu

    2016-01-01

    This elementary book provides some state-of-the-art research results on broad disciplinary sciences on complex networks. It presents an in-depth study with detailed description of dynamics, controls and applications of complex networks. The contents of this book can be summarized as follows. First, the dynamics of complex networks, for example, the cluster dynamic analysis by using kernel spectral methods, community detection algorithms in bipartite networks, epidemiological modeling with demographics and epidemic spreading on multi-layer networks, are studied. Second, the controls of complex networks are investigated including topics like distributed finite-time cooperative control of multi-agent systems by applying homogenous-degree and Lyapunov methods, composite finite-time containment control for disturbed second-order multi-agent systems, fractional-order observer design of multi-agent systems, chaos control and anticontrol of complex systems via Parrondos game and many more. Third, the applications of ...

  1. Epidemic Diffusion on Complex Networks

    Institute of Scientific and Technical Information of China (English)

    WU Xiao-Yan; LIU Zong-Hua

    2007-01-01

    Boyh diffusion and epidemic are well studied in the stochastic systems and complex networks,respetively.Here we combine these two fields and study epidemic diffusion in complex networks.Instead of studying the threshold of infection,which was focused on in previous works,we focus on the diffusion.behaviour.We find that the epidemic diffusion in a complex network is an anomalous superdiffusion with varyingg diffusion exponext γand that γ is influenced seriously by the network structure,such as the clustering coefficient and the degree distribution.Numerical simulations have confirmed the theoretical predictions.

  2. Multifractal analysis of complex networks

    Institute of Scientific and Technical Information of China (English)

    Wang Dan-Ling; Yu Zu-Guo; Anh V

    2012-01-01

    Complex networks have recently attracted much attention in diverse areas of science and technology.Many networks such as the WWW and biological networks are known to display spatial heterogeneity which can be characterized by their fractal dimensions.Multifractal analysis is a useful way to systematically describe the spatial heterogeneity of both theoretical and experimental fractal patterns.In this paper,we introduce a new box-covering algorithm for muttifractal analysis of complex networks.This algorithm is used to calculate the generalized fractal dimensions Dq of some theoretical networks,namely scale-free networks,small world networks,and random networks,and one kind of real network,namely protein-protein interaction networks of different species.Our numerical results indicate the existence of multifractality in scale-free networks and protein-protein interaction networks,while the multifractal behavior is not clear-cut for small world networks and random networks.The possible variation of Dq due to changes in the parameters of the theoretical network models is also discussed.

  3. Synchronization in uncertain complex networks

    Science.gov (United States)

    Chen, Maoyin; Zhou, Donghua

    2006-03-01

    We consider the problem of synchronization in uncertain generic complex networks. For generic complex networks with unknown dynamics of nodes and unknown coupling functions including uniform and nonuniform inner couplings, some simple linear feedback controllers with updated strengths are designed using the well-known LaSalle invariance principle. The state of an uncertain generic complex network can synchronize an arbitrary assigned state of an isolated node of the network. The famous Lorenz system is stimulated as the nodes of the complex networks with different topologies. We found that the star coupled and scale-free networks with nonuniform inner couplings can be in the state of synchronization if only a fraction of nodes are controlled.

  4. An Application of Mobile Agent System in Network Management

    Institute of Scientific and Technical Information of China (English)

    YANGChen-xiang; DUJun-ping; YINYi-xin

    2004-01-01

    This paper describes an application of a reusable mobile agent system in network management. A mobile agent reusable system is constructed to realize a new method in forming mobile agent systems. By using this method, an agent can change its route dynamically without making any change to its specific behavior. By classifying mobile agents into two categories, the task agent can be reusable in different networks. In this way, a mobile agent system can easily carry out network management tasks.

  5. On convexity in complex networks

    CERN Document Server

    Marc, Tilen

    2016-01-01

    Metric graph properties lie in the heart of the analysis of complex networks, while in this paper we study their convexity. We analyze the expansion of convex subsets of nodes in empirical networks and also convexity of small subgraphs known as graphlets. We demonstrate that convexity is an inherent property of complex networks not present in a random graph. According to our perception of convexity, a convex network is such in which every connected subset of nodes induces a convex subgraph. Especially convex are technological networks and social collaboration graphs, whereas food webs are the only networks studied that are truly non-convex. Many other networks can be divided into a non-convex core surrounded by a convex periphery. We interpret convexity in terms of redundancy of shortest paths in a network and discuss possible applications.

  6. Bridges in Complex Networks

    CERN Document Server

    Wu, Ang-Kun; Liu, Yang-Yu

    2016-01-01

    A bridge in a graph is an edge whose removal disconnects the graph and increases the number of connected components. We calculate the fraction of bridges in a wide range of real-world networks and their randomized counterparts. We find that real networks typically have more bridges than their completely randomized counterparts, but very similar fraction of bridges as their degree-preserving randomizations. We define a new edge centrality measure, called bridgeness, to differentiate the importance of a bridge in damaging a network. We find that certain real networks have very large average and variance of bridgeness compared to their degree-preserving randomizations and other real networks. Finally, we offer an analytical framework to calculate the bridge fraction and average bridgeness for uncorrelated random networks with arbitrary degree distributions.

  7. Forman curvature for complex networks

    Science.gov (United States)

    Sreejith, R. P.; Mohanraj, Karthikeyan; Jost, Jürgen; Saucan, Emil; Samal, Areejit

    2016-06-01

    We adapt Forman’s discretization of Ricci curvature to the case of undirected networks, both weighted and unweighted, and investigate the measure in a variety of model and real-world networks. We find that most nodes and edges in model and real networks have a negative curvature. Furthermore, the distribution of Forman curvature of nodes and edges is narrow in random and small-world networks, while the distribution is broad in scale-free and real-world networks. In most networks, Forman curvature is found to display significant negative correlation with degree and centrality measures. However, Forman curvature is uncorrelated with clustering coefficient in most networks. Importantly, we find that both model and real networks are vulnerable to targeted deletion of nodes with highly negative Forman curvature. Our results suggest that Forman curvature can be employed to gain novel insights on the organization of complex networks.

  8. Characteristic exponents of complex networks

    CERN Document Server

    Nicosia, Vincenzo; Latora, Vito

    2013-01-01

    We propose a method to characterize and classify complex networks based on the time series generated by random walks and different node properties. The analysis of the fluctuations of the time series reveals the presence of long-range correlations, and allows to define, for each network, a set of characteristic exponents that capture its essential structural properties. By considering a large data set of real-world networks, we show that the characteristic exponents can be used to classify complex networks according to their function, and are able to discriminate social from biological and technological systems.

  9. Organoiridium complexes: anticancer agents and catalysts.

    Science.gov (United States)

    Liu, Zhe; Sadler, Peter J

    2014-04-15

    Iridium is a relatively rare precious heavy metal, only slightly less dense than osmium. Researchers have long recognized the catalytic properties of square-planar Ir(I) complexes, such as Crabtree's hydrogenation catalyst, an organometallic complex with cyclooctadiene, phosphane, and pyridine ligands. More recently, chemists have developed half-sandwich pseudo-octahedral pentamethylcyclopentadienyl Ir(III) complexes containing diamine ligands that efficiently catalyze transfer hydrogenation reactions of ketones and aldehydes in water using H2 or formate as the hydrogen source. Although sometimes assumed to be chemically inert, the reactivity of low-spin 5d(6) Ir(III) centers is highly dependent on the set of ligands. Cp* complexes with strong σ-donor C^C-chelating ligands can even stabilize Ir(IV) and catalyze the oxidation of water. In comparison with well developed Ir catalysts, Ir-based pharmaceuticals are still in their infancy. In this Account, we review recent developments in organoiridium complexes as both catalysts and anticancer agents. Initial studies of anticancer activity with organoiridium complexes focused on square-planar Ir(I) complexes because of their structural and electronic similarity to Pt(II) anticancer complexes such as cisplatin. Recently, researchers have studied half-sandwich Ir(III) anticancer complexes. These complexes with the formula [(Cp(x))Ir(L^L')Z](0/n+) (with Cp* or extended Cp* and L^L' = chelated C^N or N^N ligands) have a much greater potency (nanomolar) toward a range of cancer cells (especially leukemia, colon cancer, breast cancer, prostate cancer, and melanoma) than cisplatin. Their mechanism of action may involve both an attack on DNA and a perturbation of the redox status of cells. Some of these complexes can form Ir(III)-hydride complexes using coenzyme NAD(P)H as a source of hydride to catalyze the generation of H2 or the reduction of quinones to semiquinones. Intriguingly, relatively unreactive organoiridium

  10. Intelligent Complex Evolutionary Agent-Based Systems

    Science.gov (United States)

    Iantovics, Barna; Enǎchescu, Cǎlin

    2009-04-01

    In this paper, we investigate the possibility to develop intelligent agent-based complex systems that use evolutionary learning techniques in order to adapt for the efficient solving of the problems by reorganizing their structure. For this investigation is proposed a complex multiagent system called EAMS (Evolutionary Adaptive Multiagent System), which using an evolutionary learning technique can learn different patterns of reorganization. The realized study proves that evolutionary techniques successfully can be used to create complex multiagent systems capable to intelligently reorganize their structure during their life cycle. The practical establishment of the intelligence of a computational system in generally, an agent-based system in particularly consists in how efficiently and flexibly the system can solve difficult problems.

  11. Organophosphate Nerve Agent Detection with Europium Complexes

    Directory of Open Access Journals (Sweden)

    Jake R. Schwierking

    2004-01-01

    Full Text Available We explore the detection of paraoxon, a model compound for nonvolatile organophosphate nerve agents such as VX. The detection utilizes europium complexes with 1,10 phenanthroline and thenoyltrifluoroacetone as sensitizing ligands. Both europium luminescence quenching and luminescence enhancement modalities are involved in the detection, which is simple, rapid, and sensitive. It is adaptable as well to the more volatile fluorophosphate nerve agents. It involves nothing more than visual luminescence observation under sample illumination by an ordinary hand-held ultraviolet lamp.

  12. Learning about knowledge: A complex network approach

    CERN Document Server

    Costa, L F

    2006-01-01

    This article describes an approach to modeling of knowledge acquisition in terms of complex networks and walks. Each subset of knowledge is represented as a node, and relationship between such knowledge are represented as edges. Two types of edges are considered, corresponding to logical equivalence and implication. Multiple conditional implications are also considered, implying that a node can only be reached after visiting previously a set of nodes (the conditions). It is shown that hierarchical networks, involving a series of interconnected layers containing a connected subnetwork, provides a simple and natural means for avoiding deadlocks, i.e. unreachable nodes. The process of knowledge acquisition can then be simulated by considering a single agent moving along the nodes and edges, starting from the lowest layer. Several configurations of such hierarchical knowledge networks are simulated and the performance of the agent quantified in terms of the percentage of visited nodes after each movement. The Bar...

  13. Coordinating complex problem-solving among distributed intelligent agents

    Science.gov (United States)

    Adler, Richard M.

    1992-01-01

    A process-oriented control model is described for distributed problem solving. The model coordinates the transfer and manipulation of information across independent networked applications, both intelligent and conventional. The model was implemented using SOCIAL, a set of object-oriented tools for distributing computing. Complex sequences of distributed tasks are specified in terms of high level scripts. Scripts are executed by SOCIAL objects called Manager Agents, which realize an intelligent coordination model that routes individual tasks to suitable server applications across the network. These tools are illustrated in a prototype distributed system for decision support of ground operations for NASA's Space Shuttle fleet.

  14. Advances in cobalt complexes as anticancer agents.

    Science.gov (United States)

    Munteanu, Catherine R; Suntharalingam, Kogularamanan

    2015-08-21

    The evolution of resistance to traditional platinum-based anticancer drugs has compelled researchers to investigate the cytostatic properties of alternative transition metal-based compounds. The anticancer potential of cobalt complexes has been extensively studied over the last three decades, and much time has been devoted to understanding their mechanisms of action. This perspective catalogues the development of antiproliferative cobalt complexes, and provides an in depth analysis of their mode of action. Early studies on simple cobalt coordination complexes, Schiff base complexes, and cobalt-carbonyl clusters will be documented. The physiologically relevant redox properties of cobalt will be highlighted and the role this plays in the preparation of hypoxia selective prodrugs and imaging agents will be discussed. The use of cobalt-containing cobalamin as a cancer specific delivery agent for cytotoxins will also be described. The work summarised in this perspective shows that the biochemical and biophysical properties of cobalt-containing compounds can be fine-tuned to produce new generations of anticancer agents with clinically relevant efficacies.

  15. Complex networks: Dynamics and security

    Indian Academy of Sciences (India)

    Ying-Cheng Lai; Adilson Motter; Takashi Nishikawa; Kwangho Park; Liang Zhao

    2005-04-01

    This paper presents a perspective in the study of complex networks by focusing on how dynamics may affect network security under attacks. In particular, we review two related problems: attack-induced cascading breakdown and range-based attacks on links. A cascade in a network means the failure of a substantial fraction of the entire network in a cascading manner, which can be induced by the failure of or attacks on only a few nodes. These have been reported for the internet and for the power grid (e.g., the August 10, 1996 failure of the western United States power grid). We study a mechanism for cascades in complex networks by constructing a model incorporating the flows of information and physical quantities in the network. Using this model we can also show that the cascading phenomenon can be understood as a phase transition in terms of the key parameter characterizing the node capacity. For a parameter value below the phase-transition point, cascading failures can cause the network to disintegrate almost entirely. We will show how to obtain a theoretical estimate for the phase-transition point. The second problem is motivated by the fact that most existing works on the security of complex networks consider attacks on nodes rather than on links. We address attacks on links. Our investigation leads to the finding that many scale-free networks are more sensitive to attacks on short-range than on long-range links. Considering that the small-world phenomenon in complex networks has been identified as being due to the presence of long-range links, i.e., links connecting nodes that would otherwise be separated by a long node-to-node distance, our result, besides its importance concerning network efficiency and security, has the striking implication that the small-world property of scale-free networks is mainly due to short-range links.

  16. Language Networks as Complex Systems

    Science.gov (United States)

    Lee, Max Kueiming; Ou, Sheue-Jen

    2008-01-01

    Starting in the late eighties, with a growing discontent with analytical methods in science and the growing power of computers, researchers began to study complex systems such as living organisms, evolution of genes, biological systems, brain neural networks, epidemics, ecology, economy, social networks, etc. In the early nineties, the research…

  17. Pattern-oriented modeling of agent-based complex systems: lessons from ecology

    NARCIS (Netherlands)

    Grimm, V.; Revilla, E.; Berger, U.; Jeltsch, F.; Mooij, W.M.; Railsback, S.F.; Thulke, H-H.; Weiner, J.; Wiegand, T.; DeAngelis, D.L.

    2005-01-01

    Agent-based complex systems are dynamic networks of many interacting agents; examples include ecosystems, financial markets, and cities. The search for general principles underlying the internal organization of such systems often uses bottom-up simulation models such as cellular automata and agent-b

  18. "Conjectural" links in complex networks

    Science.gov (United States)

    Snarskii, A. A.; Zorinets, D. I.; Lande, D. V.

    2016-11-01

    This paper introduces the concept of Conjectural Link for Complex Networks, in particular, social networks. Conjectural Link we understand as an implicit link, not available in the network, but supposed to be present, based on the characteristics of its topology. It is possible, for example, when in the formal description of the network some connections are skipped due to errors, deliberately hidden or withdrawn (e.g. in the case of partial destruction of the network). Introduced a parameter that allows ranking the Conjectural Link. The more this parameter - the more likely that this connection should be present in the network. This paper presents a method of recovery of partially destroyed Complex Networks using Conjectural Links finding. Presented two methods of finding the node pairs that are not linked directly to one another, but have a great possibility of Conjectural Link communication among themselves: a method based on the determination of the resistance between two nodes, and method based on the computation of the lengths of routes between two nodes. Several examples of real networks are reviewed and performed a comparison to know network links prediction methods, not intended to find the missing links in already formed networks.

  19. INTELLIGENT MULTI-AGENT PLATFORM WITHIN COLLABORATIVE NETWORKED ENVIRONMENT

    Directory of Open Access Journals (Sweden)

    Adina-Georgeta CREŢAN

    2016-06-01

    Full Text Available This paper proposes an agent-based intelligent platform to model and support parallel and concurrent negotiations among organizations acting in the same industrial market. The underlying complexity is to model the dynamic environment where multi-attribute and multi-participant negotiations are racing over a set of heterogeneous resources. The metaphor Interaction Abstract Machines (IAMs is used to model the parallelism and the non-deterministic aspects of the negotiation processes that occur in Collaborative Networked Environment.

  20. Griffiths phases on complex networks.

    Science.gov (United States)

    Muñoz, Miguel A; Juhász, Róbert; Castellano, Claudio; Odor, Géza

    2010-09-17

    Quenched disorder is known to play a relevant role in dynamical processes and phase transitions. Its effects on the dynamics of complex networks have hardly been studied. Aimed at filling this gap, we analyze the contact process, i.e., the simplest propagation model, with quenched disorder on complex networks. We find Griffiths phases and other rare-region effects, leading rather generically to anomalously slow (algebraic, logarithmic, …) relaxation, on Erdos-Rényi networks. Similar effects are predicted to exist for other topologies with a finite percolation threshold. More surprisingly, we find that Griffiths phases can also emerge in the absence of quenched disorder, as a consequence of topological heterogeneity in networks with finite topological dimension. These results have a broad spectrum of implications for propagation phenomena and other dynamical processes on networks.

  1. Hierarchy measure for complex networks

    CERN Document Server

    Mones, Enys; Vicsek, Tamás

    2012-01-01

    Nature, technology and society are full of complexity arising from the intricate web of the interactions among the units of the related systems (e.g., proteins, computers, people). Consequently, one of the most successful recent approaches to capturing the fundamental features of the structure and dynamics of complex systems has been the investigation of the networks associated with the above units (nodes) together with their relations (edges). Most complex systems have an inherently hierarchical organization and, correspondingly, the networks behind them also exhibit hierarchical features. Indeed, several papers have been devoted to describing this essential aspect of networks, however, without resulting in a widely accepted, converging concept concerning the quantitative characterization of the level of their hierarchy. Here we develop an approach and propose a quantity (measure) which is simple enough to be widely applicable, reveals a number of universal features of the organization of real-world networks...

  2. Hierarchy Measure for Complex Networks

    Science.gov (United States)

    Mones, Enys; Vicsek, Lilla; Vicsek, Tamás

    2012-01-01

    Nature, technology and society are full of complexity arising from the intricate web of the interactions among the units of the related systems (e.g., proteins, computers, people). Consequently, one of the most successful recent approaches to capturing the fundamental features of the structure and dynamics of complex systems has been the investigation of the networks associated with the above units (nodes) together with their relations (edges). Most complex systems have an inherently hierarchical organization and, correspondingly, the networks behind them also exhibit hierarchical features. Indeed, several papers have been devoted to describing this essential aspect of networks, however, without resulting in a widely accepted, converging concept concerning the quantitative characterization of the level of their hierarchy. Here we develop an approach and propose a quantity (measure) which is simple enough to be widely applicable, reveals a number of universal features of the organization of real-world networks and, as we demonstrate, is capable of capturing the essential features of the structure and the degree of hierarchy in a complex network. The measure we introduce is based on a generalization of the m-reach centrality, which we first extend to directed/partially directed graphs. Then, we define the global reaching centrality (GRC), which is the difference between the maximum and the average value of the generalized reach centralities over the network. We investigate the behavior of the GRC considering both a synthetic model with an adjustable level of hierarchy and real networks. Results for real networks show that our hierarchy measure is related to the controllability of the given system. We also propose a visualization procedure for large complex networks that can be used to obtain an overall qualitative picture about the nature of their hierarchical structure. PMID:22470477

  3. Markovian Dynamics on Complex Reaction Networks

    CERN Document Server

    Goutsias, John

    2012-01-01

    Complex networks, comprised of individual elements that interact with each other through reaction channels, are ubiquitous across many scientific and engineering disciplines. Examples include biochemical, pharmacokinetic, epidemiological, ecological, social, neural, and multi-agent networks. A common approach to modeling such networks is by a master equation that governs the dynamic evolution of the joint probability mass function of the underling population process and naturally leads to Markovian dynamics for such process. Due however to the nonlinear nature of most reactions, the computation and analysis of the resulting stochastic population dynamics is a difficult task. This review article provides a coherent and comprehensive coverage of recently developed approaches and methods to tackle this problem. After reviewing a general framework for modeling Markovian reaction networks and giving specific examples, the authors present numerical and computational techniques capable of evaluating or approximating...

  4. Optimal search strategies on complex networks

    CERN Document Server

    Di Patti, Francesca; Piazza, Francesco

    2014-01-01

    Complex networks are ubiquitous in nature and play a role of paramount importance in many contexts. Internet and the cyberworld, which permeate our everyday life, are self-organized hierarchical graphs. Urban traffic flows on intricate road networks, which impact both transportation design and epidemic control. In the brain, neurons are cabled through heterogeneous connections, which support the propagation of electric signals. In all these cases, the true challenge is to unveil the mechanisms through which specific dynamical features are modulated by the underlying topology of the network. Here, we consider agents randomly hopping along the links of a graph, with the additional possibility of performing long-range hops to randomly chosen disconnected nodes with a given probability. We show that an optimal combination of the two jump rules exists that maximises the efficiency of target search, the optimum reflecting the topology of the network.

  5. Is the immune network a complex network?

    CERN Document Server

    Souza-e-Silva, Hallan

    2012-01-01

    Some years ago a cellular automata model was proposed to describe the evolution of the immune repertoire of B cells and antibodies based on Jerne's immune network theory and shape-space formalism. Here we investigate if the networks generated by this model in the different regimes can be classified as complex networks. We have found that in the chaotic regime the network has random characteristics with large, constant values of clustering coefficients, while in the ordered phase, the degree distribution of the network is exponential and the clustering coefficient exhibits power law behavior. In the transition region we observed a mixed behavior (random-like and exponential) of the degree distribution as opposed to the scale-free behavior reported for other biological networks. Randomness and low connectivity in the active sites allow for rapid changes in the connectivity distribution of the immune network in order to include and/or discard information and generate a dynamic memory. However it is the availabil...

  6. Community Detection in Complex Networks

    Institute of Scientific and Technical Information of China (English)

    Nan Du; Bai Wang; Bin Wu

    2008-01-01

    With the rapidly growing evidence that various systems in nature and society can be modeled as complex networks, community detection in networks becomes a hot research topic in physics, sociology, computer society, etc. Although this investigation of community structures has motivated many diverse algorithms, most of them are unsuitable when dealing with large networks due to their computational cost. In this paper, we present a faster algorithm ComTeetor,which is more efficient for the community detection in large complex networks based on the nature of overlapping cliques.This algorithm does not require any priori knowledge about the number or the original division of the communities. With respect to practical applications, ComTector is challenging with five different types of networks including the classic Zachary Karate Club, Scientific Collaboration Network, South Florida Free Word Association Network, Urban Traffic Network, North America Power Grid and the Telecomnmnication Call Network. Experimental results show that our algorithm can discover meaningful communities that meet both the objective basis and our intuitions.

  7. Control efficacy of complex networks

    Science.gov (United States)

    Gao, Xin-Dong; Wang, Wen-Xu; Lai, Ying-Cheng

    2016-06-01

    Controlling complex networks has become a forefront research area in network science and engineering. Recent efforts have led to theoretical frameworks of controllability to fully control a network through steering a minimum set of driver nodes. However, in realistic situations not every node is accessible or can be externally driven, raising the fundamental issue of control efficacy: if driving signals are applied to an arbitrary subset of nodes, how many other nodes can be controlled? We develop a framework to determine the control efficacy for undirected networks of arbitrary topology. Mathematically, based on non-singular transformation, we prove a theorem to determine rigorously the control efficacy of the network and to identify the nodes that can be controlled for any given driver nodes. Physically, we develop the picture of diffusion that views the control process as a signal diffused from input signals to the set of controllable nodes. The combination of mathematical theory and physical reasoning allows us not only to determine the control efficacy for model complex networks and a large number of empirical networks, but also to uncover phenomena in network control, e.g., hub nodes in general possess lower control centrality than an average node in undirected networks.

  8. Synchronization in complex clustered networks

    Institute of Scientific and Technical Information of China (English)

    HUANG Liang; LAI Ying-Cheng; Kwangho PARK; WANG Xingang; LAI Choy Heng; Robert A. GATENBY

    2007-01-01

    Synchronization in complex networks has been an active area of research in recent years. While much effort has been devoted to networks with the small-world and scale-free topology, structurally they are often assumed to have a single, densely connected component. Recently it has also become apparent that many networks in social, biological, and tech-nological systems are clustered, as characterized by a number (or a hierarchy) of sparsely linked clusters, each with dense and complex internal connections. Synchronization is funda-mental to the dynamics and functions of complex clustered networks, but this problem has just begun to be addressed. This paper reviews some progress in this direction by focus-ing on the interplay between the clustered topology and net-work synchronizability. In particular, there are two parame-ters characterizing a clustered network: the intra-cluster and the inter-cluster link density. Our goal is to clarify the roles of these parameters in shaping network synchronizability. By using theoretical analysis and direct numerical simulations of oscillator networks, it is demonstrated that clustered net-works with random inter-cluster links are more synchroniz-able, and synchronization can be optimized when inter-cluster and intra-cluster links match. The latter result has one coun-terintuitive implication: more links, if placed improperly, can actually lead to destruction of synchronization, even though such links tend to decrease the average network distance. It is hoped that this review will help attract attention to the fun-damental problem of clustered structures/synchronization in network science.

  9. Benford's Distribution in Complex Networks.

    Science.gov (United States)

    Morzy, Mikołaj; Kajdanowicz, Tomasz; Szymański, Bolesław K

    2016-10-17

    Many collections of numbers do not have a uniform distribution of the leading digit, but conform to a very particular pattern known as Benford's distribution. This distribution has been found in numerous areas such as accounting data, voting registers, census data, and even in natural phenomena. Recently it has been reported that Benford's law applies to online social networks. Here we introduce a set of rigorous tests for adherence to Benford's law and apply it to verification of this claim, extending the scope of the experiment to various complex networks and to artificial networks created by several popular generative models. Our findings are that neither for real nor for artificial networks there is sufficient evidence for common conformity of network structural properties with Benford's distribution. We find very weak evidence suggesting that three measures, degree centrality, betweenness centrality and local clustering coefficient, could adhere to Benford's law for scalefree networks but only for very narrow range of their parameters.

  10. Ranking in evolving complex networks

    Science.gov (United States)

    Liao, Hao; Mariani, Manuel Sebastian; Medo, Matúš; Zhang, Yi-Cheng; Zhou, Ming-Yang

    2017-05-01

    Complex networks have emerged as a simple yet powerful framework to represent and analyze a wide range of complex systems. The problem of ranking the nodes and the edges in complex networks is critical for a broad range of real-world problems because it affects how we access online information and products, how success and talent are evaluated in human activities, and how scarce resources are allocated by companies and policymakers, among others. This calls for a deep understanding of how existing ranking algorithms perform, and which are their possible biases that may impair their effectiveness. Many popular ranking algorithms (such as Google's PageRank) are static in nature and, as a consequence, they exhibit important shortcomings when applied to real networks that rapidly evolve in time. At the same time, recent advances in the understanding and modeling of evolving networks have enabled the development of a wide and diverse range of ranking algorithms that take the temporal dimension into account. The aim of this review is to survey the existing ranking algorithms, both static and time-aware, and their applications to evolving networks. We emphasize both the impact of network evolution on well-established static algorithms and the benefits from including the temporal dimension for tasks such as prediction of network traffic, prediction of future links, and identification of significant nodes.

  11. Agent Based Modeling on Organizational Dynamics of Terrorist Network

    Directory of Open Access Journals (Sweden)

    Bo Li

    2015-01-01

    Full Text Available Modeling organizational dynamics of terrorist network is a critical issue in computational analysis of terrorism research. The first step for effective counterterrorism and strategic intervention is to investigate how the terrorists operate with the relational network and what affects the performance. In this paper, we investigate the organizational dynamics by employing a computational experimentation methodology. The hierarchical cellular network model and the organizational dynamics model are developed for modeling the hybrid relational structure and complex operational processes, respectively. To intuitively elucidate this method, the agent based modeling is used to simulate the terrorist network and test the performance in diverse scenarios. Based on the experimental results, we show how the changes of operational environments affect the development of terrorist organization in terms of its recovery and capacity to perform future tasks. The potential strategies are also discussed, which can be used to restrain the activities of terrorists.

  12. NEXCADE: perturbation analysis for complex networks.

    Directory of Open Access Journals (Sweden)

    Gitanjali Yadav

    Full Text Available Recent advances in network theory have led to considerable progress in our understanding of complex real world systems and their behavior in response to external threats or fluctuations. Much of this research has been invigorated by demonstration of the 'robust, yet fragile' nature of cellular and large-scale systems transcending biology, sociology, and ecology, through application of the network theory to diverse interactions observed in nature such as plant-pollinator, seed-dispersal agent and host-parasite relationships. In this work, we report the development of NEXCADE, an automated and interactive program for inducing disturbances into complex systems defined by networks, focusing on the changes in global network topology and connectivity as a function of the perturbation. NEXCADE uses a graph theoretical approach to simulate perturbations in a user-defined manner, singly, in clusters, or sequentially. To demonstrate the promise it holds for broader adoption by the research community, we provide pre-simulated examples from diverse real-world networks including eukaryotic protein-protein interaction networks, fungal biochemical networks, a variety of ecological food webs in nature as well as social networks. NEXCADE not only enables network visualization at every step of the targeted attacks, but also allows risk assessment, i.e. identification of nodes critical for the robustness of the system of interest, in order to devise and implement context-based strategies for restructuring a network, or to achieve resilience against link or node failures. Source code and license for the software, designed to work on a Linux-based operating system (OS can be downloaded at http://www.nipgr.res.in/nexcade_download.html. In addition, we have developed NEXCADE as an OS-independent online web server freely available to the scientific community without any login requirement at http://www.nipgr.res.in/nexcade.html.

  13. Consensus in networks of mobile communicating agents

    Science.gov (United States)

    Baronchelli, Andrea; Díaz-Guilera, Albert

    2012-01-01

    Populations of mobile and communicating agents describe a vast array of technological and natural systems, ranging from sensor networks to animal groups. Here, we investigate how a group-level agreement may emerge in the continuously evolving network defined by the local interactions of the moving individuals. We adopt a general scheme of motion in two dimensions and we let the individuals interact through the minimal naming game, a prototypical scheme to investigate social consensus. We distinguish different regimes of convergence determined by the emission range of the agents and by their mobility, and we identify the corresponding scaling behaviors of the consensus time. In the same way, we rationalize also the behavior of the maximum memory used during the convergence process, which determines the minimum cognitive/storage capacity needed by the individuals. Overall, we believe that the simple and general model presented in this paper can represent a helpful reference for a better understanding of the behavior of populations of mobile agents.

  14. Consensus in evolving networks of mobile agents

    Science.gov (United States)

    Baronchelli, Andrea; Díaz-Guilera, Albert

    2012-02-01

    Populations of mobile and communicating agents describe a vast array of technological and natural systems, ranging from sensor networks to animal groups. Here, we investigate how a group-level agreement may emerge in the continuously evolving networks defined by the local interactions of the moving individuals. We adopt a general scheme of motion in two dimensions and we let the individuals interact through the minimal naming game, a prototypical scheme to investigate social consensus. We distinguish different regimes of convergence determined by the emission range of the agents and by their mobility, and we identify the corresponding scaling behaviors of the consensus time. In the same way, we rationalize also the behavior of the maximum memory used during the convergence process, which determines the minimum cognitive/storage capacity needed by the individuals. Overall, we believe that the simple and general model presented in this talk can represent a helpful reference for a better understanding of the behavior of populations of mobile agents.

  15. Resilience of modular complex networks

    CERN Document Server

    Shai, Saray; Kenett, Yoed N; Faust, Miriam; Dobson, Simon; Havlin, Shlomo

    2014-01-01

    Complex networks often have a modular structure, where a number of tightly- connected groups of nodes (modules) have relatively few interconnections. Modularity had been shown to have an important effect on the evolution and stability of biological networks, on the scalability and efficiency of large-scale infrastructure, and the development of economic and social systems. An analytical framework for understanding modularity and its effects on network vulnerability is still missing. Through recent advances in the understanding of multilayer networks, however, it is now possible to develop a theoretical framework to systematically study this critical issue. Here we study, analytically and numerically, the resilience of modular networks under attacks on interconnected nodes, which exhibit high betweenness values and are often more exposed to failure. Our model provides new understandings into the feedback between structure and function in real world systems, and consequently has important implications as divers...

  16. Transport optimization on complex networks

    CERN Document Server

    Danila, Bogdan; Marsh, John A; Bassler, Kevin E

    2007-01-01

    We present a comparative study of the application of a recently introduced heuristic algorithm to the optimization of transport on three major types of complex networks. The algorithm balances network traffic iteratively by minimizing the maximum node betweenness with as little path lengthening as possible. We show that by using this optimal routing, a network can sustain significantly higher traffic without jamming than in the case of shortest path routing. A formula is proved that allows quick computation of the average number of hops along the path and of the average travel times once the betweennesses of the nodes are computed. Using this formula, we show that routing optimization preserves the small-world character exhibited by networks under shortest path routing, and that it significantly reduces the average travel time on congested networks with only a negligible increase in the average travel time at low loads. Finally, we study the correlation between the weights of the links in the case of optimal ...

  17. Complex Networks in Psychological Models

    Science.gov (United States)

    Wedemann, R. S.; Carvalho, L. S. A. V. D.; Donangelo, R.

    We develop schematic, self-organizing, neural-network models to describe mechanisms associated with mental processes, by a neurocomputational substrate. These models are examples of real world complex networks with interesting general topological structures. Considering dopaminergic signal-to-noise neuronal modulation in the central nervous system, we propose neural network models to explain development of cortical map structure and dynamics of memory access, and unify different mental processes into a single neurocomputational substrate. Based on our neural network models, neurotic behavior may be understood as an associative memory process in the brain, and the linguistic, symbolic associative process involved in psychoanalytic working-through can be mapped onto a corresponding process of reconfiguration of the neural network. The models are illustrated through computer simulations, where we varied dopaminergic modulation and observed the self-organizing emergent patterns at the resulting semantic map, interpreting them as different manifestations of mental functioning, from psychotic through to normal and neurotic behavior, and creativity.

  18. Composing Music with Complex Networks

    Science.gov (United States)

    Liu, Xiaofan; Tse, Chi K.; Small, Michael

    In this paper we study the network structure in music and attempt to compose music artificially. Networks are constructed with nodes and edges corresponding to musical notes and their co-occurrences. We analyze sample compositions from Bach, Mozart, Chopin, as well as other types of music including Chinese pop music. We observe remarkably similar properties in all networks constructed from the selected compositions. Power-law exponents of degree distributions, mean degrees, clustering coefficients, mean geodesic distances, etc. are reported. With the network constructed, music can be created by using a biased random walk algorithm, which begins with a randomly chosen note and selects the subsequent notes according to a simple set of rules that compares the weights of the edges, weights of the nodes, and/or the degrees of nodes. The newly created music from complex networks will be played in the presentation.

  19. Remote Synchronization in Complex Networks

    CERN Document Server

    Gambuzza, Lucia Valentina; Fiasconaro, Alessandro; Fortuna, Luigi; Gómez-Gardeñes, Jesús; Frasca, Mattia

    2013-01-01

    We show the existence of a novel dynamical state called remote synchronization in general networks of coupled oscillators. This state is characterized by the synchronization of pairs of nodes that are not directly connected via a physical link or any sequence of synchronized nodes. This phenomenon cannot be observed in networks of phase oscillators as its underlying mechanism is the modulation of the amplitude of those intermediary nodes between the remotely synchronized units. Our findings thus show the ubiquity and robustness of these states and bridge the gap from their recent observation in simple toy graphs to complex networks.

  20. Geographical Effects on Complex Networks

    Institute of Scientific and Technical Information of China (English)

    LIN Zhong-Cai; YANG Lei; YANG Kong-Qing

    2005-01-01

    @@ We investigate how the geographical structure of a complex network affects its network topology, synchronization and the average spatial length of edges. The geographical structure means that the connecting probability of two nodes is related to the spatial distance of the two nodes. Our simulation results show that the geographical structure changes the network topology. The synchronization tendency is enhanced and the average spatial length of edges is enlarged when the node can randomly connect to the further one. Analytic results support our understanding of the phenomena.

  1. Neuronal avalanches in complex networks

    Directory of Open Access Journals (Sweden)

    Victor Hernandez-Urbina

    2016-12-01

    Full Text Available Brain networks are neither regular nor random. Their structure allows for optimal information processing and transmission across the entire neural substrate of an organism. However, for topological features to be appropriately harnessed, brain networks should implement a dynamical regime which prevents phase-locked and chaotic behaviour. Critical neural dynamics refer to a dynamical regime in which the system is poised at the boundary between regularity and randomness. It has been reported that neural systems poised at this boundary achieve maximum computational power. In this paper, we review recent results regarding critical neural dynamics that emerge from systems whose underlying structure exhibits complex network properties.

  2. Complexity reduction of astrochemical networks

    CERN Document Server

    Grassi, T; Gianturco, F A; Baiocchi, P; Merlin, E

    2012-01-01

    We present a new computational scheme aimed at reducing the complexity of the chemical networks in astrophysical models, one which is shown to markedly improve their computational efficiency. It contains a flux-reduction scheme that permits to deal with both large and small systems. This procedure is shown to yield a large speed-up of the corresponding numerical codes and provides good accord with the full network results. We analyse and discuss two examples involving chemistry networks of the interstellar medium and show that the results from the present reduction technique reproduce very well the results from fuller calculations.

  3. Markovian dynamics on complex reaction networks

    Energy Technology Data Exchange (ETDEWEB)

    Goutsias, J., E-mail: goutsias@jhu.edu; Jenkinson, G., E-mail: jenkinson@jhu.edu

    2013-08-10

    Complex networks, comprised of individual elements that interact with each other through reaction channels, are ubiquitous across many scientific and engineering disciplines. Examples include biochemical, pharmacokinetic, epidemiological, ecological, social, neural, and multi-agent networks. A common approach to modeling such networks is by a master equation that governs the dynamic evolution of the joint probability mass function of the underlying population process and naturally leads to Markovian dynamics for such process. Due however to the nonlinear nature of most reactions and the large size of the underlying state-spaces, computation and analysis of the resulting stochastic population dynamics is a difficult task. This review article provides a coherent and comprehensive coverage of recently developed approaches and methods to tackle this problem. After reviewing a general framework for modeling Markovian reaction networks and giving specific examples, the authors present numerical and computational techniques capable of evaluating or approximating the solution of the master equation, discuss a recently developed approach for studying the stationary behavior of Markovian reaction networks using a potential energy landscape perspective, and provide an introduction to the emerging theory of thermodynamic analysis of such networks. Three representative problems of opinion formation, transcription regulation, and neural network dynamics are used as illustrative examples.

  4. 通用型多语竞争与政策调控复杂Agent网络模型%Universal Complex Agent Network Model for Multi-Lingual Competition and Policy Intervention

    Institute of Scientific and Technical Information of China (English)

    于群修; 毕贵红; 张寿明; 曾振华

    2016-01-01

    利用基于社会圈子理论的agent微观建模技术来构建语言竞争社会网络。构建的网络拓扑结构参数更接近实际社会网络参数,agent可以赋予空间属性,可以描述混合居住和分片聚居社会网络,而且具有动态特性。以三语竞争为例,提出了一种将网络中个体间的三语竞争分解为三个两种语言竞争的问题,给出了一种基于竞争原理的通用多语竞争复杂agent网络仿真建模方法。网络上的节点agent代表具有学习和遗忘功能的个体,每个个体均可以通过学习获得第二或第三种语言成为双语或三语者,也可以通过遗忘重新成为单语或双语者,同时agent考虑了语言的垂直传播。分析了语言地位、不同语言人口比例、移动人口比例、社会半径、不同语言人口的空间居住模式、语言传承率等因素及其综合调控措施对语言竞争的影响。仿真分析表明,该模型贴近实际社会,为多语竞争提供依据。%This paper proposes a dynamic social network model for the competition among three languages with agent based modeling method and social circles theory. The parameters of the topological structure of constructed social network are more close to the parameters of actual social network. The individual agents in the network can give space attribute and can describe mixed habitation in a region with different languages and separation habitation in individual area with a language, so the constructed social network is endowed with dynamic characteristics. Taking the competition among three languages as an example, this paper proposes a method that the competition among three languages is decomposed into three times of bilingual competition, and presents a universal complex agent net-work model for multi-lingual competition and policy intervention. The agents on the network represent the individual which has the function of learning and forgetting. And each agent

  5. Application of mobile scanning agent in the network security

    Institute of Scientific and Technical Information of China (English)

    闵君; 冯珊; 唐超; 梅纲

    2004-01-01

    To enhance the security of network systems, puts forward a kind of software agent is put forward, which has the induction ability of network frameworks and the ability of behavior independence. It is mobile scanning agent. More attentions is paid to expound how to design and realize mobile scanning agent. Besides, it is also explained the programs of mobile scanning agent system. In the end, it expects mobile scanning agent.

  6. Complex-Valued Neural Networks

    CERN Document Server

    Hirose, Akira

    2012-01-01

    This book is the second enlarged and revised edition of the first successful monograph on complex-valued neural networks (CVNNs) published in 2006, which lends itself to graduate and undergraduate courses in electrical engineering, informatics, control engineering, mechanics, robotics, bioengineering, and other relevant fields. In the second edition the recent trends in CVNNs research are included, resulting in e.g. almost a doubled number of references. The parametron invented in 1954 is also referred to with discussion on analogy and disparity. Also various additional arguments on the advantages of the complex-valued neural networks enhancing the difference to real-valued neural networks are given in various sections. The book is useful for those beginning their studies, for instance, in adaptive signal processing for highly functional sensing and imaging, control in unknown and changing environment, robotics inspired by human neural systems, and brain-like information processing, as well as interdisciplina...

  7. Optimal Disruption of Complex Networks

    CERN Document Server

    Zhao, Jin-Hua

    2016-01-01

    The collection of all the strongly connected components in a directed graph, among each cluster of which any node has a path to another node, is a typical example of the intertwining structure and dynamics in complex networks, as its relative size indicates network cohesion and it also composes of all the feedback cycles in the network. Here we consider finding an optimal strategy with minimal effort in removal arcs (for example, deactivation of directed interactions) to fragment all the strongly connected components into tree structure with no effect from feedback mechanism. We map the optimal network disruption problem to the minimal feedback arc set problem, a non-deterministically polynomial hard combinatorial optimization problem in graph theory. We solve the problem with statistical physical methods from spin glass theory, resulting in a simple numerical method to extract sub-optimal disruption arc sets with significantly better results than a local heuristic method and a simulated annealing method both...

  8. Complex networks for streamflow dynamics

    Directory of Open Access Journals (Sweden)

    B. Sivakumar

    2014-07-01

    Full Text Available Streamflow modeling is an enormously challenging problem, due to the complex and nonlinear interactions between climate inputs and landscape characteristics over a wide range of spatial and temporal scales. A basic idea in streamflow studies is to establish connections that generally exist, but attempts to identify such connections are largely dictated by the problem at hand and the system components in place. While numerous approaches have been proposed in the literature, our understanding of these connections remains far from adequate. The present study introduces the theory of networks, and in particular complex networks, to examine the connections in streamflow dynamics, with a particular focus on spatial connections. Monthly streamflow data observed over a period of 52 years from a large network of 639 monitoring stations in the contiguous United States are studied. The connections in this streamflow network are examined using the concept of clustering coefficient, which is a measure of local density and quantifies the network's tendency to cluster. The clustering coefficient analysis is performed with several different threshold levels, which are based on correlations in streamflow data between the stations. The clustering coefficient values of the 639 stations are used to obtain important information about the connections in the network and their extent, similarity and differences between stations/regions, and the influence of thresholds. The relationship of the clustering coefficient with the number of links/actual links in the network and the number of neighbors is also addressed. The results clearly indicate the usefulness of the network-based approach for examining connections in streamflow, with important implications for interpolation and extrapolation, classification of catchments, and predictions in ungaged basins.

  9. Multilevel Complex Networks and Systems

    Science.gov (United States)

    Caldarelli, Guido

    2014-03-01

    Network theory has been a powerful tool to model isolated complex systems. However, the classical approach does not take into account the interactions often present among different systems. Hence, the scientific community is nowadays concentrating the efforts on the foundations of new mathematical tools for understanding what happens when multiple networks interact. The case of economic and financial networks represents a paramount example of multilevel networks. In the case of trade, trade among countries the different levels can be described by the different granularity of the trading relations. Indeed, we have now data from the scale of consumers to that of the country level. In the case of financial institutions, we have a variety of levels at the same scale. For example one bank can appear in the interbank networks, ownership network and cds networks in which the same institution can take place. In both cases the systemically important vertices need to be determined by different procedures of centrality definition and community detection. In this talk I will present some specific cases of study related to these topics and present the regularities found. Acknowledged support from EU FET Project ``Multiplex'' 317532.

  10. Physical controllability of complex networks

    Science.gov (United States)

    Wang, Le-Zhi; Chen, Yu-Zhong; Wang, Wen-Xu; Lai, Ying-Cheng

    2017-01-01

    A challenging problem in network science is to control complex networks. In existing frameworks of structural or exact controllability, the ability to steer a complex network toward any desired state is measured by the minimum number of required driver nodes. However, if we implement actual control by imposing input signals on the minimum set of driver nodes, an unexpected phenomenon arises: due to computational or experimental error there is a great probability that convergence to the final state cannot be achieved. In fact, the associated control cost can become unbearably large, effectively preventing actual control from being realized physically. The difficulty is particularly severe when the network is deemed controllable with a small number of drivers. Here we develop a physical controllability framework based on the probability of achieving actual control. Using a recently identified fundamental chain structure underlying the control energy, we offer strategies to turn physically uncontrollable networks into physically controllable ones by imposing slightly augmented set of input signals on properly chosen nodes. Our findings indicate that, although full control can be theoretically guaranteed by the prevailing structural controllability theory, it is necessary to balance the number of driver nodes and control cost to achieve physical control. PMID:28074900

  11. Complex Networks and Socioeconomic Applications

    Science.gov (United States)

    Almendral, Juan A.; López, Luis; Mendes, Jose F.; Sanjuán, Miguel A. F.

    2003-04-01

    The study and characterization of complex systems is a fruitful research area nowadays. Special attention has been paid recently to complex networks, where graph and network analysis plays an important role since they reduce a given system to a simpler problem. Using a simple model for the information flow on social networks, we show that the traditional hierarchical topologies frequently used by companies and organizations, are poorly designed in terms of efficiency. Moreover, we prove that this type of structures are the result of the individual aim of monopolizing as much information as possible within the network. As the information is an appropriate measurement of centrality, we conclude that this kind of topology is so attractive for leaders because the global influence each actor has within the network is completely determined by the hierarchical level occupied. The effect on the efficiency caused by a change in a traditional hierarchical topology is also analyzed. In particular, by introducing the possibility of communication on the same level of the hierarchy.

  12. Physical controllability of complex networks

    Science.gov (United States)

    Wang, Le-Zhi; Chen, Yu-Zhong; Wang, Wen-Xu; Lai, Ying-Cheng

    2017-01-01

    A challenging problem in network science is to control complex networks. In existing frameworks of structural or exact controllability, the ability to steer a complex network toward any desired state is measured by the minimum number of required driver nodes. However, if we implement actual control by imposing input signals on the minimum set of driver nodes, an unexpected phenomenon arises: due to computational or experimental error there is a great probability that convergence to the final state cannot be achieved. In fact, the associated control cost can become unbearably large, effectively preventing actual control from being realized physically. The difficulty is particularly severe when the network is deemed controllable with a small number of drivers. Here we develop a physical controllability framework based on the probability of achieving actual control. Using a recently identified fundamental chain structure underlying the control energy, we offer strategies to turn physically uncontrollable networks into physically controllable ones by imposing slightly augmented set of input signals on properly chosen nodes. Our findings indicate that, although full control can be theoretically guaranteed by the prevailing structural controllability theory, it is necessary to balance the number of driver nodes and control cost to achieve physical control.

  13. Epidemic processes in complex networks

    Science.gov (United States)

    Pastor-Satorras, Romualdo; Castellano, Claudio; Van Mieghem, Piet; Vespignani, Alessandro

    2015-07-01

    In recent years the research community has accumulated overwhelming evidence for the emergence of complex and heterogeneous connectivity patterns in a wide range of biological and sociotechnical systems. The complex properties of real-world networks have a profound impact on the behavior of equilibrium and nonequilibrium phenomena occurring in various systems, and the study of epidemic spreading is central to our understanding of the unfolding of dynamical processes in complex networks. The theoretical analysis of epidemic spreading in heterogeneous networks requires the development of novel analytical frameworks, and it has produced results of conceptual and practical relevance. A coherent and comprehensive review of the vast research activity concerning epidemic processes is presented, detailing the successful theoretical approaches as well as making their limits and assumptions clear. Physicists, mathematicians, epidemiologists, computer, and social scientists share a common interest in studying epidemic spreading and rely on similar models for the description of the diffusion of pathogens, knowledge, and innovation. For this reason, while focusing on the main results and the paradigmatic models in infectious disease modeling, the major results concerning generalized social contagion processes are also presented. Finally, the research activity at the forefront in the study of epidemic spreading in coevolving, coupled, and time-varying networks is reported.

  14. Modern approaches to agent-based complex automated negotiation

    CERN Document Server

    Bai, Quan; Ito, Takayuki; Zhang, Minjie; Ren, Fenghui; Aydoğan, Reyhan; Hadfi, Rafik

    2017-01-01

    This book addresses several important aspects of complex automated negotiations and introduces a number of modern approaches for facilitating agents to conduct complex negotiations. It demonstrates that autonomous negotiation is one of the most important areas in the field of autonomous agents and multi-agent systems. Further, it presents complex automated negotiation scenarios that involve negotiation encounters that may have, for instance, a large number of agents, a large number of issues with strong interdependencies and/or real-time constraints.

  15. An Intelligent Mobile-Agent Based Scalable Network Management Architecture for Large-Scale Enterprise System

    CERN Document Server

    Sharma, A K; Singh, Vijay

    2012-01-01

    Several Mobile Agent based distributed network management models have been proposed in recent times to address the scalability and flexibility problems of centralized (SNMP or CMIP management models) models. Though the use of Mobile Agents to distribute and delegate management tasks comes handy in dealing with the previously stated issues, many of the agent-based management frameworks like initial flat bed models and static mid-level managers employing mobile agents models cannot efficiently meet the demands of current networks which are growing in size and complexity. Moreover, varied technologies, such as SONET, ATM, Ethernet, DWDM etc., present at different layers of the Access, Metro and Core (long haul) sections of the network, have contributed to the complexity in terms of their own framing and protocol structures. Thus, controlling and managing the traffic in these networks is a challenging task. This paper presents an intelligent scalable hierarchical agent based model for the management of large-scal...

  16. Nonparametric Bayesian Modeling of Complex Networks

    DEFF Research Database (Denmark)

    Schmidt, Mikkel Nørgaard; Mørup, Morten

    2013-01-01

    Modeling structure in complex networks using Bayesian nonparametrics makes it possible to specify flexible model structures and infer the adequate model complexity from the observed data. This article provides a gentle introduction to nonparametric Bayesian modeling of complex networks: Using...... for complex networks can be derived and point out relevant literature....

  17. Pattern-oriented modeling of agent-based complex systems: lessons from ecology

    NARCIS (Netherlands)

    Grimm, V.; Revilla, E.; Berger, U.; Jeltsch, F.; Mooij, W.M.; Railsback, S.F.; Thulke, H-H.; Weiner, J.; Wiegand, T.; DeAngelis, D.L.

    2005-01-01

    Agent-based complex systems are dynamic networks of many interacting agents; examples include ecosystems, financial markets, and cities. The search for general principles underlying the internal organization of such systems often uses bottom-up simulation models such as cellular automata and

  18. Statistical physics of complex networks

    Science.gov (United States)

    Xie, Huafeng

    We live in a connected world. It is of great practical importance and intellectual appeal to understand the networks surrounding us. In this work we study ranking of the nodes in complex networks. In large networks such as World Wide Web (WWW) and citation networks of scientific literature, searching by keywords is a common practice to retrieve useful information. On the WWW, apart from the contents of webpages, the topology of the network itself can be a rich source of information about their relative importance and relevancy to the search query. It is the effective utilization of this topological information [50] which advanced the Google search engine to its present position of the most popular tool on the WWW. The World-Wide Web (WWW) is characterized by a strong community structure in which communities of webpages are densely interconnected by hyperlinks. We study how such network architecture affects the average Google ranking of individual webpages in the community. Using a mean-field approximation, we quantify how the average Google rank of community's webpages depends on the degree to which it is isolated from the rest of the world in both incoming and outgoing directions, and alpha -- the only intrinsic parameter of Google's PageRank algorithm. We proceed with numerical study of simulated networks and empirical study of several internal web-communities within two US universities. The predictions of our mean-field treatment were qualitatively verified in those real-life networks. Furthermore, the value alpha = 0.15 used by Google seems to be optimized for the degree of isolation of communities as they exist in the actual WWW. We then extend Google's PageRank algorithm to citation networks of scientific literature. Unlike hyperlinks, citations cannot be updated after the point of publication. This results in strong aging characteristics of citation networks that affect the performance of the PageRank algorithm. To rectify this we modify the Page

  19. Fault Tolerance Mobile Agent System Using Witness Agent in 2-Dimensional Mesh Network

    Directory of Open Access Journals (Sweden)

    Ahmad Rostami

    2010-09-01

    Full Text Available Mobile agents are computer programs that act autonomously on behalf of a user or its owner and travel through a network of heterogeneous machines. Fault tolerance is important in their itinerary. In this paper, existent methods of fault tolerance in mobile agents are described which they are considered in linear network topology. In the methods three agents are used to fault tolerance by cooperating to each others for detecting and recovering server and agent failure. Three types of agents are: actual agent which performs programs for its owner, witness agent which monitors the actual agent and the witness agent after itself, probe which is sent for recovery the actual agent or the witness agent on the side of the witness agent. Communication mechanism in the methods is message passing between these agents. The methods are considered in linear network. We introduce our witness agent approach for fault tolerance mobile agent systems in Two Dimensional Mesh (2D-Mesh Network. Indeed Our approach minimizes Witness-Dependency in this network and then represents its algorithm.

  20. Biodegradability of ethylenediamine-based complexing agents.

    Science.gov (United States)

    Sýkora, V; Pitter, P; Bittnerová, I; Lederer, T

    2001-06-01

    Biological degradability of ethylenediamine derivatives depends on the type and number of substituents. The susceptibility to biodegradation decreases in the sequence of substituents -COCH3, -CH3, -C2H5, -CH2CH2OH, -CH2COOH and with polysubstitution. The biodegradability depends also on the kind and number of nitrogen atoms. Complexing agents with a single-nitrogen atom in the molecule (e.g. NTA) succumb relatively readily to biodegradation whereas, compounds with two or more tertiary amino groups are biologically highly stable and do not undergo biodegradation even in experiments with activated sludge adapted at an age of up to 30 days (EDTA, DTPA, PDTA, HEDTA). A lowering of the degree of substitution brings about an increased susceptibility to biodegradation. This holds, e.g., for replacement of tertiary amino groups with secondary ones; thus the symmetrically disubstituted ethylenediamine-N,N'-diacetic acid (EDDA) possesses still sufficient complexing ability while belonging already to the group of potentially degradable substances.

  1. Consensus clustering in complex networks

    CERN Document Server

    Lancichinetti, Andrea; 10.1038/srep00336

    2012-01-01

    The community structure of complex networks reveals both their organization and hidden relationships among their constituents. Most community detection methods currently available are not deterministic, and their results typically depend on the specific random seeds, initial conditions and tie-break rules adopted for their execution. Consensus clustering is used in data analysis to generate stable results out of a set of partitions delivered by stochastic methods. Here we show that consensus clustering can be combined with any existing method in a self-consistent way, enhancing considerably both the stability and the accuracy of the resulting partitions. This framework is also particularly suitable to monitor the evolution of community structure in temporal networks. An application of consensus clustering to a large citation network of physics papers demonstrates its capability to keep track of the birth, death and diversification of topics.

  2. Nested subgraphs of complex networks

    Energy Technology Data Exchange (ETDEWEB)

    Corominas-Murtra, Bernat; Sole, Ricard V [ICREA-Complex Systems Lab, Universitat Pompeu Fabra, Dr Aiguader 80, 08003 Barcelona (Spain); Mendes, Jose F F [Departamento de Fisica da Universidade de Aveiro, 3810-193 Aveiro (Portugal)], E-mail: bernat.corominas@upf.edu

    2008-09-26

    We analytically explore the scaling properties of a general class of nested subgraphs in complex networks, which includes the K-core and the K-scaffold, among others. We name such a class of subgraphs K-nested subgraphs since they generate families of subgraphs such that ...S{sub K+1}(G) subset or equal S{sub K}(G) subset or equal S{sub K-1}(G).... Using the so-called configuration model it is shown that any family of nested subgraphs over a network with diverging second moment and finite first moment has infinite elements (i.e. lacking a percolation threshold). Moreover, for a scale-free network with the above properties, we show that any nested family of subgraphs is self-similar by looking at the degree distribution. Both numerical simulations and real data are analyzed and display good agreement with our theoretical predictions.

  3. Theoretical research progress in complexity of complex dynamical networks

    Institute of Scientific and Technical Information of China (English)

    Fang Jinqing

    2007-01-01

    This article reviews the main progress in dynamical complexity of theoretical models for nonlinear complex networks proposed by our Joint Complex Network Research Group (JCNRG). The topological and dynamical properties of these theoretical models are numerically and analytically studied. Several findings are useful for understanding and deeply studying complex networks from macroscopic to microscopic levels and have a potential of applications in real-world networks.

  4. Bell Inequalities for Complex Networks

    Science.gov (United States)

    2015-10-26

    AFRL-AFOSR-VA-TR-2015-0355 YIP Bell Inequalities for Complex Networks Greg Ver Steeg UNIVERSITY OF SOUTHERN CALIFORNIA LOS ANGELES Final Report 10/26...Period: 1 August 2012 to 31 July 2015 Information Sciences Institute University of Southern California, 4676 Admiralty Way Marina del Rey, CA 90292...Machine Intelligence and Autonomy ” in 2014. Besides these Air Force affiliated interactions, I disseminated results of this effort in standard academic

  5. Measurement methods on the complexity of network

    Institute of Scientific and Technical Information of China (English)

    LIN Lin; DING Gang; CHEN Guo-song

    2010-01-01

    Based on the size of network and the number of paths in the network,we proposed a model of topology complexity of a network to measure the topology complexity of the network.Based on the analyses of the effects of the number of the equipment,the types of equipment and the processing time of the node on the complexity of the network with the equipment-constrained,a complexity model of equipment-constrained network was constructed to measure the integrated complexity of the equipment-constrained network.The algorithms for the two models were also developed.An automatic generator of the random single label network was developed to test the models.The results show that the models can correctly evaluate the topology complexity and the integrated complexity of the networks.

  6. Consensus and Synchronization in Complex Networks

    CERN Document Server

    2013-01-01

    Synchronization in complex networks is one of the most captivating cooperative phenomena in nature and has been shown to be of fundamental importance in such varied circumstances as the continued existence of species, the functioning of heart pacemaker cells, epileptic seizures, neuronal firing in the feline visual cortex and cognitive tasks in humans. E.g. coupled visual and acoustic interactions make fireflies flash, crickets chirp, and an audience clap in unison. On the other hand, in distributed systems and networks, it is often necessary for some or all of the nodes to calculate some function of certain parameters, e.g. sink nodes in sensor networks being tasked with calculating the average measurement value of all the sensors or multi-agent systems in which all agents are required to coordinate their speed and direction. When all nodes calculate the same function of the initial values in the system, they are said to reach consensus. Such concepts - sometimes also called state agreement, rendezvous, and ...

  7. Epidemic and Cascading Survivability of Complex Networks

    DEFF Research Database (Denmark)

    Manzano, Marc; Calle, Eusebi; Ripoll, Jordi

    2014-01-01

    Our society nowadays is governed by complex networks, examples being the power grids, telecommunication networks, biological networks, and social networks. It has become of paramount importance to understand and characterize the dynamic events (e.g. failures) that might happen in these complex...

  8. Perancangan Network Monitoring Tools Menggunakan Autonomous Agent Java

    Directory of Open Access Journals (Sweden)

    Khurniawan Eko S

    2016-08-01

    Full Text Available Tugas pengelolaan jaringan yang dilakukan administrator jaringan diantaranya yaitu pengumpulan informasi resource jaringan yang tersedia. Teknologi SNMP (Simple Network Management Protocol memberikan fleksibilitas bagi administrator jaringan dalam mengatur network secara keseluruhan dari satu lokasi. Aplikasi Network Monitoring Tools berbasis Agent JAVA terdiri dari Master agent yang bertugas untuk melakukan management Request agent serta akses database. Request agent yang bertugas untuk melakukan pemantauan server yang mengimplementasi library SNMP4j dengan sistem multi-agent. Disisi interface, aplikasi Network Monitoring Tools menggunakan media web sebagai interface administrator sehingga dapat digunakan darimana saja  dan kapan saja.  Hasil dari penelitian ini memperlihatkan bahwa aplikasi yang dibuat bekerja sebagai Network Monitoring Tools mampu bekerja dengan persen error pada kisaran 0-18%. Selain itu Aplikasi ini menghasilkan tren pembacaan data server lebih stabil dan cepat dibandingkan dengan aplikasi Cacti. Hal ini didukung oleh kemampuan Request Agent yang mampu merespon tingkat beban kerja server yang di pantau.

  9. Durer-pentagon-based complex network

    Directory of Open Access Journals (Sweden)

    Rui Hou

    2016-04-01

    Full Text Available A novel Durer-pentagon-based complex network was constructed by adding a centre node. The properties of the complex network including the average degree, clustering coefficient, average path length, and fractal dimension were determined. The proposed complex network is small-world and fractal.

  10. Robustness and Optimization of Complex Networks: Reconstructability, Algorithms and Modeling

    NARCIS (Netherlands)

    Liu, D.

    2013-01-01

    The infrastructure networks, including the Internet, telecommunication networks, electrical power grids, transportation networks (road, railway, waterway, and airway networks), gas networks and water networks, are becoming more and more complex. The complex infrastructure networks are crucial to our

  11. Mapping Nuclear Decay to Complex Network

    Institute of Scientific and Technical Information of China (English)

    2011-01-01

    Network model is always a key topic in the research of network science. Large Unifying Hybrid Network (LUHNM) theory, which we proposed before, is a universal network model that can be used to depict the diversity and complexity of the natural network.

  12. Emergent self-organized complex network topology out of stability constraints.

    Science.gov (United States)

    Perotti, Juan I; Billoni, Orlando V; Tamarit, Francisco A; Chialvo, Dante R; Cannas, Sergio A

    2009-09-04

    Although most networks in nature exhibit complex topologies, the origins of such complexity remain unclear. We propose a general evolutionary mechanism based on global stability. This mechanism is incorporated into a model of a growing network of interacting agents in which each new agent's membership in the network is determined by the agent's effect on the network's global stability. It is shown that out of this stability constraint complex topological properties emerge in a self-organized manner, offering an explanation for their observed ubiquity in biological networks.

  13. Spreading dynamics in complex networks

    CERN Document Server

    Pei, Sen

    2013-01-01

    Searching for influential spreaders in complex networks is an issue of great significance for applications across various domains, ranging from the epidemic control, innovation diffusion, viral marketing, social movement to idea propagation. In this paper, we first display some of the most important theoretical models that describe spreading processes, and then discuss the problem of locating both the individual and multiple influential spreaders respectively. Recent approaches in these two topics are presented. For the identification of privileged single spreaders, we summarize several widely used centralities, such as degree, betweenness centrality, PageRank, k-shell, etc. We investigate the empirical diffusion data in a large scale online social community -- LiveJournal. With this extensive dataset, we find that various measures can convey very distinct information of nodes. Of all the users in LiveJournal social network, only a small fraction of them involve in spreading. For the spreading processes in Li...

  14. Complexity and state-transitions in social dependence networks

    Directory of Open Access Journals (Sweden)

    Giuliano Pistolesi

    2001-01-01

    Full Text Available Computation of complexity in Social Dependence Networks is an interesting research domain to understand evolution processes and group exchange dynamics in natural and artificial intelligent Multi-Agent Systems. We perform an agent-based simulation by NET-PLEX (Conte and Pistolesi, 2000, a new software system able both to build interdependence networks tipically emerging in Multi-Agent System scenarios and to investigate complexity phenomena, i.e., unstability and state-transitions like Hopf bifurcation (Nowak and Lewenstein, 1994, and to describe social self organization phenomena emerging in these artificial social systems by means of complexity measures similar to those introduced by Hubermann and Hogg (1986. By performing analysis of complexity in these kind of artificial societies we observed interesting phenomena in emerging organizations that suggest state-transitions induced by critical configurations of parameters describing the social system similar to those observed in many studies on state-transitions in bifurcation chaos (Schuster, 1988; Ruelle, 1989.

  15. Aging in complex interdependency networks

    Science.gov (United States)

    Vural, Dervis C.; Morrison, Greg; Mahadevan, L.

    2014-02-01

    Although species longevity is subject to a diverse range of evolutionary forces, the mortality curves of a wide variety of organisms are rather similar. Here we argue that qualitative and quantitative features of aging can be reproduced by a simple model based on the interdependence of fault-prone agents on one other. In addition to fitting our theory to the empiric mortality curves of six very different organisms, we establish the dependence of lifetime and aging rate on initial conditions, damage and repair rate, and system size. We compare the size distributions of disease and death and see that they have qualitatively different properties. We show that aging patterns are independent of the details of interdependence network structure, which suggests that aging is a many-body effect, and that the qualitative and quantitative features of aging are not sensitively dependent on the details of dependency structure or its formation.

  16. Recent advances in agent-based complex automated negotiation

    CERN Document Server

    Ito, Takayuki; Zhang, Minjie; Fujita, Katsuhide; Robu, Valentin

    2016-01-01

    This book covers recent advances in Complex Automated Negotiations as a widely studied emerging area in the field of Autonomous Agents and Multi-Agent Systems. The book includes selected revised and extended papers from the 7th International Workshop on Agent-Based Complex Automated Negotiation (ACAN2014), which was held in Paris, France, in May 2014. The book also includes brief introductions about Agent-based Complex Automated Negotiation which are based on tutorials provided in the workshop, and brief summaries and descriptions about the ANAC'14 (Automated Negotiating Agents Competition) competition, where authors of selected finalist agents explain the strategies and the ideas used by them. The book is targeted to academic and industrial researchers in various communities of autonomous agents and multi-agent systems, such as agreement technology, mechanism design, electronic commerce, related areas, as well as graduate, undergraduate, and PhD students working in those areas or having interest in them.

  17. Reorganizing Complex Network to Improve Large-Scale Multiagent Teamwork

    Directory of Open Access Journals (Sweden)

    Yang Xu

    2014-01-01

    Full Text Available Large-scale multiagent teamwork has been popular in various domains. Similar to human society infrastructure, agents only coordinate with some of the others, with a peer-to-peer complex network structure. Their organization has been proven as a key factor to influence their performance. To expedite team performance, we have analyzed that there are three key factors. First, complex network effects may be able to promote team performance. Second, coordination interactions coming from their sources are always trying to be routed to capable agents. Although they could be transferred across the network via different paths, their sources and sinks depend on the intrinsic nature of the team which is irrelevant to the network connections. In addition, the agents involved in the same plan often form a subteam and communicate with each other more frequently. Therefore, if the interactions between agents can be statistically recorded, we are able to set up an integrated network adjustment algorithm by combining the three key factors. Based on our abstracted teamwork simulations and the coordination statistics, we implemented the adaptive reorganization algorithm. The experimental results briefly support our design that the reorganized network is more capable of coordinating heterogeneous agents.

  18. In search of stars: network formation among heterogeneous agents

    NARCIS (Netherlands)

    Goeree, J.K.; Riedl, A.; Ule, A.

    2007-01-01

    This paper reports results from a laboratory experiment on network formation among heterogeneous agents. The experimental design extends the Bala-Goyal (2000) model of network formation with decay and two-way flow of benefits by allowing for agents with lower linking costs or higher benefits to

  19. In search of stars: network formation among heterogeneous agents

    NARCIS (Netherlands)

    J.K. Goeree; A. Riedl; A. Ule

    2007-01-01

    This paper reports results from a laboratory experiment on network formation among heterogeneous agents. The experimental design extends the Bala-Goyal (2000) model of network formation with decay and two-way flow of benefits by allowing for agents with lower linking costs or higher benefits to othe

  20. Structural Analysis of Complex Networks

    CERN Document Server

    Dehmer, Matthias

    2011-01-01

    Filling a gap in literature, this self-contained book presents theoretical and application-oriented results that allow for a structural exploration of complex networks. The work focuses not only on classical graph-theoretic methods, but also demonstrates the usefulness of structural graph theory as a tool for solving interdisciplinary problems. Applications to biology, chemistry, linguistics, and data analysis are emphasized. The book is suitable for a broad, interdisciplinary readership of researchers, practitioners, and graduate students in discrete mathematics, statistics, computer science,

  1. Mathematical Properties of Complex Networks

    Directory of Open Access Journals (Sweden)

    Angel Garrido

    2011-01-01

    Full Text Available Many researchers are attempting to create systems which
    mimic human thought, or understand speech, or beat to the best human chess-player [14]. Understanding intelligence and Creating intelligent artifacts both are the twin goals of Artificial Intelligence (AI.In more recent times, the interest is focused on problems related with Complex Networks [3, 5,6, 19], in particular on questions such as clustering search and identification. We attempt, in this paper, a panoramic vision of such mathematical methods in AI.

  2. Longest-path attacks on complex networks

    CERN Document Server

    Pu, Cunlai

    2014-01-01

    We investigate the longest-path attacks on complex networks. Specifically, we remove approximately the longest simple path from a network iteratively until there are no paths left in the network. We propose two algorithms, the random augmenting approach (RPA) and the Hamilton-path based approach (HPA), for finding the approximately longest simple path in a network. Results demonstrate that steps of longest-path attacks increase with network density linearly for random networks, while exponentially increasing for scale-free networks. The more homogeneous the degree distribution is, the more fragile the network, which is totally different from the previous results of node or edge attacks. HPA is generally more efficient than RPA in the longest-path attacks of complex networks. These findings further help us understand the vulnerability of complex systems, better protect complex systems, and design more tolerant complex systems.

  3. A new information dimension of complex networks

    Energy Technology Data Exchange (ETDEWEB)

    Wei, Daijun [School of Computer and Information Science, Southwest University, Chongqing 400715 (China); School of Science, Hubei University for Nationalities, Enshi 445000 (China); Wei, Bo [School of Computer and Information Science, Southwest University, Chongqing 400715 (China); Hu, Yong [Institute of Business Intelligence and Knowledge Discovery, Guangdong University of Foreign Studies, Guangzhou 510006 (China); Zhang, Haixin [School of Computer and Information Science, Southwest University, Chongqing 400715 (China); Deng, Yong, E-mail: ydeng@swu.edu.cn [School of Computer and Information Science, Southwest University, Chongqing 400715 (China); School of Engineering, Vanderbilt University, TN 37235 (United States)

    2014-03-01

    Highlights: •The proposed measure is more practical than the classical information dimension. •The difference of information for box in the box-covering algorithm is considered. •Results indicate the measure can capture the fractal property of complex networks. -- Abstract: The fractal and self-similarity properties are revealed in many complex networks. The classical information dimension is an important method to study fractal and self-similarity properties of planar networks. However, it is not practical for real complex networks. In this Letter, a new information dimension of complex networks is proposed. The nodes number in each box is considered by using the box-covering algorithm of complex networks. The proposed method is applied to calculate the fractal dimensions of some real networks. Our results show that the proposed method is efficient when dealing with the fractal dimension problem of complex networks.

  4. Project SAFE. Complexing agents in SFR

    Energy Technology Data Exchange (ETDEWEB)

    Fanger, G.; Skagius, K.; Wiborgh, M. [Kemakta Konsult AB, Stockholm (Sweden)

    2001-01-01

    number (56) of waste packages of waste type S.09. The presence of cellulose based additives in cement used as backfill was evaluated. Calculations resulted in a concentration of ISA below critical levels. For the waste types in BLA the presence of complexing agents has not been studied as no credit is given in the safety assessment to sorption in this repository part (no cement/concrete). The performed calculations have shown that, due to the presence of ISA and other complexants in SFR, a reduction in sorption may have to be applied for some elements in certain waste types when carrying out calculations of the radionuclide transport (the number of waste types depends on assumptions regarding the ISA yield). It should be pointed out that the estimates of concentrations in different waste types are based on a number of conservative assumptions, thus the actual concentrations are probably lower than the calculated.

  5. Minimum complexity echo state network.

    Science.gov (United States)

    Rodan, Ali; Tino, Peter

    2011-01-01

    Reservoir computing (RC) refers to a new class of state-space models with a fixed state transition structure (the reservoir) and an adaptable readout form the state space. The reservoir is supposed to be sufficiently complex so as to capture a large number of features of the input stream that can be exploited by the reservoir-to-output readout mapping. The field of RC has been growing rapidly with many successful applications. However, RC has been criticized for not being principled enough. Reservoir construction is largely driven by a series of randomized model-building stages, with both researchers and practitioners having to rely on a series of trials and errors. To initialize a systematic study of the field, we concentrate on one of the most popular classes of RC methods, namely echo state network, and ask: What is the minimal complexity of reservoir construction for obtaining competitive models and what is the memory capacity (MC) of such simplified reservoirs? On a number of widely used time series benchmarks of different origin and characteristics, as well as by conducting a theoretical analysis we show that a simple deterministically constructed cycle reservoir is comparable to the standard echo state network methodology. The (short-term) MC of linear cyclic reservoirs can be made arbitrarily close to the proved optimal value.

  6. Novel insights in agent-based complex automated negotiation

    CERN Document Server

    Lopez-Carmona, Miguel; Ito, Takayuki; Zhang, Minjie; Bai, Quan; Fujita, Katsuhide

    2014-01-01

    This book focuses on all aspects of complex automated negotiations, which are studied in the field of autonomous agents and multi-agent systems. This book consists of two parts. I: Agent-Based Complex Automated Negotiations, and II: Automated Negotiation Agents Competition. The chapters in Part I are extended versions of papers presented at the 2012 international workshop on Agent-Based Complex Automated Negotiation (ACAN), after peer reviews by three Program Committee members. Part II examines in detail ANAC 2012 (The Third Automated Negotiating Agents Competition), in which automated agents that have different negotiation strategies and are implemented by different developers are automatically negotiated in the several negotiation domains. ANAC is an international competition in which automated negotiation strategies, submitted by a number of universities and research institutes across the world, are evaluated in tournament style. The purpose of the competition is to steer the research in the area of bilate...

  7. Synchronizability on complex networks via pinning control

    Indian Academy of Sciences (India)

    Yi Liang; Xingyuan Wang

    2013-04-01

    It is proved that the maximum eigenvalue sequence of the principal submatrices of coupling matrix is decreasing. The method of calculating the number of pinning nodes is given based on this theory. The findings reveal the relationship between the decreasing speed of maximum eigenvalue sequence of the principal submatrices for coupling matrix and the synchronizability on complex networks via pinning control. We discuss the synchronizability on some networks, such as scale-free networks and small-world networks. Numerical simulations show that different pinning strategies have different pinning synchronizability on the same complex network, and the synchronizability with pinning control is consistent with one without pinning control in various complex networks.

  8. A Comparison of Geographic Information Systems, Complex Networks, and Other Models for Analyzing Transportation Network Topologies

    Science.gov (United States)

    Alexandrov, Natalia (Technical Monitor); Kuby, Michael; Tierney, Sean; Roberts, Tyler; Upchurch, Christopher

    2005-01-01

    This report reviews six classes of models that are used for studying transportation network topologies. The report is motivated by two main questions. First, what can the "new science" of complex networks (scale-free, small-world networks) contribute to our understanding of transport network structure, compared to more traditional methods? Second, how can geographic information systems (GIS) contribute to studying transport networks? The report defines terms that can be used to classify different kinds of models by their function, composition, mechanism, spatial and temporal dimensions, certainty, linearity, and resolution. Six broad classes of models for analyzing transport network topologies are then explored: GIS; static graph theory; complex networks; mathematical programming; simulation; and agent-based modeling. Each class of models is defined and classified according to the attributes introduced earlier. The paper identifies some typical types of research questions about network structure that have been addressed by each class of model in the literature.

  9. In search of stars: network formation among heterogeneous agents

    NARCIS (Netherlands)

    J.K. Goeree; A. Riedl; A. Ule

    2009-01-01

    This paper reports results from a laboratory experiment on network formation among heterogeneous agents. The experimental design extends the Bala-Goyal [Bala, V., Goyal, S., 2000. A non-cooperative model of network formation, Econometrica 68, 1131-1230] model of network formation with decay and two-

  10. Agent-oriented modeling of the dynamics of complex biological processes I: single agent models

    NARCIS (Netherlands)

    Jonker, C.M.; Treur, J.

    2008-01-01

    In the pair of papers of which this is Part I, the agent-oriented modeling perspective to cope with biological complexity is discussed. Three levels of dynamics are distinguished and related to each other: dynamics of externally observable agent behavior, dynamics of internal agent processes, and dy

  11. Cobalt Complexes as Antiviral and Antibacterial Agents

    Science.gov (United States)

    2010-01-01

    L = thioacetamide L = semicarbazide L = thiosemicarbazide L = pyrazole Pharmaceuticals 2010, 3 1719 The complexes...alanine; c: alanine methyl ester d: pyrazole ; e: dimethyl pyrazole L L = 29 28 Organometallic complexes containing a formal metal carbon bond are

  12. Global behavior of dynamical agents in directed network

    Institute of Scientific and Technical Information of China (English)

    Hongwang YU; Yufan ZHENG

    2009-01-01

    This paper investigates the global behavior of controlled dynamical agents in directed networks.The agents are Lyapunov stable,are distributed in a line,and communicate through a directed network.The communication topology of the network is characterized by a directed graph and the control protocol is designed in simple linear decentralized feedback law.We study the different conditions under which agents will achieve aggregation,and critical and divergent trajectories,respectively.Our investigation on the dynamical agent system under network is extended to the time-delay network case.Furthermore,we study the case with two pre-specified virtual leaders in the system.Numerical simulations are given and demonstrate that our theoretical results are effective.

  13. Using Swarming Agents for Scalable Security in Large Network Environments

    Energy Technology Data Exchange (ETDEWEB)

    Crouse, Michael; White, Jacob L.; Fulp, Errin W.; Berenhaut, Kenneth S.; Fink, Glenn A.; Haack, Jereme N.

    2011-09-23

    The difficulty of securing computer infrastructures increases as they grow in size and complexity. Network-based security solutions such as IDS and firewalls cannot scale because of exponentially increasing computational costs inherent in detecting the rapidly growing number of threat signatures. Hostbased solutions like virus scanners and IDS suffer similar issues, and these are compounded when enterprises try to monitor these in a centralized manner. Swarm-based autonomous agent systems like digital ants and artificial immune systems can provide a scalable security solution for large network environments. The digital ants approach offers a biologically inspired design where each ant in the virtual colony can detect atoms of evidence that may help identify a possible threat. By assembling the atomic evidences from different ant types the colony may detect the threat. This decentralized approach can require, on average, fewer computational resources than traditional centralized solutions; however there are limits to its scalability. This paper describes how dividing a large infrastructure into smaller managed enclaves allows the digital ant framework to effectively operate in larger environments. Experimental results will show that using smaller enclaves allows for more consistent distribution of agents and results in faster response times.

  14. Cobalt Complexes as Antiviral and Antibacterial Agents

    Directory of Open Access Journals (Sweden)

    Eddie L. Chang

    2010-05-01

    Full Text Available Metal ion complexes are playing an increasing role in the development of antimicrobials. We review here the antimicrobial properties of cobalt coordination complexes in oxidation state 3+. In addition to reviewing the cobalt complexes containing polydentate donor ligands, we also focus on the antimicrobial activity of the homoleptic [Co(NH36]3+ ion.

  15. Cobalt Complexes as Antiviral and Antibacterial Agents

    OpenAIRE

    Eddie L. Chang; Christa Simmers; D. Andrew Knight

    2010-01-01

    Metal ion complexes are playing an increasing role in the development of antimicrobials. We review here the antimicrobial properties of cobalt coordination complexes in oxidation state 3+. In addition to reviewing the cobalt complexes containing polydentate donor ligands, we also focus on the antimicrobial activity of the homoleptic [Co(NH3)6]3+ ion.

  16. A Complex Network Approach to Stylometry.

    Directory of Open Access Journals (Sweden)

    Diego Raphael Amancio

    Full Text Available Statistical methods have been widely employed to study the fundamental properties of language. In recent years, methods from complex and dynamical systems proved useful to create several language models. Despite the large amount of studies devoted to represent texts with physical models, only a limited number of studies have shown how the properties of the underlying physical systems can be employed to improve the performance of natural language processing tasks. In this paper, I address this problem by devising complex networks methods that are able to improve the performance of current statistical methods. Using a fuzzy classification strategy, I show that the topological properties extracted from texts complement the traditional textual description. In several cases, the performance obtained with hybrid approaches outperformed the results obtained when only traditional or networked methods were used. Because the proposed model is generic, the framework devised here could be straightforwardly used to study similar textual applications where the topology plays a pivotal role in the description of the interacting agents.

  17. A Complex Network Approach to Stylometry.

    Science.gov (United States)

    Amancio, Diego Raphael

    2015-01-01

    Statistical methods have been widely employed to study the fundamental properties of language. In recent years, methods from complex and dynamical systems proved useful to create several language models. Despite the large amount of studies devoted to represent texts with physical models, only a limited number of studies have shown how the properties of the underlying physical systems can be employed to improve the performance of natural language processing tasks. In this paper, I address this problem by devising complex networks methods that are able to improve the performance of current statistical methods. Using a fuzzy classification strategy, I show that the topological properties extracted from texts complement the traditional textual description. In several cases, the performance obtained with hybrid approaches outperformed the results obtained when only traditional or networked methods were used. Because the proposed model is generic, the framework devised here could be straightforwardly used to study similar textual applications where the topology plays a pivotal role in the description of the interacting agents.

  18. Complexity Characteristics of Currency Networks

    Science.gov (United States)

    Gorski, A. Z.; Drozdz, S.; Kwapien, J.; Oswiecimka, P.

    2006-11-01

    A large set of daily FOREX time series is analyzed. The corresponding correlation matrices (CM) are constructed for USD, EUR and PLN used as the base currencies. The triangle rule is interpreted as constraints reducing the number of independent returns. The CM spectrum is computed and compared with the cases of shuffled currencies and a fictitious random currency taken as a base currency. The Minimal Spanning Tree (MST) graphs are calculated and the clustering effects for strong currencies are found. It is shown that for MSTs the node rank has power like, scale free behavior. Finally, the scaling exponents are evaluated and found in the range analogous to those identified recently for various complex networks.

  19. Community structure of complex networks based on continuous neural network

    Science.gov (United States)

    Dai, Ting-ting; Shan, Chang-ji; Dong, Yan-shou

    2017-09-01

    As a new subject, the research of complex networks has attracted the attention of researchers from different disciplines. Community structure is one of the key structures of complex networks, so it is a very important task to analyze the community structure of complex networks accurately. In this paper, we study the problem of extracting the community structure of complex networks, and propose a continuous neural network (CNN) algorithm. It is proved that for any given initial value, the continuous neural network algorithm converges to the eigenvector of the maximum eigenvalue of the network modularity matrix. Therefore, according to the stability of the evolution of the network symbol will be able to get two community structure.

  20. Spreading dynamics in complex networks

    Science.gov (United States)

    Pei, Sen; Makse, Hernán A.

    2013-12-01

    Searching for influential spreaders in complex networks is an issue of great significance for applications across various domains, ranging from epidemic control, innovation diffusion, viral marketing, and social movement to idea propagation. In this paper, we first display some of the most important theoretical models that describe spreading processes, and then discuss the problem of locating both the individual and multiple influential spreaders respectively. Recent approaches in these two topics are presented. For the identification of privileged single spreaders, we summarize several widely used centralities, such as degree, betweenness centrality, PageRank, k-shell, etc. We investigate the empirical diffusion data in a large scale online social community—LiveJournal. With this extensive dataset, we find that various measures can convey very distinct information of nodes. Of all the users in the LiveJournal social network, only a small fraction of them are involved in spreading. For the spreading processes in LiveJournal, while degree can locate nodes participating in information diffusion with higher probability, k-shell is more effective in finding nodes with a large influence. Our results should provide useful information for designing efficient spreading strategies in reality.

  1. Epidemic and Cascading Survivability of Complex Networks

    CERN Document Server

    Manzano, Marc; Ripoll, Jordi; Fagertun, Anna Manolova; Torres-Padrosa, Victor; Pahwa, Sakshi; Scoglio, Caterina

    2014-01-01

    Our society nowadays is governed by complex networks, examples being the power grids, telecommunication networks, biological networks, and social networks. It has become of paramount importance to understand and characterize the dynamic events (e.g. failures) that might happen in these complex networks. For this reason, in this paper, we propose two measures to evaluate the vulnerability of complex networks in two different dynamic multiple failure scenarios: epidemic-like and cascading failures. Firstly, we present \\emph{epidemic survivability} ($ES$), a new network measure that describes the vulnerability of each node of a network under a specific epidemic intensity. Secondly, we propose \\emph{cascading survivability} ($CS$), which characterizes how potentially injurious a node is according to a cascading failure scenario. Then, we show that by using the distribution of values obtained from $ES$ and $CS$ it is possible to describe the vulnerability of a given network. We consider a set of 17 different compl...

  2. Leader Election for Anonymous Asynchronous Agents in Arbitrary Networks

    CERN Document Server

    Dereniowski, Dariusz

    2012-01-01

    We study the problem of leader election among mobile agents operating in an arbitrary network modeled as an undirected graph. Nodes of the network are unlabeled and all agents are identical. Hence the only way to elect a leader among agents is by exploiting asymmetries in their initial positions in the graph. Agents do not know the graph or their positions in it, hence they must gain this knowledge by navigating in the graph and share it with other agents to accomplish leader election. This can be done using meetings of agents, which is difficult because of their asynchronous nature: an adversary has total control over the speed of agents. When can a leader be elected in this adversarial scenario and how to do it? We give a complete answer to this question by characterizing all initial configurations for which leader election is possible and by constructing an algorithm that accomplishes leader election for all configurations for which this can be done.

  3. Outer Synchronization of Complex Networks by Impulse

    Institute of Scientific and Technical Information of China (English)

    孙文; 燕子宗; 陈士华; 吕金虎

    2011-01-01

    This paper investigates outer synchronization of complex networks, especially, outer complete synchronization and outer anti-synchronization between the driving network and the response network. Employing the impulsive control method which is uncontinuous, simple, efficient, low-cost and easy to implement in practical applications, we obtain some sufficient conditions of outer complete synchronization and outer anti-synchronization between two complex networks. Numerical simulations demonstrate the effectiveness of the proposed impulsive control scheme.

  4. How random are complex networks

    CERN Document Server

    Orsini, Chiara; Jamakovic, Almerima; Mahadevan, Priya; Colomer-de-Simón, Pol; Vahdat, Amin; Bassler, Kevin E; Toroczkai, Zoltán; Boguñá, Marián; Caldarelli, Guido; Fortunato, Santo; Krioukov, Dmitri

    2015-01-01

    Represented as graphs, real networks are intricate combinations of order and disorder. Fixing some of the structural properties of network models to their values observed in real networks, many other properties appear as statistical consequences of these fixed observables, plus randomness in other respects. Here we employ the $dk$-series, a complete set of basic characteristics of the network structure, to study the statistical dependencies between different network properties. We consider six real networks---the Internet, US airport network, human protein interactions, technosocial web of trust, English word network, and an fMRI map of the human brain---and find that many important local and global structural properties of these networks are closely reproduced by $dk$-random graphs whose degree distributions, degree correlations, and clustering are as in the corresponding real network. We discuss important conceptual, methodological, and practical implications of this evaluation of network randomness.

  5. Optimising the topology of complex neural networks

    CERN Document Server

    Jiang, Fei; Schoenauer, Marc

    2007-01-01

    In this paper, we study instances of complex neural networks, i.e. neural netwo rks with complex topologies. We use Self-Organizing Map neural networks whose n eighbourhood relationships are defined by a complex network, to classify handwr itten digits. We show that topology has a small impact on performance and robus tness to neuron failures, at least at long learning times. Performance may howe ver be increased (by almost 10%) by artificial evolution of the network topo logy. In our experimental conditions, the evolved networks are more random than their parents, but display a more heterogeneous degree distribution.

  6. Higher-order organization of complex networks.

    Science.gov (United States)

    Benson, Austin R; Gleich, David F; Leskovec, Jure

    2016-07-08

    Networks are a fundamental tool for understanding and modeling complex systems in physics, biology, neuroscience, engineering, and social science. Many networks are known to exhibit rich, lower-order connectivity patterns that can be captured at the level of individual nodes and edges. However, higher-order organization of complex networks--at the level of small network subgraphs--remains largely unknown. Here, we develop a generalized framework for clustering networks on the basis of higher-order connectivity patterns. This framework provides mathematical guarantees on the optimality of obtained clusters and scales to networks with billions of edges. The framework reveals higher-order organization in a number of networks, including information propagation units in neuronal networks and hub structure in transportation networks. Results show that networks exhibit rich higher-order organizational structures that are exposed by clustering based on higher-order connectivity patterns.

  7. Synchronization of fractional order complex dynamical networks

    Science.gov (United States)

    Wang, Yu; Li, Tianzeng

    2015-06-01

    In this letter the synchronization of complex dynamical networks with fractional order chaotic nodes is studied. A fractional order controller for synchronization of complex network is presented. Some new sufficient synchronization criteria are proposed based on the Lyapunov stability theory and the LaSalle invariance principle. These synchronization criteria can apply to an arbitrary fractional order complex network in which the coupling-configuration matrix and the inner-coupling matrix are not assumed to be symmetric or irreducible. It means that this method is more general and effective. Numerical simulations of two fractional order complex networks demonstrate the universality and the effectiveness of the proposed method.

  8. Complex-network description of seismicity

    Directory of Open Access Journals (Sweden)

    S. Abe

    2006-01-01

    Full Text Available The seismic data taken in California and Japan are mapped to growing random networks. It is shown in the undirected network picture that these earthquake networks are scale-free and small-work networks with the power-law connectivity distributions, the large values of the clustering coefficient, and the small values of the average path length. It is demonstrated how the present network approach reveals complexity of seismicity in a novel manner.

  9. Online community detection for large complex networks.

    Directory of Open Access Journals (Sweden)

    Gang Pan

    Full Text Available Complex networks describe a wide range of systems in nature and society. To understand complex networks, it is crucial to investigate their community structure. In this paper, we develop an online community detection algorithm with linear time complexity for large complex networks. Our algorithm processes a network edge by edge in the order that the network is fed to the algorithm. If a new edge is added, it just updates the existing community structure in constant time, and does not need to re-compute the whole network. Therefore, it can efficiently process large networks in real time. Our algorithm optimizes expected modularity instead of modularity at each step to avoid poor performance. The experiments are carried out using 11 public data sets, and are measured by two criteria, modularity and NMI (Normalized Mutual Information. The results show that our algorithm's running time is less than the commonly used Louvain algorithm while it gives competitive performance.

  10. Structural Dissection for Controlling Complex Networks

    CERN Document Server

    Wang, Wen-Xu; Zhao, Chen; Liu, Yang-Yu; Lai, Ying-Cheng

    2015-01-01

    Controlling complex networked systems has been a central goal in different fields and understanding controllability of complex networks has been at the forefront of contemporary science. Despite the recent progress in the development of controllability theories for complex networks, we continue to lack efficient tools to fully understand the effect of network topology and interaction strengths among nodes on controllability. Here we establish a framework to discern the significance of links and nodes for controlling general complex networks in a simple way based on local information. A dissection process is offered by the framework to probe and classify nodes and links completely, giving rise to a criterion for strong structural controllability. Analytical results indicate phase transitions associated with link and node categories, and strong structural controllability. Applying the tools to real networks demonstrate that real technological networks are strong structurally controllable, whereas most of real s...

  11. Multi-agent cooperative intrusion response in mobile adhoc networks

    Institute of Scientific and Technical Information of China (English)

    Yi Ping; Zou Futai; Jiang Xinghao; Li Jianhua

    2007-01-01

    The nature of adhoc networks makes them vulnerable to security attacks. Many security technologies such as intrusion prevention and intrusion detection are passive in response to intrusions in that their countermeasures are only to protect the networks, and there is no automated network-wide counteraction against detected intrusions. the architecture of cooperation intrusion response based multi-agent is propose. The architecture is composed of mobile agents. Monitor agent resides on every node and monitors its neighbor nodes. Decision agent collects information from monitor nodes and detects an intrusion by security policies. When an intruder is found in the architecture, the block agents will get to the neighbor nodes of the intruder and form the mobile firewall to isolate the intruder. In the end, we evaluate it by simulation.

  12. Using Mobile Agents and Overlay Networks to Secure Electrical Netoworks

    Energy Technology Data Exchange (ETDEWEB)

    Dawes, Neal A.; Prosser, Bryan J.; Fulp, Errin W.; McKinnon, Archibald D.

    2013-04-01

    ABSTRACT The use of wandering, mobile agents can provide a robust approach for managing, monitoring, and securing electrical distribution networks. However, the topological structure of electrical networks can affect system performance. For example, if the multi-agent system relies on a regular inspection rate (on average, points of interest are inspected with equal frequency), then locations that are not well connected will on average be inspected less frequently. This paper discusses creation and use of overlay networks that create a virtual grid graph can provide faster coverage and a more uniform average agent sampling rate. Using overlays agents wander a virtual neighborhood consisting of only points of interest that are interconnected in a regular fashion (each point has the same number of neighbors). Experimental results will show that an overlay can often provide better network coverage and a more uniform inspection rate, which can improve cyber security by providing a faster detection of threats

  13. Pinning Synchronization of Switched Complex Dynamical Networks

    Directory of Open Access Journals (Sweden)

    Liming Du

    2015-01-01

    Full Text Available Network topology and node dynamics play a key role in forming synchronization of complex networks. Unfortunately there is no effective synchronization criterion for pinning synchronization of complex dynamical networks with switching topology. In this paper, pinning synchronization of complex dynamical networks with switching topology is studied. Two basic problems are considered: one is pinning synchronization of switched complex networks under arbitrary switching; the other is pinning synchronization of switched complex networks by design of switching when synchronization cannot achieved by using any individual connection topology alone. For the two problems, common Lyapunov function method and single Lyapunov function method are used respectively, some global synchronization criteria are proposed and the designed switching law is given. Finally, simulation results verify the validity of the results.

  14. The Fractal Dimensions of Complex Networks

    Institute of Scientific and Technical Information of China (English)

    GUO Long; CAI Xu

    2009-01-01

    It is shown that many real complex networks share distinctive features,such as the small-world effect and the heterogeneous property of connectivity of vertices,which are different from random networks and regular lattices.Although these features capture the important characteristics of complex networks,their applicability depends on the style of networks.To unravel the universal characteristics many complex networks have in common,we study the fractal dimensions of complex networks using the method introduced by Shanker.We lind that the average 'density' (p(r)) of complex networks follows a better power-law function as a function of distance r with the exponent df,which is defined as the fractal dimension,in some real complex networks.Furthermore,we study the relation between df and the shortcuts Nadd in small-world networks and the size N in regular lattices.Our present work provides a new perspective to understand the dependence of the fractal dimension df on the complex network structure.

  15. Multi-agent Based Modeling of Manufacturing Network

    Institute of Scientific and Technical Information of China (English)

    GUO Yuming; SUN Yanming; ZHENG Shixiong

    2006-01-01

    An intelligent manufacturing system is modeled currently from the viewpoint of manufacturing applications, and the network platform's influence to manufacturing applications is not considered adequately. However any bottleneck in service oriented architecture (SOA) for the manufacturing network can affect the agility of the IT environment. In this paper, to achieve a trade-off between manufacturing resources and network resources, the manufacturing network is modeled with multi-agent, in which two kinds of basic elements, the manufacturing application unit and the network carrier of manufacturing information, are presented. And their main characters are described by colored petri net. The manufacturing application model drives the network platform that inversely provides this application model technology supports. The proposed multi-agent system is demonstrated through an example integration scenario involving production plan, resources management and execution subsystems. And the result suggests that analyzing and designing the system architecture of networked manufacturing should give due attention to the operation system as well as manufacturing applications.

  16. Properties of Bottleneck on Complex Networks

    Institute of Scientific and Technical Information of China (English)

    WANG Chao-Yang; WU Jian-Jun; GAO Zi-You

    2011-01-01

    The traffic bottleneck plays a key role in most of the natural and artificial network.Here we present a simply model for bottleneck dynamical characteristics consideration the reliability on the complex network by taking into account the network topology characteristics and system size.We find that there is a critical rate of flow generation below which the network traffic is free but above which traffic congestion occurs.Also, it is found that random networks have larger critical flow generating rate than scale free ones.Analytical results may be practically useful for designing networks, especially for the urban traffic network.

  17. Modelling, Estimation and Control of Networked Complex Systems

    CERN Document Server

    Chiuso, Alessandro; Frasca, Mattia; Rizzo, Alessandro; Schenato, Luca; Zampieri, Sandro

    2009-01-01

    The paradigm of complexity is pervading both science and engineering, leading to the emergence of novel approaches oriented at the development of a systemic view of the phenomena under study; the definition of powerful tools for modelling, estimation, and control; and the cross-fertilization of different disciplines and approaches. This book is devoted to networked systems which are one of the most promising paradigms of complexity. It is demonstrated that complex, dynamical networks are powerful tools to model, estimate, and control many interesting phenomena, like agent coordination, synchronization, social and economics events, networks of critical infrastructures, resources allocation, information processing, or control over communication networks. Moreover, it is shown how the recent technological advances in wireless communication and decreasing in cost and size of electronic devices are promoting the appearance of large inexpensive interconnected systems, each with computational, sensing and mobile cap...

  18. Discovering universal statistical laws of complex networks

    CERN Document Server

    Cardanobile, Stefano; Deger, Moritz; Rotter, Stefan

    2011-01-01

    Different network models have been suggested for the topology underlying complex interactions in natural systems. These models are aimed at replicating specific statistical features encountered in real-world networks. However, it is rarely considered to which degree the results obtained for one particular network class can be extrapolated to real-world networks. We address this issue by comparing different classical and more recently developed network models with respect to their generalisation power, which we identify with large structural variability and absence of constraints imposed by the construction scheme. After having identified the most variable networks, we address the issue of which constraints are common to all network classes and are thus suitable candidates for being generic statistical laws of complex networks. In fact, we find that generic, not model-related dependencies between different network characteristics do exist. This allows, for instance, to infer global features from local ones usi...

  19. H∞ CONTROL OF NETWORKED MULTI-AGENT SYSTEMS

    Institute of Scientific and Technical Information of China (English)

    Zhongkui LI; Zhisheng DUAN; Lin HUANG

    2009-01-01

    This paper concerns the disturbance rejection problem arising in the coordination control of a group of autonomous agents subject to external disturbances. The agent network is said to possess a desired level of disturbance rejection, if the H∞ norm of its transfer function matrix from the disturbance to the controlled output is satisfactorily small. Undirected graph is used to represent the information flow topology among agents. It is shown that the disturbance rejection problem of an agent network can be solved by analyzing the H∞ control problem of a set of independent systems whose dimensions are equal to that of a single node. An interesting result is that the disturbance rejection ability of the whole agent network coupled via feedback of merely relative measurements between agents will never be better than that of an isolated agent. To improve this, local feedback injections are applied to a small fraction of the agents in the network. Some criteria for possible performance improvement are derived in terms of linear matrix inequalities. Finally, extensions to the case when communication time delays exist are also discussed.

  20. Domain-Partitioned Element Management Systems Employing Mobile Agents for Distributed Network Management

    Directory of Open Access Journals (Sweden)

    Anish Saini

    2014-06-01

    Full Text Available Network management systems based on mobile agents are efficiently a better alternative than typicalclient / server based architectures. Centralized management models like SNMP or CMIP based management models suffer from scalability and flexibility issues which are addressed to great extent by flat bed or static mid-level manager models based on mobile agents, yet the use of mobile agents to distribute and delegate management tasks for above stated agent-based management frameworks like initial flat bed models and static mid-level managers cannot efficiently meet the demands of current networks which are growing in size and complexity. In view of the above mentioned limitations, we proposed a domain partitioned network management model based-on mobile agent & Element Management Systems in order to minimize management data flow to a centralized server. Intelligent agent allocated to specific EMS performs local network management and reports the results to the superior manager and finally the global manager performs global network management using those submitted management results. Experimental results of various scenarios of the proposed model have been presented to support the arguments given in favor of the prototype system based on mobile agents..

  1. Approaching human language with complex networks

    Science.gov (United States)

    Cong, Jin; Liu, Haitao

    2014-12-01

    The interest in modeling and analyzing human language with complex networks is on the rise in recent years and a considerable body of research in this area has already been accumulated. We survey three major lines of linguistic research from the complex network approach: 1) characterization of human language as a multi-level system with complex network analysis; 2) linguistic typological research with the application of linguistic networks and their quantitative measures; and 3) relationships between the system-level complexity of human language (determined by the topology of linguistic networks) and microscopic linguistic (e.g., syntactic) features (as the traditional concern of linguistics). We show that the models and quantitative tools of complex networks, when exploited properly, can constitute an operational methodology for linguistic inquiry, which contributes to the understanding of human language and the development of linguistics. We conclude our review with suggestions for future linguistic research from the complex network approach: 1) relationships between the system-level complexity of human language and microscopic linguistic features; 2) expansion of research scope from the global properties to other levels of granularity of linguistic networks; and 3) combination of linguistic network analysis with other quantitative studies of language (such as quantitative linguistics).

  2. Local Natural Connectivity in Complex Networks

    Institute of Scientific and Technical Information of China (English)

    SHANG Yi-Lun

    2011-01-01

    @@ In network theory, a complex network represents a system whose evolving structure and dynamic behavior contribute to its robustness.The natural connectivity is recently proposed as a spectral measure to characterize the robustness of complex networks.We decompose the natural connectivity of a network as local natural connectivity of its connected components and quantify their contributions to the network robustness.In addition, we compare the natural connectivity of a network with that of an induced subgraph of it based on interlacing theorems.As an application, we derive an inequality for eigenvalues of ErdSs-Renyi random graphs.%In network theory, a complex network represents a system whose evolving structure and dynamic behavior contribute to its robustness. The natural connectivity is recently proposed as a spectral measure to characterize the robustness of complex networks. We decompose the natural connectivity of a network as local naturai connectivity of its connected components and quantify their contributions to the network robustness. In addition, we compare the naturai connectivity of a network with that of an induced subgraph of it based on interlacing theorems. As an application, we derive an inequality for eigenvalues of Erdos-Renyi random graphs.

  3. Pinning-controllability of complex networks

    OpenAIRE

    Sorrentino, Francesco; Di Bernardo, Mario; Garofalo, Franco; Chen, Guanrong

    2007-01-01

    We study the problem of controlling a general complex network towards an assigned synchronous evolution, by means of a pinning control strategy. We define the pinning-controllability of the network in terms of the spectral properties of an extended network topology. The roles of the control and coupling gains as well as of the number of pinned nodes are also discussed.

  4. Modelling the structure of complex networks

    DEFF Research Database (Denmark)

    Herlau, Tue

    networks has been independently studied as mathematical objects in their own right. As such, there has been both an increased demand for statistical methods for complex networks as well as a quickly growing mathematical literature on the subject. In this dissertation we explore aspects of modelling complex....... The next chapters will treat some of the various symmetries, representer theorems and probabilistic structures often deployed in the modelling complex networks, the construction of sampling methods and various network models. The introductory chapters will serve to provide context for the included written...

  5. Synchronization in complex networks with adaptive coupling

    Science.gov (United States)

    Zhang, Rong; Hu, Manfeng; Xu, Zhenyuan

    2007-08-01

    Generally it is very difficult to realized synchronization for some complex networks. In order to synchronize, the coupling coefficient of networks has to be very large, especially when the number of coupled nodes is larger. In this Letter, we consider the problem of synchronization in complex networks with adaptive coupling. A new concept about asymptotic stability is presented, then we proved by using the well-known LaSalle invariance principle, that the state of such a complex network can synchronize an arbitrary assigned state of an isolated node of the network as long as the feedback gain is positive. Unified system is simulated as the nodes of adaptive coupling complex networks with different topologies.

  6. Synchronization in complex networks with adaptive coupling

    Energy Technology Data Exchange (ETDEWEB)

    Zhang Rong [School of Science, Southern Yangtze University, Wuxi 214122 (China); School of Information Engineering, Southern Yangtze University, Wuxi 214122 (China)], E-mail: ronia62@yahoo.com; Hu Manfeng [School of Science, Southern Yangtze University, Wuxi 214122 (China); School of Information Engineering, Southern Yangtze University, Wuxi 214122 (China); Xu Zhenyuan [School of Science, Southern Yangtze University, Wuxi 214122 (China)

    2007-08-20

    Generally it is very difficult to realized synchronization for some complex networks. In order to synchronize, the coupling coefficient of networks has to be very large, especially when the number of coupled nodes is larger. In this Letter, we consider the problem of synchronization in complex networks with adaptive coupling. A new concept about asymptotic stability is presented, then we proved by using the well-known LaSalle invariance principle, that the state of such a complex network can synchronize an arbitrary assigned state of an isolated node of the network as long as the feedback gain is positive. Unified system is simulated as the nodes of adaptive coupling complex networks with different topologies.

  7. Complex Networks of Words in Fables

    CERN Document Server

    Holovatch, Yurij

    2016-01-01

    In this chapter we give an overview of the application of complex network theory to quantify some properties of language. Our study is based on two fables in Ukrainian, Mykyta the Fox and Abu-Kasym's slippers. It consists of two parts: the analysis of frequency-rank distributions of words and the application of complex-network theory. The first part shows that the text sizes are sufficiently large to observe statistical properties. This supports their selection for the analysis of typical properties of the language networks in the second part of the chapter. In describing language as a complex network, while words are usually associated with nodes, there is more variability in the choice of links and different representations result in different networks. Here, we examine a number of such representations of the language network and perform a comparative analysis of their characteristics. Our results suggest that, irrespective of link representation, the Ukrainian language network used in the selected fables i...

  8. Pinning impulsive control algorithms for complex network.

    Science.gov (United States)

    Sun, Wen; Lü, Jinhu; Chen, Shihua; Yu, Xinghuo

    2014-03-01

    In this paper, we further investigate the synchronization of complex dynamical network via pinning control in which a selection of nodes are controlled at discrete times. Different from most existing work, the pinning control algorithms utilize only the impulsive signals at discrete time instants, which may greatly improve the communication channel efficiency and reduce control cost. Two classes of algorithms are designed, one for strongly connected complex network and another for non-strongly connected complex network. It is suggested that in the strongly connected network with suitable coupling strength, a single controller at any one of the network's nodes can always pin the network to its homogeneous solution. In the non-strongly connected case, the location and minimum number of nodes needed to pin the network are determined by the Frobenius normal form of the coupling matrix. In addition, the coupling matrix is not necessarily symmetric or irreducible. Illustrative examples are then given to validate the proposed pinning impulsive control algorithms.

  9. Agent-based model of information spread in social networks

    CERN Document Server

    Lande, D V; Berezin, B O

    2016-01-01

    We propose evolution rules of the multiagent network and determine statistical patterns in life cycle of agents - information messages. The main discussed statistical pattern is connected with the number of likes and reposts for a message. This distribution corresponds to Weibull distribution according to modeling results. We examine proposed model using the data from Twitter, an online social networking service.

  10. Challenges of Detecting Bioterrorism Agents in Complex Matrices

    Science.gov (United States)

    Hartmann, Erica M.; Halden, Rolf U.

    This chapter offers an overview of the shift from the use of mass ­spectrometry for studying purified bioterrorism agents to the development of methods for rapid detection thereof in environmental and clinical samples. We discuss the difficulties of working with such complex matrices and present methods for quickly and effectively reducing complexity through sample preparation. Finally, we examine a success story wherein the common pathogen and potential bioterrorism agent norovirus is detected at clinically relevant levels in human stool.

  11. Controlling Congestion on Complex Networks

    CERN Document Server

    Buzna, Lubos

    2016-01-01

    From the Internet to road networks and the power grid, modern life depends on controlling flows on critical infrastructure networks that often operate in a congested state. Yet, we have a limited understanding of the relative performance of the control mechanisms available to manage congestion and of the interplay between network topology, path layout and congestion control algorithms. Here, we consider two flow algorithms (max-flow and uniform-flow), and two more realistic congestion control schemes (max-min fairness and proportional fairness). We analyse how the algorithms and network topology affect throughput, fairness and the location of bottleneck edges. Our results show that on large random networks a network operator can implement the trade-off (proportional fairness) instead of the fair allocation (max-min fairness) with little sacrifice in throughput. We illustrate how the previously studied uniform-flow approach leaves networks severely underutilised in comparison with congestion control algorithms...

  12. Effective Augmentation of Complex Networks

    Science.gov (United States)

    Wang, Jinjian; Yu, Xinghuo; Stone, Lewi

    2016-05-01

    Networks science plays an enormous role in many aspects of modern society from distributing electrical power across nations to spreading information and social networking amongst global populations. While modern networks constantly change in size, few studies have sought methods for the difficult task of optimising this growth. Here we study theoretical requirements for augmenting networks by adding source or sink nodes, without requiring additional driver-nodes to accommodate the change i.e., conserving structural controllability. Our “effective augmentation” algorithm takes advantage of clusters intrinsic to the network topology, and permits rapidly and efficient augmentation of a large number of nodes in one time-step. “Effective augmentation” is shown to work successfully on a wide range of model and real networks. The method has numerous applications (e.g. study of biological, social, power and technological networks) and potentially of significant practical and economic value.

  13. Pattern-oriented modeling of agent-based complex systems: Lessons from ecology

    Science.gov (United States)

    Grimm, Volker; Revilla, Eloy; Berger, Uta; Jeltsch, Florian; Mooij, Wolf M.; Railsback, Steven F.; Thulke, Hans-Hermann; Weiner, Jacob; Wiegand, Thorsten; DeAngelis, Donald L.

    2005-01-01

    Agent-based complex systems are dynamic networks of many interacting agents; examples include ecosystems, financial markets, and cities. The search for general principles underlying the internal organization of such systems often uses bottom-up simulation models such as cellular automata and agent-based models. No general framework for designing, testing, and analyzing bottom-up models has yet been established, but recent advances in ecological modeling have come together in a general strategy we call pattern-oriented modeling. This strategy provides a unifying framework for decoding the internal organization of agent-based complex systems and may lead toward unifying algorithmic theories of the relation between adaptive behavior and system complexity.

  14. Pattern-oriented modeling of agent-based complex systems: lessons from ecology.

    Science.gov (United States)

    Grimm, Volker; Revilla, Eloy; Berger, Uta; Jeltsch, Florian; Mooij, Wolf M; Railsback, Steven F; Thulke, Hans-Hermann; Weiner, Jacob; Wiegand, Thorsten; DeAngelis, Donald L

    2005-11-11

    Agent-based complex systems are dynamic networks of many interacting agents; examples include ecosystems, financial markets, and cities. The search for general principles underlying the internal organization of such systems often uses bottom-up simulation models such as cellular automata and agent-based models. No general framework for designing, testing, and analyzing bottom-up models has yet been established, but recent advances in ecological modeling have come together in a general strategy we call pattern-oriented modeling. This strategy provides a unifying framework for decoding the internal organization of agent-based complex systems and may lead toward unifying algorithmic theories of the relation between adaptive behavior and system complexity.

  15. Contagion on complex networks with persuasion

    Science.gov (United States)

    Huang, Wei-Min; Zhang, Li-Jie; Xu, Xin-Jian; Fu, Xinchu

    2016-03-01

    The threshold model has been widely adopted as a classic model for studying contagion processes on social networks. We consider asymmetric individual interactions in social networks and introduce a persuasion mechanism into the threshold model. Specifically, we study a combination of adoption and persuasion in cascading processes on complex networks. It is found that with the introduction of the persuasion mechanism, the system may become more vulnerable to global cascades, and the effects of persuasion tend to be more significant in heterogeneous networks than those in homogeneous networks: a comparison between heterogeneous and homogeneous networks shows that under weak persuasion, heterogeneous networks tend to be more robust against random shocks than homogeneous networks; whereas under strong persuasion, homogeneous networks are more stable. Finally, we study the effects of adoption and persuasion threshold heterogeneity on systemic stability. Though both heterogeneities give rise to global cascades, the adoption heterogeneity has an overwhelmingly stronger impact than the persuasion heterogeneity when the network connectivity is sufficiently dense.

  16. Medicinal organometallic chemistry: designing metal arene complexes as anticancer agents.

    Science.gov (United States)

    Peacock, Anna F A; Sadler, Peter J

    2008-11-13

    The field of medicinal inorganic chemistry is rapidly advancing. In particular organometallic complexes have much potential as therapeutic and diagnostic agents. The carbon-bound and other ligands allow the thermodynamic and kinetic reactivity of the metal ion to be controlled and also provide a scaffold for functionalization. The establishment of structure-activity relationships and elucidation of the speciation of complexes under conditions relevant to drug testing and formulation are crucial for the further development of promising medicinal applications of organometallic complexes. Specific examples involving the design of ruthenium and osmium arene complexes as anticancer agents are discussed.

  17. Securing Information with Complex Optical Encryption Networks

    Science.gov (United States)

    2015-08-11

    Encryption Networks 5a. CONTRACT NUMBER FA2386-13-1-4106 5b. GRANT NUMBER Grant AOARD-134106 5c. PROGRAM ELEMENT NUMBER 61102F 6. AUTHOR(S...configure complex optical encryption networks for securing information. The goal is to study/develop the architectures for a number of complex optical... encryption networks, and to provide effective and reliable solutions for information security. 15. SUBJECT TERMS Optical Encryption

  18. FIPA agent based network distributed control system

    CERN Document Server

    Gyurjyan, V; Heyes, G; Jastrzembski, E; Timmer, C; Wolin, E

    2003-01-01

    A control system with the capabilities to combine heteregeneous control systems or processes into a uniform homogeneous environment is discussed. This dynamically extensible system is an example of the software system at the agent level of abstraction. This level of abstraction considers agents as atomic entities that communicate to implement the functionality of the control system. Agents engineering aspects are addressed by adopting the domain independent software standard, formulated by FIPA. Jade core Java classes are used as a FIPA specification implementation. A special, lightweight, XML RDFS based, control oriented, ontology markup language is developed to standardize the description of the arbitrary control system data processor. Control processes, described in this language, are integrated into the global system at runtime, without actual programming. Fault tolerance and recovery issues are also addressed.

  19. FIPA agent based network distributed control system

    Energy Technology Data Exchange (ETDEWEB)

    D. Abbott; V. Gyurjyan; G. Heyes; E. Jastrzembski; C. Timmer; E. Wolin

    2003-03-01

    A control system with the capabilities to combine heterogeneous control systems or processes into a uniform homogeneous environment is discussed. This dynamically extensible system is an example of the software system at the agent level of abstraction. This level of abstraction considers agents as atomic entities that communicate to implement the functionality of the control system. Agents' engineering aspects are addressed by adopting the domain independent software standard, formulated by FIPA. Jade core Java classes are used as a FIPA specification implementation. A special, lightweight, XML RDFS based, control oriented, ontology markup language is developed to standardize the description of the arbitrary control system data processor. Control processes, described in this language, are integrated into the global system at runtime, without actual programming. Fault tolerance and recovery issues are also addressed.

  20. Pinning control of complex networked systems synchronization, consensus and flocking of networked systems via pinning

    CERN Document Server

    Su, Housheng

    2013-01-01

    Synchronization, consensus and flocking are ubiquitous requirements in networked systems. Pinning Control of Complex Networked Systems investigates these requirements by using the pinning control strategy, which aims to control the whole dynamical network with huge numbers of nodes by imposing controllers for only a fraction of the nodes. As the direct control of every node in a dynamical network with huge numbers of nodes might be impossible or unnecessary, it’s then very important to use the pinning control strategy for the synchronization of complex dynamical networks. The research on pinning control strategy in consensus and flocking of multi-agent systems can not only help us to better understand the mechanisms of natural collective phenomena, but also benefit applications in mobile sensor/robot networks. This book offers a valuable resource for researchers and engineers working in the fields of control theory and control engineering.   Housheng Su is an Associate Professor at the Department of Contro...

  1. Complex Network Analysis of Brazilian Power Grid

    CERN Document Server

    Martins, Gabriela C; Ribeiro, Fabiano L; Forgerini, Fabricio L

    2016-01-01

    Power Grids and other delivery networks has been attracted some attention by the network literature last decades. Despite the Power Grids dynamics has been controlled by computer systems and human operators, the static features of this type of network can be studied and analyzed. The topology of the Brazilian Power Grid (BPG) was studied in this work. We obtained the spatial structure of the BPG from the ONS (electric systems national operator), consisting of high-voltage transmission lines, generating stations and substations. The local low-voltage substations and local power delivery as well the dynamic features of the network were neglected. We analyze the complex network of the BPG and identify the main topological information, such as the mean degree, the degree distribution, the network size and the clustering coefficient to caracterize the complex network. We also detected the critical locations on the network and, therefore, the more susceptible points to lead to a cascading failure and even to a blac...

  2. Visualizing global properties of large complex networks.

    Directory of Open Access Journals (Sweden)

    Weijiang Li

    Full Text Available For complex biological networks, graphical representations are highly desired for understanding some design principles, but few drawing methods are available that capture topological features of a large and highly heterogeneous network, such as a protein interaction network. Here we propose the circular perspective drawing (CPD method to visualize global structures of large complex networks. The presented CPD combines the quasi-continuous search (QCS analogous to the steepest descent method with a random node swapping strategy for an enhanced calculation speed. The CPD depicts a network in an aesthetic manner by showing connection patterns between different parts of the network instead of detailed links between nodes. Global structural features of networks exhibited by CPD provide clues toward a comprehensive understanding of the network organizations.Software is freely available at http://www.cadlive.jp.

  3. 7th Workshop on Complex Networks

    CERN Document Server

    Gonçalves, Bruno; Menezes, Ronaldo; Sinatra, Roberta

    2016-01-01

    The last decades have seen the emergence of Complex Networks as the language with which a wide range of complex phenomena in fields as diverse as Physics, Computer Science, and Medicine (to name just a few) can be properly described and understood. This book provides a view of the state of the art in this dynamic field and covers topics ranging from network controllability, social structure, online behavior, recommendation systems, and network structure. This book includes the peer-reviewed list of works presented at the 7th Workshop on Complex Networks CompleNet 2016 which was hosted by the Université de Bourgogne, France, from March 23-25, 2016. The 28 carefully reviewed and selected contributions in this book address many topics related to complex networks and have been organized in seven major groups: (1) Theory of Complex Networks, (2) Multilayer networks, (3) Controllability of networks, (4) Algorithms for networks, (5) Community detection, (6) Dynamics and spreading phenomena on networks, (7) Applicat...

  4. Understanding the Complexity of Terrorist Networks

    CERN Document Server

    Fellman, Philip V

    2009-01-01

    Complexity science affords a number of novel tools for examining terrorism, particularly network analysis and NK-Boolean fitness landscapes. The following paper explores various aspects of terrorist networks which can be illuminated through applications of non-linear dynamical systems modeling to terrorist network structures. Of particular interest are some of the emergent properties of terrorist networks as typified by the 9-11 hijackers network, properties of centrality, hierarchy and distance, as well as ways in which attempts to disrupt the transmission of information through terrorist networks may be expected to produce greater or lesser levels of fitness in those organizations.

  5. Trusted intermediating agents in electronic trade networks

    NARCIS (Netherlands)

    T.B. Klos (Tomas); F. Alkemade (Floortje)

    2005-01-01

    htmlabstract Electronic commerce and trading of information goods significantly impact the role of intermediaries: consumers can bypass intermediating agents by forming direct links to producers. One reason that traditional intermediaries can still make a profit, is that they have more knowledge of

  6. Trusted intermediating agents in electronic trade networks

    NARCIS (Netherlands)

    Klos, T.B.; Alkemade, F.

    2005-01-01

    Electronic commerce and trading of information goods significantly impact the role of intermediaries: consumers can bypass intermediating agents by forming direct links to producers. One reason that traditional intermediaries can still make a profit, is that they have more knowledge of the market, s

  7. AN INTELLIGENT MOBILE-AGENT BASED SCALABLE NETWORK MANAGEMENT ARCHITECTURE FOR LARGE-SCALE ENTERPRISE SYSTEM

    Directory of Open Access Journals (Sweden)

    A.K. Sharma

    2012-02-01

    Full Text Available Several Mobile Agent based distributed network management models have been proposed in recent times toaddress the scalability and flexibility problems of centralized (SNMP or CMIP management modelsmodels. Though the use of Mobile Agents to distribute and delegate management tasks comes handy indealing with the previously stated issues, many of the agent-based management frameworks like initial flatbed models and static mid-level managers employing mobile agents models cannot efficiently meet thedemands of current networks which are growing in size and complexity. Moreover, varied technologies,such as SONET, ATM, Ethernet, DWDM etc., present at different layers of the Access, Metro and Core(long haul sections of the network, have contributed to the complexity in terms of their own framing andprotocol structures. Thus, controlling and managing the traffic in these networks is a challenging task. Thispaper presents an intelligent scalable hierarchical agent based model for the management of large-scalecomplex networks to address aforesaid issues. The cost estimation, carried out with a view to compute theoverall management cost in terms of management data overhead, is being presented. The results obtainedthereafter establish the usefulness of the presented architecture as compare to centralized and flat bedagent based models.

  8. Ecological Complexity and the Success of Fungal Biological Control Agents

    Directory of Open Access Journals (Sweden)

    Guy R. Knudsen

    2014-01-01

    Full Text Available Fungal biological control agents against plant pathogens, especially those in soil, operate within physically, biologically, and spatially complex systems by means of a variety of trophic and nontrophic interspecific interactions. However, the biocontrol agents themselves are also subject to the same types of interactions, which may reduce or in some cases enhance their efficacy against target plant pathogens. Characterization of these ecologically complex systems is challenging, but a number of tools are available to help unravel this complexity. Several of these tools are described here, including the use of molecular biology to generate biocontrol agents with useful marker genes and then to quantify these agents in natural systems, epifluorescence and confocal laser scanning microscopy to observe their presence and activity in situ, and spatial statistics and computer simulation modeling to evaluate and predict these activities in heterogeneous soil habitats.

  9. An Agent Based Software Approach towards Building Complex Systems

    Directory of Open Access Journals (Sweden)

    Latika Kharb

    2015-08-01

    Full Text Available Agent-oriented techniques represent an exciting new means of analyzing, designing and building complex software systems. They have the potential to significantly improve current practice in software engineering and to extend the range of applications that can feasibly be tackled. Yet, to date, there have been few serious attempts to cast agent systems as a software engineering paradigm. This paper seeks to rectify this omission. Specifically, points to be argued include:firstly, the conceptual apparatus of agent-oriented systems is well-suited to building software solutions for complex systems and secondly, agent-oriented approaches represent a genuine advance over the current state of the art for engineering complex systems. Following on from this view, the major issues raised by adopting an agentoriented approach to software engineering are highlighted and discussed in this paper.

  10. Constrained target controllability of complex networks

    Science.gov (United States)

    Guo, Wei-Feng; Zhang, Shao-Wu; Wei, Ze-Gang; Zeng, Tao; Liu, Fei; Zhang, Jingsong; Wu, Fang-Xiang; Chen, Luonan

    2017-06-01

    It is of great theoretical interest and practical significance to study how to control a system by applying perturbations to only a few driver nodes. Recently, a hot topic of modern network researches is how to determine driver nodes that allow the control of an entire network. However, in practice, to control a complex network, especially a biological network, one may know not only the set of nodes which need to be controlled (i.e. target nodes), but also the set of nodes to which only control signals can be applied (i.e. constrained control nodes). Compared to the general concept of controllability, we introduce the concept of constrained target controllability (CTC) of complex networks, which concerns the ability to drive any state of target nodes to their desirable state by applying control signals to the driver nodes from the set of constrained control nodes. To efficiently investigate the CTC of complex networks, we further design a novel graph-theoretic algorithm called CTCA to estimate the ability of a given network to control targets by choosing driver nodes from the set of constrained control nodes. We extensively evaluate the CTC of numerous real complex networks. The results indicate that biological networks with a higher average degree are easier to control than biological networks with a lower average degree, while electronic networks with a lower average degree are easier to control than web networks with a higher average degree. We also show that our CTCA can more efficiently produce driver nodes for target-controlling the networks than existing state-of-the-art methods. Moreover, we use our CTCA to analyze two expert-curated bio-molecular networks and compare to other state-of-the-art methods. The results illustrate that our CTCA can efficiently identify proven drug targets and new potentials, according to the constrained controllability of those biological networks.

  11. Evolution Properties of Modules in Complex Networks

    Institute of Scientific and Technical Information of China (English)

    LI Ke-Ping; GAO Zi-You

    2008-01-01

    In complex networks, network modules play a center role, which carry out a key function. In this paper, we introduce the spatial correlation function to describe the relationships among the network modules. Our focus is to investigate how the network modules evolve, and what the evolution properties of the modules are. In order to test the proposed method, as the examples, we use our method to analyze and discuss the ER random network and scale-free network. Rigorous analysis of the existing data shows that the introduced correlation function is suitable for describing the evolution properties of network modules. Remarkably, the numerical simulations indicate that the ER random network and scale-free network have different evolution properties.

  12. Contagion on complex networks with persuasion

    CERN Document Server

    Huang, Wei-Min; Xu, Xin-Jian; Fu, Xinchu

    2016-01-01

    The threshold model has been widely adopted as a classic model for studying contagion processes on social networks. We consider asymmetric individual interactions in social networks and introduce a persuasion mechanism into the threshold model. Specifically, we study a combination of adoption and persuasion in cascading processes on complex networks. It is found that with the introduction of the persuasion mechanism, the system may become more vulnerable to global cascades, and the effects of persuasion tend to be more significant in heterogeneous networks than those in homogeneous networks: a comparison between heterogeneous and homogeneous networks shows that under weak persuasion, heterogeneous networks tend to be more robust against random shocks than homogeneous networks; whereas under strong persuasion, homogeneous networks are more stable. Finally, we study the effects of adoption and persuasion threshold heterogeneity on systemic stability. Though both heterogeneities give rise to global cascades, the...

  13. Revealing the Hidden Language of Complex Networks

    Science.gov (United States)

    Yaveroğlu, Ömer Nebil; Malod-Dognin, Noël; Davis, Darren; Levnajic, Zoran; Janjic, Vuk; Karapandza, Rasa; Stojmirovic, Aleksandar; Pržulj, Nataša

    2014-04-01

    Sophisticated methods for analysing complex networks promise to be of great benefit to almost all scientific disciplines, yet they elude us. In this work, we make fundamental methodological advances to rectify this. We discover that the interaction between a small number of roles, played by nodes in a network, can characterize a network's structure and also provide a clear real-world interpretation. Given this insight, we develop a framework for analysing and comparing networks, which outperforms all existing ones. We demonstrate its strength by uncovering novel relationships between seemingly unrelated networks, such as Facebook, metabolic, and protein structure networks. We also use it to track the dynamics of the world trade network, showing that a country's role of a broker between non-trading countries indicates economic prosperity, whereas peripheral roles are associated with poverty. This result, though intuitive, has escaped all existing frameworks. Finally, our approach translates network topology into everyday language, bringing network analysis closer to domain scientists.

  14. NOVEL MULTI-LEVEL OPTIMIZATION METHOD FOR CHEMICAL COMPLEX USING INTELLIGENT AGENT

    Institute of Scientific and Technical Information of China (English)

    Xiaojun LI; Huanjun YU; Shangxu HU

    2003-01-01

    Multi-level optimization of complex chemical complex was comprehensively analyzed, including the optimization of management plan, production scheme, operating conditions, etc. The software framework of multi-level optimization of chemical complex was worked out. Basing upon the frame of multi-level optimization, the intelligent agent technique was adopted to search for global optimum. The organization, function, design and the implementation of a series of intelligent agents were discussed. According to the strategy that to spend most computing time in optimization solving and much less time in exchanging information regarding the tasks and results of optimization through network, the communication mechanism and cooperation rules for Multi-Agent System for hierarchically optimizing chemical complex was proposed.

  15. CORRELATION PROFILES AND MOTIFS IN COMPLEX NETWORKS.

    Energy Technology Data Exchange (ETDEWEB)

    MASLOV,S.SNEPPEN,K.ALON,U.

    2004-01-16

    Networks have recently emerged as a unifying theme in complex systems research [1]. It is in fact no coincidence that networks and complexity are so heavily intertwined. Any future definition of a complex system should reflect the fact that such systems consist of many mutually interacting components. These components are far from being identical as say electrons in systems studied by condensed matter physics. In a truly complex system each of them has a unique identity allowing one to separate it from the others. The very first question one may ask about such a system is which other components a given component interacts with? This information system wide can be visualized as a graph, whose nodes correspond to individual components of the complex system in question and edges to their mutual interactions. Such a network can be thought of as a backbone of the complex system. Of course, system's dynamics depends not only on the topology of an underlying network but also on the exact form of interaction of components with each other, which can be very different in various complex systems. However, the underlying network may contain clues about the basic design principles and/or evolutionary history of the complex system in question. The goal of this article is to provide readers with a set of useful tools that would help to decide which features of a complex network are there by pure chance alone, and which of them were possibly designed or evolved to their present state.

  16. Synchronization of impulsively coupled complex networks

    Institute of Scientific and Technical Information of China (English)

    Sun Wen; Chen Zhong; Chen Shi-Hua

    2012-01-01

    We investigate the synchronization of complex networks,which are impulsively coupled only at discrete instants.Based on the comparison theory of impulsive differential systems,a distributed impulsive control scheme is proposed for complex dynamical networks to achieve synchronization.The proposed scheme not only takes into account the influence of all nodes to network synchronization,which depends on the weight of each node in the network,but also provides us with a flexible method to select the synchronized state of the network.In addition,it is unnecessary for the impulsive coupling matrix to be symmetrical.Finally,the proposed control scheme is applied to a chaotic Lorenz network and Chua's circuit network.Numerical simulations are used to illustrate the validity of this control scheme.

  17. Percolation of localized attack on complex networks

    CERN Document Server

    Shao, Shuai; Stanley, H Eugene; Havlin, Shlomo

    2014-01-01

    The robustness of complex networks against node failure and malicious attack has been of interest for decades, while most of the research has focused on random attack or hub-targeted attack. In many real-world scenarios, however, attacks are neither random nor hub-targeted, but localized, where a group of neighboring nodes in a network are attacked and fail. In this paper we develop a percolation framework to analytically and numerically study the robustness of complex networks against such localized attack. In particular, we investigate this robustness in Erd\\H{o}s-R\\'{e}nyi networks, random-regular networks, and scale-free networks. Our results provide insight into how to better protect networks, enhance cybersecurity, and facilitate the design of more robust infrastructures.

  18. A Novel Agent Based Approach for Controlling Network Storms

    CERN Document Server

    Nair, Dr T R Gopalakrishnan; M, Vaidehi

    2011-01-01

    One of the fundamental data transmission mechanisms in Ethernet LAN is broadcasting. Flooding is a direct broadcasting technique used in these networks. A significant drawback of this method is that it can lead to broadcast storms. This phenomenon is more common in multivendor switch environment. Broadcast storms usually results in dissension, collision and redundancy leading to degradation of the network performance. Most of the storms appear without much warning and it affects the efficiency of network even in situations when the network is expected to work most efficiently. There are several characteristic patterns by which storm can appear in a LAN, like rate monotonic repetition, transient appearances with different types of growth properties and decay profiles. In this paper we discuss the storm build up pattern in an industry and present various reasons for storm in LAN. We have identified a strategy for controlling network storms, using multiple static agents. These agents inhibit storm packet regener...

  19. Controlling complex networks with conformity behavior

    Science.gov (United States)

    Wang, Xu-Wen; Nie, Sen; Wang, Wen-Xu; Wang, Bing-Hong

    2015-09-01

    Controlling complex networks accompanied by common conformity behavior is a fundamental problem in social and physical science. Conformity behavior that individuals tend to follow the majority in their neighborhood is common in human society and animal communities. Despite recent progress in understanding controllability of complex networks, the existent controllability theories cannot be directly applied to networks associated with conformity. Here we propose a simple model to incorporate conformity-based decision making into the evolution of a network system, which allows us to employ the exact controllability theory to explore the controllability of such systems. We offer rigorous theoretical results of controllability for representative regular networks. We also explore real networks in different fields and some typical model networks, finding some interesting results that are different from the predictions of structural and exact controllability theory in the absence of conformity. We finally present an example of steering a real social network to some target states to further validate our controllability theory and tools. Our work offers a more realistic understanding of network controllability with conformity behavior and can have potential applications in networked evolutionary games, opinion dynamics and many other complex networked systems.

  20. Project SAFE. Complexing agents in SFR

    Energy Technology Data Exchange (ETDEWEB)

    Fanger, G.; Skagius, K.; Wiborgh, M. [Kemakta Konsult AB, Stockholm (Sweden)

    2001-01-01

    Low- and intermediate level radioactive waste, produced at Swedish nuclear power plants, will be deposited in an underground repository, SFR. Different substances in the waste or in degradation products emanating from the waste, and chemicals added during the building of cementitious barriers in the repository, may exhibit complexing properties. The complexation of radionuclides with such ligands may increase the mobility of the deposited radionuclides as sorption on the cement phases is decreased and solubility increased. This could lead to an increased leaching of the radionuclides from the repository to the geosphere and biosphere. To be able to evaluate the implications for the function and long-term safety of the repository a study has been performed on complexants in SFR. The study is a part of project SAFE (Safety Assessment of Final Repository for operational Radioactive Waste) at the Swedish Nuclear Fuel and Waste Management Co, SKB. Concentrations of complexants were calculated in different waste types in the repository and compared to critical levels above which radionuclide sorption may be affected. The analysis is based on recent research presented in international and national literature sources. The waste in SFR that may act or give rise to substances with complexing properties mainly consists of cellulose materials, including cement additives used in waste conditioning and backfill grout. The radioactive waste also contains chemicals mainly used in decontamination processes at the nuclear power plants, e.g. EDTA, NTA, gluconate, citric acid and oxalic acid. The calculations performed in this report show that the presence of complexants in SFR may lead to a sorption reduction for some radionuclides in certain waste types. This may have to be considered when performing calculations of the radionuclide transport. Concentration calculations of isosaccharinic acid (ISA), using a degradation yield of 0.1 mole/kg cellulose (2%), showed that the limit above

  1. Complex groundwater flow systems as traveling agent models

    CERN Document Server

    López-Corona, Oliver; Escolero, Oscar; González, Tomás; Morales-Casique, Eric

    2014-01-01

    Analyzing field data from pumping tests, we show that as with many other natural phenomena, groundwater flow exhibits a complex dynamics described by 1/f power spectrum. This result is theoretically studied within an agent perspective. Using a traveling agent model, we prove that this statistical behavior emerges when the medium is complex. Some heuristic reasoning is provided to justify both spatial and dynamic complexity, as the result of the superposition of an infinite number of stochastic processes. Even more, we show that this implies that non-Kolmogorovian probability is needed for its study, and provide a set of new partial differential equations for groundwater flow.

  2. Managing Complex Network Operation with Predictive Analytics

    Energy Technology Data Exchange (ETDEWEB)

    Huang, Zhenyu; Wong, Pak C.; Mackey, Patrick S.; Chen, Yousu; Ma, Jian; Schneider, Kevin P.; Greitzer, Frank L.

    2008-03-26

    Complex networks play an important role in modern societies. Their failures, such as power grid blackouts, would lead to significant disruption of people’s life, industry and commercial activities, and result in massive economic losses. Operation of these complex networks is an extremely challenging task due to their complex structures, wide geographical coverage, complex data/information technology systems, and highly dynamic and nonlinear behaviors. None of the complex network operation is fully automated; human-in-the-loop operation is critical. Given the complexity involved, there may be thousands of possible topological configurations at any given time. During an emergency, it is not uncommon for human operators to examine thousands of possible configurations in near real-time to choose the best option and operate the network effectively. In today’s practice, network operation is largely based on experience with very limited real-time decision support, resulting in inadequate management of complex predictions and inability to anticipate, recognize, and respond to situations caused by human errors, natural disasters, and cyber attacks. A systematic approach is needed to manage the complex operation paradigms and choose the best option in a near-real-time manner. This paper applies predictive analytics techniques to establish a decision support system for complex network operation management and help operators to predict potential network failures and adapt the network to adverse situations. The resultant decision support system enables continuous monitoring of network performance and turns large amounts of data into actionable information. Examples with actual power grid data are presented to demonstrate the capability of this proposed decision support system.

  3. New Trends in Agent-Based Complex Automated Negotiations

    CERN Document Server

    Zhang, Minjie; Robu, Valentin; Fatima, Shaheen; Matsuo, Tokuro

    2012-01-01

    Complex Automated Negotiations represent an important, emerging area in the field of Autonomous Agents and Multi-Agent Systems. Automated negotiations can be complex, since there are a lot of factors that characterize such negotiations. These factors include the number of issues, dependencies between these issues,  representation of utilities, the negotiation protocol, the number of parties in the negotiation (bilateral or multi-party), time constraints, etc. Software agents can support automation or simulation of such complex negotiations on the behalf of their owners, and can provide them with efficient bargaining strategies. To realize such a complex automated negotiation, we have to incorporate advanced Artificial Intelligence technologies includes search, CSP, graphical utility models, Bayes nets, auctions, utility graphs, predicting and learning methods. Applications could include e-commerce tools, decision-making support tools, negotiation support tools, collaboration tools, etc. This book aims to pro...

  4. Optimization of spatial complex networks

    Science.gov (United States)

    Guillier, S.; Muñoz, V.; Rogan, J.; Zarama, R.; Valdivia, J. A.

    2017-02-01

    First, we estimate the connectivity properties of a predefined (fixed node locations) spatial network which optimizes a connectivity functional that balances construction and transportation costs. In this case we obtain a Gaussian distribution for the connectivity. However, when we consider these spatial networks in a growing process, we obtain a power law distribution for the connectivity. If the transportation costs in the functional involve the shortest geometrical path, we obtain a scaling exponent γ = 2.5. However, if the transportation costs in the functional involve just the shortest path, we obtain γ = 2.2. Both cases may be useful to analyze in some real networks.

  5. Towards an Information Theory of Complex Networks

    CERN Document Server

    Dehmer, Matthias; Mehler, Alexander

    2011-01-01

    For over a decade, complex networks have steadily grown as an important tool across a broad array of academic disciplines, with applications ranging from physics to social media. A tightly organized collection of carefully-selected papers on the subject, Towards an Information Theory of Complex Networks: Statistical Methods and Applications presents theoretical and practical results about information-theoretic and statistical models of complex networks in the natural sciences and humanities. The book's major goal is to advocate and promote a combination of graph-theoretic, information-theoreti

  6. Note on the Complex Networks and Epidemiology Part I: Complex Networks

    CERN Document Server

    Kim, James

    2013-01-01

    Complex networks describe a wide range of systems in nature and society. Frequently cited examples include Internet, WWW, a network of chemicals linked by chemical reactions, social relationship networks, citation networks, etc. The research of complex networks has attracted many scientists' attention. Physicists have shown that these networks exhibit some surprising characters, such as high clustering coefficient, small diameter, and the absence of the thresholds of percolation. Scientists in mathematical epidemiology discovered that the threshold of infectious disease disappears on contact networks that following Scale-Free distribution. Researchers in economics and public health also find that the imitation behavior could lead to cluster phenomena of vaccination and un-vaccination. In this note, we will review the basic concepts of complex networks; Basic epidemic models; the development of complex networks and epidemiology.

  7. Controlling centrality in complex networks

    Science.gov (United States)

    Nicosia, V.; Criado, R.; Romance, M.; Russo, G.; Latora, V.

    2012-01-01

    Spectral centrality measures allow to identify influential individuals in social groups, to rank Web pages by popularity, and even to determine the impact of scientific researches. The centrality score of a node within a network crucially depends on the entire pattern of connections, so that the usual approach is to compute node centralities once the network structure is assigned. We face here with the inverse problem, that is, we study how to modify the centrality scores of the nodes by acting on the structure of a given network. We show that there exist particular subsets of nodes, called controlling sets, which can assign any prescribed set of centrality values to all the nodes of a graph, by cooperatively tuning the weights of their out-going links. We found that many large networks from the real world have surprisingly small controlling sets, containing even less than 5 – 10% of the nodes. PMID:22355732

  8. Statistically validated networks in bipartite complex systems.

    Directory of Open Access Journals (Sweden)

    Michele Tumminello

    Full Text Available Many complex systems present an intrinsic bipartite structure where elements of one set link to elements of the second set. In these complex systems, such as the system of actors and movies, elements of one set are qualitatively different than elements of the other set. The properties of these complex systems are typically investigated by constructing and analyzing a projected network on one of the two sets (for example the actor network or the movie network. Complex systems are often very heterogeneous in the number of relationships that the elements of one set establish with the elements of the other set, and this heterogeneity makes it very difficult to discriminate links of the projected network that are just reflecting system's heterogeneity from links relevant to unveil the properties of the system. Here we introduce an unsupervised method to statistically validate each link of a projected network against a null hypothesis that takes into account system heterogeneity. We apply the method to a biological, an economic and a social complex system. The method we propose is able to detect network structures which are very informative about the organization and specialization of the investigated systems, and identifies those relationships between elements of the projected network that cannot be explained simply by system heterogeneity. We also show that our method applies to bipartite systems in which different relationships might have different qualitative nature, generating statistically validated networks in which such difference is preserved.

  9. Link Prediction in Complex Networks: A Survey

    CERN Document Server

    Lu, Linyuan

    2010-01-01

    Link prediction in complex networks has attracted increasing attention from both physical and computer science communities. The algorithms can be used to extract missing information, identify spurious interactions, evaluate network evolving mechanisms, and so on. This article summaries recent progress about link prediction algorithms, emphasizing on the contributions from physical perspectives and approaches, such as the random-walk-based methods and the maximum likelihood methods. We also introduce three typical applications: reconstruction of networks, evaluation of network evolving mechanism and classification of partially labelled networks. Finally, we introduce some applications and outline future challenges of link prediction algorithms.

  10. Universality in complex networks: random matrix analysis.

    Science.gov (United States)

    Bandyopadhyay, Jayendra N; Jalan, Sarika

    2007-08-01

    We apply random matrix theory to complex networks. We show that nearest neighbor spacing distribution of the eigenvalues of the adjacency matrices of various model networks, namely scale-free, small-world, and random networks follow universal Gaussian orthogonal ensemble statistics of random matrix theory. Second, we show an analogy between the onset of small-world behavior, quantified by the structural properties of networks, and the transition from Poisson to Gaussian orthogonal ensemble statistics, quantified by Brody parameter characterizing a spectral property. We also present our analysis for a protein-protein interaction network in budding yeast.

  11. Next frontier in agent-based complex automated negotiation

    CERN Document Server

    Ito, Takayuki; Zhang, Minjie; Robu, Valentin

    2015-01-01

    This book focuses on automated negotiations based on multi-agent systems. It is intended for researchers and students in various fields involving autonomous agents and multi-agent systems, such as e-commerce tools, decision-making and negotiation support systems, and collaboration tools. The contents will help them to understand the concept of automated negotiations, negotiation protocols, negotiating agents’ strategies, and the applications of those strategies. In this book, some negotiation protocols focusing on the multiple interdependent issues in negotiations are presented, making it possible to find high-quality solutions for the complex agents’ utility functions. This book is a compilation of the extended versions of the very best papers selected from the many that were presented at the International Workshop on Agent-Based Complex Automated Negotiations.

  12. Seeking for Simplicity in Complex Networks

    CERN Document Server

    Costa, L F

    2007-01-01

    Complex networks can be understood as graphs whose connectivity deviates from those of regular or near-regular graphs (which can be understood as `simple'). While a great deal of the attention so far foressen for complex networks has been duly driven by the above principle, in this work we take the dual approach and address the identification of simplicity, in the sense of regularity, in complex networks. The basic idea is to seek for subgraphs exhibiting small dispersion (e.g. standard deviation or entropy) of local measurements such as the node degree and clustering coefficient. Here we consider two types of subgraphs: (a) those defined by the progressive neighborhoods around each node and (b) subgraphs obtained from sets of nodes presenting similar local measurements. The former approach allows the assignment of a hierarchical regularity index to all network nodes, the latter paves the way for the identification of subgraphs (patches) in the original network, with nearly uniform connectivity. We illustrate...

  13. Traffic congestion in interconnected complex networks.

    Science.gov (United States)

    Tan, Fei; Wu, Jiajing; Xia, Yongxiang; Tse, Chi K

    2014-06-01

    Traffic congestion in isolated complex networks has been investigated extensively over the last decade. Coupled network models have recently been developed to facilitate further understanding of real complex systems. Analysis of traffic congestion in coupled complex networks, however, is still relatively unexplored. In this paper, we try to explore the effect of interconnections on traffic congestion in interconnected Barabási-Albert scale-free networks. We find that assortative coupling can alleviate traffic congestion more readily than disassortative and random coupling when the node processing capacity is allocated based on node usage probability. Furthermore, the optimal coupling probability can be found for assortative coupling. However, three types of coupling preferences achieve similar traffic performance if all nodes share the same processing capacity. We analyze interconnected Internet autonomous-system-level graphs of South Korea and Japan and obtain similar results. Some practical suggestions are presented to optimize such real-world interconnected networks accordingly.

  14. Topological structural classes of complex networks

    Science.gov (United States)

    Estrada, Ernesto

    2007-01-01

    We use theoretical principles to study how complex networks are topologically organized at large scale. Using spectral graph theory we predict the existence of four different topological structural classes of networks. These classes correspond, respectively, to highly homogenous networks lacking structural bottlenecks, networks organized into highly interconnected modules with low inter-community connectivity, networks with a highly connected central core surrounded by a sparser periphery, and networks displaying a combination of highly connected groups (quasicliques) and groups of nodes partitioned into disjoint subsets (quasibipartites). Here we show by means of the spectral scaling method that these classes really exist in real-world ecological, biological, informational, technological, and social networks. We show that neither of three network growth mechanisms—random with uniform distribution, preferential attachment, and random with the same degree sequence as real network—is able to reproduce the four structural classes of complex networks. These models reproduce two of the network classes as a function of the average degree but completely fail in reproducing the other two classes of networks.

  15. Epidemics spreading in interconnected complex networks

    Energy Technology Data Exchange (ETDEWEB)

    Wang, Y. [School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore 639798 (Singapore); Institute of High Performance Computing, Agency for Science, Technology and Research (A-STAR), Singapore 138632 (Singapore); Xiao, G., E-mail: egxxiao@ntu.edu.sg [School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore 639798 (Singapore)

    2012-09-03

    We study epidemic spreading in two interconnected complex networks. It is found that in our model the epidemic threshold of the interconnected network is always lower than that in any of the two component networks. Detailed theoretical analysis is proposed which allows quick and accurate calculations of epidemic threshold and average outbreak/epidemic size. Theoretical analysis and simulation results show that, generally speaking, the epidemic size is not significantly affected by the inter-network correlation. In interdependent networks which can be viewed as a special case of interconnected networks, however, impacts of inter-network correlation on the epidemic threshold and outbreak size are more significant. -- Highlights: ► We study epidemic spreading in two interconnected complex networks. ► The epidemic threshold is lower than that in any of the two networks. And Interconnection correlation has impacts on threshold and average outbreak size. ► Detailed theoretical analysis is proposed which allows quick and accurate calculations of epidemic threshold and average outbreak/epidemic size. ► We demonstrated and proved that Interconnection correlation does not affect epidemic size significantly. ► In interdependent networks, impacts of inter-network correlation on the epidemic threshold and outbreak size are more significant.

  16. Robust Multi-Agent Sensor Network Systems

    Science.gov (United States)

    2012-05-08

    neighbors with c ≥ 5.1774 then the network is a.a.s. connected as n → ∞. In [8], Balister et al. advanced the results in [5] and improved the lower and...upper bounds to 0.3043 log n and 0.5139 log n respectively. In a more recent paper [10] Balister et al. achieved much improved results by showing...Computing, vol. 3, no. 3, pp. 246–257, 2004. [8] P. Balister , B. Bollobas, A. Sarkar, and M. Walters, “Con- nectivity of random k-nearest-neighbour graphs

  17. Agent Collaborative Target Localization and Classification in Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Sheng Wang

    2007-07-01

    Full Text Available Wireless sensor networks (WSNs are autonomous networks that have beenfrequently deployed to collaboratively perform target localization and classification tasks.Their autonomous and collaborative features resemble the characteristics of agents. Suchsimilarities inspire the development of heterogeneous agent architecture for WSN in thispaper. The proposed agent architecture views WSN as multi-agent systems and mobileagents are employed to reduce in-network communication. According to the architecture,an energy based acoustic localization algorithm is proposed. In localization, estimate oftarget location is obtained by steepest descent search. The search algorithm adapts tomeasurement environments by dynamically adjusting its termination condition. With theagent architecture, target classification is accomplished by distributed support vectormachine (SVM. Mobile agents are employed for feature extraction and distributed SVMlearning to reduce communication load. Desirable learning performance is guaranteed bycombining support vectors and convex hull vectors. Fusion algorithms are designed tomerge SVM classification decisions made from various modalities. Real world experimentswith MICAz sensor nodes are conducted for vehicle localization and classification.Experimental results show the proposed agent architecture remarkably facilitates WSNdesigns and algorithm implementation. The localization and classification algorithms alsoprove to be accurate and energy efficient.

  18. Competing epidemics on complex networks

    CERN Document Server

    Karrer, Brian

    2011-01-01

    Human diseases spread over networks of contacts between individuals and a substantial body of recent research has focused on the dynamics of the spreading process. Here we examine a model of two competing diseases spreading over the same network at the same time, where infection with either disease gives an individual subsequent immunity to both. Using a combination of analytic and numerical methods, we derive the phase diagram of the system and estimates of the expected final numbers of individuals infected with each disease. The system shows an unusual dynamical transition between dominance of one disease and dominance of the other as a function of their relative rates of growth. Close to this transition the final outcomes show strong dependence on stochastic fluctuations in the early stages of growth, dependence that decreases with increasing network size, but does so sufficiently slowly as still to be easily visible in systems with millions or billions of individuals. In most regions of the phase diagram ...

  19. Shock waves on complex networks

    CERN Document Server

    Mones, Enys; Vicsek, Tamás; Herrmann, Hans J

    2014-01-01

    Power grids, road maps, and river streams are examples of infrastructural networks which are highly vulnerable to external perturbations. An abrupt local change of load (voltage, traffic density, or water level) might propagate in a cascading way and affect a significant fraction of the network. Almost discontinuous perturbations can be modeled by shock waves which can eventually interfere constructively and endanger the normal functionality of the infrastructure. We study their dynamics by solving the Burgers equation under random perturbations on several real and artificial directed graphs. Even for graphs with a narrow distribution of node properties (e.g., degree or betweenness), a steady state is reached exhibiting a heterogeneous load distribution, having a difference of one order of magnitude between the highest and average loads. Unexpectedly we find for the European power grid and for finite Watts-Strogatz networks a broad pronounced bimodal distribution for the loads. To identify the most vulnerable...

  20. Motif structure and cooperation in real-world complex networks

    Science.gov (United States)

    Salehi, Mostafa; Rabiee, Hamid R.; Jalili, Mahdi

    2010-12-01

    Networks of dynamical nodes serve as generic models for real-world systems in many branches of science ranging from mathematics to physics, technology, sociology and biology. Collective behavior of agents interacting over complex networks is important in many applications. The cooperation between selfish individuals is one of the most interesting collective phenomena. In this paper we address the interplay between the motifs’ cooperation properties and their abundance in a number of real-world networks including yeast protein-protein interaction, human brain, protein structure, email communication, dolphins’ social interaction, Zachary karate club and Net-science coauthorship networks. First, the amount of cooperativity for all possible undirected subgraphs with three to six nodes is calculated. To this end, the evolutionary dynamics of the Prisoner’s Dilemma game is considered and the cooperativity of each subgraph is calculated as the percentage of cooperating agents at the end of the simulation time. Then, the three- to six-node motifs are extracted for each network. The significance of the abundance of a motif, represented by a Z-value, is obtained by comparing them with some properly randomized versions of the original network. We found that there is always a group of motifs showing a significant inverse correlation between their cooperativity amount and Z-value, i.e. the more the Z-value the less the amount of cooperativity. This suggests that networks composed of well-structured units do not have good cooperativity properties.

  1. Localized recovery of complex networks against failure

    Science.gov (United States)

    Shang, Yilun

    2016-07-01

    Resilience of complex networks to failure has been an important issue in network research for decades, and recent studies have begun to focus on the inverse recovery of network functionality through strategically healing missing nodes or edges. However, the effect of network recovery is far from fully understood, and a general theory is still missing. Here we propose and study a general model of localized recovery, where a group of neighboring nodes are restored in an invasive way from a seed node. We develop a theoretical framework to compare the effect of random recovery (RR) and localized recovery (LR) in complex networks including Erdős-Rényi networks, random regular networks, and scale-free networks. We find detailed phase diagrams for the subnetwork of occupied nodes and the “complement network” of failed nodes under RR and LR. By identifying the two competitive forces behind LR, we present an analytical and numerical approach to guide us in choosing the appropriate recovery strategy and provide estimation on its effect by using the degree distribution of the original network as the only input. Our work therefore provides insight for quantitatively understanding recovery process and its implications in infrastructure protection in various complex systems.

  2. Extracting the abstraction pyramid from complex networks

    Directory of Open Access Journals (Sweden)

    Hu Yuh-Jyh

    2010-08-01

    Full Text Available Abstract Background At present, the organization of system modules is typically limited to either a multilevel hierarchy that describes the "vertical" relationships between modules at different levels (e.g., module A at level two is included in module B at level one, or a single-level graph that represents the "horizontal" relationships among modules (e.g., genetic interactions between module A and module B. Both types of organizations fail to provide a broader and deeper view of the complex systems that arise from an integration of vertical and horizontal relationships. Results We propose a complex network analysis tool, Pyramabs, which was developed to integrate vertical and horizontal relationships and extract information at various granularities to create a pyramid from a complex system of interacting objects. The pyramid depicts the nested structure implied in a complex system, and shows the vertical relationships between abstract networks at different levels. In addition, at each level the abstract network of modules, which are connected by weighted links, represents the modules' horizontal relationships. We first tested Pyramabs on hierarchical random networks to verify its ability to find the module organization pre-embedded in the networks. We later tested it on a protein-protein interaction (PPI network and a metabolic network. According to Gene Ontology (GO and the Kyoto Encyclopedia of Genes and Genomes (KEGG, the vertical relationships identified from the PPI and metabolic pathways correctly characterized the inclusion (i.e., part-of relationship, and the horizontal relationships provided a good indication of the functional closeness between modules. Our experiments with Pyramabs demonstrated its ability to perform knowledge mining in complex systems. Conclusions Networks are a flexible and convenient method of representing interactions in a complex system, and an increasing amount of information in real-world situations is

  3. 8th Conference on Complex Networks

    CERN Document Server

    Menezes, Ronaldo; Sinatra, Roberta; Zlatic, Vinko

    2017-01-01

    This book collects the works presented at the 8th International Conference on Complex Networks (CompleNet) 2017 in Dubrovnik, Croatia, on March 21-24, 2017. CompleNet aims at bringing together researchers and practitioners working in areas related to complex networks. The past two decades has witnessed an exponential increase in the number of publications within this field. From biological systems to computer science, from economic to social systems, complex networks are becoming pervasive in many fields of science. It is this interdisciplinary nature of complex networks that CompleNet aims at addressing. The last decades have seen the emergence of complex networks as the language with which a wide range of complex phenomena in fields as diverse as physics, computer science, and medicine (to name a few) can be properly described and understood. This book provides a view of the state-of-the-art in this dynamic field and covers topics such as network controllability, social structure, online behavior, recommend...

  4. Maximizing information exchange between complex networks

    Science.gov (United States)

    West, Bruce J.; Geneston, Elvis L.; Grigolini, Paolo

    2008-10-01

    Science is not merely the smooth progressive interaction of hypothesis, experiment and theory, although it sometimes has that form. More realistically the scientific study of any given complex phenomenon generates a number of explanations, from a variety of perspectives, that eventually requires synthesis to achieve a deep level of insight and understanding. One such synthesis has created the field of out-of-equilibrium statistical physics as applied to the understanding of complex dynamic networks. Over the past forty years the concept of complexity has undergone a metamorphosis. Complexity was originally seen as a consequence of memory in individual particle trajectories, in full agreement with a Hamiltonian picture of microscopic dynamics and, in principle, macroscopic dynamics could be derived from the microscopic Hamiltonian picture. The main difficulty in deriving macroscopic dynamics from microscopic dynamics is the need to take into account the actions of a very large number of components. The existence of events such as abrupt jumps, considered by the conventional continuous time random walk approach to describing complexity was never perceived as conflicting with the Hamiltonian view. Herein we review many of the reasons why this traditional Hamiltonian view of complexity is unsatisfactory. We show that as a result of technological advances, which make the observation of single elementary events possible, the definition of complexity has shifted from the conventional memory concept towards the action of non-Poisson renewal events. We show that the observation of crucial processes, such as the intermittent fluorescence of blinking quantum dots as well as the brain’s response to music, as monitored by a set of electrodes attached to the scalp, has forced investigators to go beyond the traditional concept of complexity and to establish closer contact with the nascent field of complex networks. Complex networks form one of the most challenging areas of

  5. Maximizing information exchange between complex networks

    Energy Technology Data Exchange (ETDEWEB)

    West, Bruce J. [Mathematical and Information Science, Army Research Office, Research Triangle Park, NC 27708 (United States); Physics Department, Duke University, Durham, NC 27709 (United States)], E-mail: bwest@nc.rr.com; Geneston, Elvis L. [Center for Nonlinear Science, University of North Texas, P.O. Box 311427, Denton, TX 76203-1427 (United States); Physics Department, La Sierra University, 4500 Riverwalk Parkway, Riverside, CA 92515 (United States); Grigolini, Paolo [Center for Nonlinear Science, University of North Texas, P.O. Box 311427, Denton, TX 76203-1427 (United States); Istituto di Processi Chimico Fisici del CNR, Area della Ricerca di Pisa, Via G. Moruzzi, 56124, Pisa (Italy); Dipartimento di Fisica ' E. Fermi' Universita' di Pisa, Largo Pontecorvo 3, 56127 Pisa (Italy)

    2008-10-15

    Science is not merely the smooth progressive interaction of hypothesis, experiment and theory, although it sometimes has that form. More realistically the scientific study of any given complex phenomenon generates a number of explanations, from a variety of perspectives, that eventually requires synthesis to achieve a deep level of insight and understanding. One such synthesis has created the field of out-of-equilibrium statistical physics as applied to the understanding of complex dynamic networks. Over the past forty years the concept of complexity has undergone a metamorphosis. Complexity was originally seen as a consequence of memory in individual particle trajectories, in full agreement with a Hamiltonian picture of microscopic dynamics and, in principle, macroscopic dynamics could be derived from the microscopic Hamiltonian picture. The main difficulty in deriving macroscopic dynamics from microscopic dynamics is the need to take into account the actions of a very large number of components. The existence of events such as abrupt jumps, considered by the conventional continuous time random walk approach to describing complexity was never perceived as conflicting with the Hamiltonian view. Herein we review many of the reasons why this traditional Hamiltonian view of complexity is unsatisfactory. We show that as a result of technological advances, which make the observation of single elementary events possible, the definition of complexity has shifted from the conventional memory concept towards the action of non-Poisson renewal events. We show that the observation of crucial processes, such as the intermittent fluorescence of blinking quantum dots as well as the brain's response to music, as monitored by a set of electrodes attached to the scalp, has forced investigators to go beyond the traditional concept of complexity and to establish closer contact with the nascent field of complex networks. Complex networks form one of the most challenging areas of

  6. Simplistic pathways or complex networks?

    DEFF Research Database (Denmark)

    Jørgensen, Claus; Linding, Rune

    2010-01-01

    Signaling events are frequently described in textbooks as linear cascades. However, in reality, input cues are processed by dynamic and context-specific networks, which are assembled from numerous signaling molecules. Diseases, such as cancer, are typically associated with multiple genomic altera...

  7. Controlling centrality in complex networks

    CERN Document Server

    Nicosia, Vincenzo; Romance, Miguel; Russo, Giovanni; Latora, Vito

    2011-01-01

    Spectral centrality measures allow to identify influential individuals in social groups, to rank Web pages by their popularity, and even to determine the impact of scientific researches. The centrality score of a node within a network crucially depends on the entire pattern of connections, so that the usual approach is to compute the node centralities once the network structure is assigned. We face here with the inverse problem, that is, we study how to modify the centrality scores of the nodes by acting on the structure of a given network. We prove that there exist particular subsets of nodes, called controlling sets, which can assign any prescribed set of centrality values to all the nodes of a graph, by cooperatively tuning the weights of their out-going links. We show that many large networks from the real world have surprisingly small controlling sets, containing even less than 5-10% of the nodes. These results suggest that rankings obtained from spectral centrality measures have to be considered with ex...

  8. Traffic resource allocation for complex networks

    Institute of Scientific and Technical Information of China (English)

    Ling Xiang; Hu Mao-Bin; Long Jian-Cheng; Ding Jian-Xun; Shi Qin

    2013-01-01

    In this paper,an optimal resource allocation strategy is proposed to enhance traffic dynamics in complex networks.The network resources are the total node packet-delivering capacity and the total link bandwidth.An analytical method is developed to estimate the overall network capacity by using the concept of efficient betweenness (ratio of algorithmic betweenness and local processing capacity).Three network structures (scale-free,small-world,and random networks) and two typical routing protocols (shortest path protocol and efficient routing protocol) are adopted to demonstrate the performance of the proposed strategy.Our results show that the network capacity is reversely proportional to the average path length for a particular routing protocol and the shortest path protocol can achieve the largest network capacity when the proposed resource allocation strategy is adopted.

  9. Factors determining nestedness in complex networks

    CERN Document Server

    Johnson, Samuel; Munoz, Miguel A

    2013-01-01

    Understanding the causes and effects of network structural features is a key task in deciphering complex systems. In this context, the property of network nestedness has aroused a fair amount of interest as regards ecological networks. Indeed, Bastolla et al. introduced a simple measure of network nestedness which opened the door to analytical understanding, allowing them to conclude that biodiversity is strongly enhanced in highly nested mutualistic networks. Here, we suggest a slightly refined version of such a measure and go on to study how it is influenced by the most basic structural properties of networks, such as degree distribution and degree-degree correlations (i.e. assortativity). We find that heterogeneity in the degree has a very strong influence on nestedness. Once such an influence has been discounted, we find that nestedness is strongly correlated with disassortativity and hence, as random (neutral) networks have been recently found to be naturally disassortative, they tend to be naturally nes...

  10. Controlling edge dynamics in complex networks

    CERN Document Server

    Nepusz, Tamás

    2011-01-01

    The interaction of distinct units in physical, social, biological and technological systems naturally gives rise to complex network structures. Networks have constantly been in the focus of research for the last decade, with considerable advances in the description of their structural and dynamical properties. However, much less effort has been devoted to studying the controllability of the dynamics taking place on them. Here we introduce and evaluate a dynamical process defined on the edges of a network, and demonstrate that the controllability properties of this process significantly differ from simple nodal dynamics. Evaluation of real-world networks indicates that most of them are more controllable than their randomized counterparts. We also find that transcriptional regulatory networks are particularly easy to control. Analytic calculations show that networks with scale-free degree distributions have better controllability properties than uncorrelated networks, and positively correlated in- and out-degre...

  11. Discovering large network motifs from a complex biological network

    Energy Technology Data Exchange (ETDEWEB)

    Terada, Aika; Sese, Jun, E-mail: terada@sel.is.ocha.ac.j, E-mail: sesejun@is.ocha.ac.j [Department of Computer Science, Ochanomizu University, 2-1-1 Ohtsuka, Bunkyo-ku, Tokyo 112-8610 (Japan)

    2009-12-01

    Graph structures representing relationships between entries have been studied in statistical analysis, and the results of these studies have been applied to biological networks, whose nodes and edges represent proteins and the relationships between them, respectively. Most of the studies have focused on only graph structures such as scale-free properties and cliques, but the relationships between nodes are also important features since most of the proteins perform their functions by connecting to other proteins. In order to determine such relationships, the problem of network motif discovery has been addressed; network motifs are frequently appearing graph structures in a given graph. However, the methods for network motif discovery are highly restrictive for the application to biological network because they can only be used to find small network motifs or they do not consider noise and uncertainty in observations. In this study, we introduce a new index to measure network motifs called AR index and develop a novel algorithm called ARIANA for finding large motifs even when the network has noise. Experiments using a synthetic network verify that our method can find better network motifs than an existing algorithm. By applying ARIANA to a real complex biological network, we find network motifs associated with regulations of start time of cell functions and generation of cell energies and discover that the cell cycle proteins can be categorized into two different groups.

  12. Neural Networks as Improving Tools for Agent Behavior

    Directory of Open Access Journals (Sweden)

    Alketa Hyso

    2011-05-01

    Full Text Available Current trends in software development show a move towards supporting autonomous, rational components (agents. One of the most interesting issues in agent technology has always been the modeling and enhancement of agent behavior. In this paper we are focused in the intersection of agent technology and machine learning techniques for producing intelligent agents. Our application shows that using neural network techniques we improve the reasoning mechanism of our agent supplying to it a new behavior which it did not possess from the beginning. The learning process can be applied initially to train 'dummy' agent to further improve agent reasoning. The machine learning algorithms allow for an agent to adequately respond to environment changes and improve the behavioral rules or acquire intelligent behavior. A case study will be given to demonstrate such enhancement. We simulate the behavior of a robot moving in an environment with random obstacles. Learning techniques that are added to the reasoning mechanism of this robot enrich his behavior in the dynamic environment, displaying a rational and intelligent behavior.

  13. Onset of traffic congestion in complex networks.

    Science.gov (United States)

    Zhao, Liang; Lai, Ying-Cheng; Park, Kwangho; Ye, Nong

    2005-02-01

    Free traffic flow on a complex network is key to its normal and efficient functioning. Recent works indicate that many realistic networks possess connecting topologies with a scale-free feature: the probability distribution of the number of links at nodes, or the degree distribution, contains a power-law component. A natural question is then how the topology influences the dynamics of traffic flow on a complex network. Here we present two models to address this question, taking into account the network topology, the information-generating rate, and the information-processing capacity of individual nodes. For each model, we study four kinds of networks: scale-free, random, and regular networks and Cayley trees. In the first model, the capacity of packet delivery of each node is proportional to its number of links, while in the second model, it is proportional to the number of shortest paths passing through the node. We find, in both models, that there is a critical rate of information generation, below which the network traffic is free but above which traffic congestion occurs. Theoretical estimates are given for the critical point. For the first model, scale-free networks and random networks are found to be more tolerant to congestion. For the second model, the congestion condition is independent of network size and topology, suggesting that this model may be practically useful for designing communication protocols.

  14. A Framework for Evaluating Complex Networks Measurements

    CERN Document Server

    Comin, Cesar H; Costa, Luciano da F

    2014-01-01

    A good deal of current research in complex networks involves the characterization and/or classification of the topological properties of given structures, which has motivated several respective measurements. This letter proposes a framework for evaluating the quality of complex network measurements in terms of their effective resolution, degree of degeneracy and discriminability. The potential of the suggested approach is illustrated with respect to comparing the characterization of several model and real-world networks by using concentric and symmetry measurements. The results indicate a markedly superior performance for the latter type of mapping.

  15. Topology identification of complex dynamical networks

    Science.gov (United States)

    Zhao, Junchan; Li, Qin; Lu, Jun-An; Jiang, Zhong-Ping

    2010-06-01

    Recently, some researchers investigated the topology identification for complex networks via LaSalle's invariance principle. The principle cannot be directly applied to time-varying systems since the positive limit sets are generally not invariant. In this paper, we study the topology identification problem for a class of weighted complex networks with time-varying node systems. Adaptive identification laws are proposed to estimate the coupling parameters of the networks with and without communication delays. We prove that the asymptotic identification is ensured by a persistently exciting condition. Numerical simulations are given to demonstrate the effectiveness of the proposed approach.

  16. Study of the Improvement on Network Management Performance with Mobile Agent

    Institute of Scientific and Technical Information of China (English)

    LI Jie; WANG Ru-chuan

    2003-01-01

    Owing to the increasing great complexity, computer network systems require more sophisticated management strategies to be adopted so as to guarantee adequate levels of performance. The classic centralized paradigm, adopted by SNMP, which was once appropriate in the prevenient phrase, has posed problems with the explosive expansion of networks, as well as other centralized models. Mobile Agent (MA), owing to its capability of implementing a distributed system, represents a challenging approach to provide network management with high performance. In this paper we analyze the network management structure model based on MA at first, and then we put forward a reference scenario based on MA and compare it with the traditional model. We also describe a prototype implementation based on our mobile agent system named MAS. Finally, we do some experiments to verify the performance of our framework prototype.

  17. Impact of mobility structure on the optimization of small-world networks of mobile agents

    CERN Document Server

    Lee, Eun

    2015-01-01

    In ad hoc wireless networking, units are connected to each other rather than to a central, fixed, infrastructure. Constructing and maintaining such networks create several trade-off problems between robustness, communication speed, power consumption, etc., that bridges engineering, computer science and the physics of complex systems. In this work, we address the role of mobility patterns of the agents on the optimal tuning of a small-world type network construction method. By this method, the network is updated periodically and held static between the updates. We investigate the optimal updating times for different scenarios of the movement of agents (modeling, for example, the fat-tailed trip distances, and periodicities, of human travel). We find that these mobility patterns affect the power consumption in non-trivial ways and discuss how these effects can best be handled.

  18. Impact of mobility structure on optimization of small-world networks of mobile agents

    Science.gov (United States)

    Lee, Eun; Holme, Petter

    2016-06-01

    In ad hoc wireless networking, units are connected to each other rather than to a central, fixed, infrastructure. Constructing and maintaining such networks create several trade-off problems between robustness, communication speed, power consumption, etc., that bridges engineering, computer science and the physics of complex systems. In this work, we address the role of mobility patterns of the agents on the optimal tuning of a small-world type network construction method. By this method, the network is updated periodically and held static between the updates. We investigate the optimal updating times for different scenarios of the movement of agents (modeling, for example, the fat-tailed trip distances, and periodicities, of human travel). We find that these mobility patterns affect the power consumption in non-trivial ways and discuss how these effects can best be handled.

  19. The price of complexity in financial networks.

    Science.gov (United States)

    Battiston, Stefano; Caldarelli, Guido; May, Robert M; Roukny, Tarik; Stiglitz, Joseph E

    2016-09-06

    Financial institutions form multilayer networks by engaging in contracts with each other and by holding exposures to common assets. As a result, the default probability of one institution depends on the default probability of all of the other institutions in the network. Here, we show how small errors on the knowledge of the network of contracts can lead to large errors in the probability of systemic defaults. From the point of view of financial regulators, our findings show that the complexity of financial networks may decrease the ability to mitigate systemic risk, and thus it may increase the social cost of financial crises.

  20. The price of complexity in financial networks

    Science.gov (United States)

    Battiston, Stefano; Caldarelli, Guido; May, Robert M.; Roukny, Tarik; Stiglitz, Joseph E.

    2016-09-01

    Financial institutions form multilayer networks by engaging in contracts with each other and by holding exposures to common assets. As a result, the default probability of one institution depends on the default probability of all of the other institutions in the network. Here, we show how small errors on the knowledge of the network of contracts can lead to large errors in the probability of systemic defaults. From the point of view of financial regulators, our findings show that the complexity of financial networks may decrease the ability to mitigate systemic risk, and thus it may increase the social cost of financial crises.

  1. The price of complexity in financial networks

    Science.gov (United States)

    May, Robert M.; Roukny, Tarik; Stiglitz, Joseph E.

    2016-01-01

    Financial institutions form multilayer networks by engaging in contracts with each other and by holding exposures to common assets. As a result, the default probability of one institution depends on the default probability of all of the other institutions in the network. Here, we show how small errors on the knowledge of the network of contracts can lead to large errors in the probability of systemic defaults. From the point of view of financial regulators, our findings show that the complexity of financial networks may decrease the ability to mitigate systemic risk, and thus it may increase the social cost of financial crises. PMID:27555583

  2. Quantum-classical transitions in complex networks

    Science.gov (United States)

    Javarone, Marco Alberto; Armano, Giuliano

    2013-04-01

    The inherent properties of specific physical systems can be used as metaphors for investigation of the behavior of complex networks. This insight has already been put into practice in previous work, e.g., studying the network evolution in terms of phase transitions of quantum gases or representing distances among nodes as if they were particle energies. This paper shows that the emergence of different structures in complex networks, such as the scale-free and the winner-takes-all networks, can be represented in terms of a quantum-classical transition for quantum gases. In particular, we propose a model of fermionic networks that allows us to investigate the network evolution and its dependence on the system temperature. Simulations, performed in accordance with the cited model, clearly highlight the separation between classical random and winner-takes-all networks, in full correspondence with the separation between classical and quantum regions for quantum gases. We deem this model useful for the analysis of synthetic and real complex networks.

  3. Analysis of complex networks using aggressive abstraction.

    Energy Technology Data Exchange (ETDEWEB)

    Colbaugh, Richard; Glass, Kristin.; Willard, Gerald

    2008-10-01

    This paper presents a new methodology for analyzing complex networks in which the network of interest is first abstracted to a much simpler (but equivalent) representation, the required analysis is performed using the abstraction, and analytic conclusions are then mapped back to the original network and interpreted there. We begin by identifying a broad and important class of complex networks which admit abstractions that are simultaneously dramatically simplifying and property preserving we call these aggressive abstractions -- and which can therefore be analyzed using the proposed approach. We then introduce and develop two forms of aggressive abstraction: 1.) finite state abstraction, in which dynamical networks with uncountable state spaces are modeled using finite state systems, and 2.) onedimensional abstraction, whereby high dimensional network dynamics are captured in a meaningful way using a single scalar variable. In each case, the property preserving nature of the abstraction process is rigorously established and efficient algorithms are presented for computing the abstraction. The considerable potential of the proposed approach to complex networks analysis is illustrated through case studies involving vulnerability analysis of technological networks and predictive analysis for social processes.

  4. Access Path Planning of Mobile Agent in Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Chaoyu Yang

    2014-02-01

    Full Text Available Adopting the two-stage optimization model and hybrid optimized algorithm based on evolutionary computation, a new two-stage optimization model that more conforms to the actual demand is proposed on the basis of formal description of Mobile Agent access path planning. This new model divides the access path planning problem into two sub problems of integer linear programming --data integration sub paths and return sub paths, which can reduce search space and improve the efficiency of algorithm. Then a hybrid optimized method named GAPSO, combined with GA (Genetic Algorithm and PSO (Particle Swarm Optimization, is advanced to solve this model, which integrates discrete PSO into the interlace operation of GA to avoid infeasible solution and improve search quality. Meanwhile convergence can be accelerated by optimizing the GA population with PSO in search of return sub paths. By means of virtual connected topology graph, the high-quality to-be-accessed candidate node set is acquired, the number of to-be-selected nodes is reduced,and the complexity of solution space is decreased, making planning algorithm performance not rely on network scale directly any more. Simulation results show that the advantages of the optimization model is obvious as the node number increases, and GASPO has a better performance than GA and BPSO in the same model

  5. Quantum Navigation and Ranking in Complex Networks

    Science.gov (United States)

    Sánchez-Burillo, Eduardo; Duch, Jordi; Gómez-Gardeñes, Jesús; Zueco, David

    2012-08-01

    Complex networks are formal frameworks capturing the interdependencies between the elements of large systems and databases. This formalism allows to use network navigation methods to rank the importance that each constituent has on the global organization of the system. A key example is Pagerank navigation which is at the core of the most used search engine of the World Wide Web. Inspired in this classical algorithm, we define a quantum navigation method providing a unique ranking of the elements of a network. We analyze the convergence of quantum navigation to the stationary rank of networks and show that quantumness decreases the number of navigation steps before convergence. In addition, we show that quantum navigation allows to solve degeneracies found in classical ranks. By implementing the quantum algorithm in real networks, we confirm these improvements and show that quantum coherence unveils new hierarchical features about the global organization of complex systems.

  6. Complex Networks and Symmetry I: A Review

    Directory of Open Access Journals (Sweden)

    Riccardo Basosi

    2010-09-01

    Full Text Available In this review we establish various connections between complex networks and symmetry. While special types of symmetries (e.g., automorphisms are studied in detail within discrete mathematics for particular classes of deterministic graphs, the analysis of more general symmetries in real complex networks is far less developed. We argue that real networks, as any entity characterized by imperfections or errors, necessarily require a stochastic notion of invariance. We therefore propose a definition of stochastic symmetry based on graph ensembles and use it to review the main results of network theory from an unusual perspective. The results discussed here and in a companion paper show that stochastic symmetry highlights the most informative topological properties of real networks, even in noisy situations unaccessible to exact techniques.

  7. Parallel Graph Partitioning for Complex Networks

    CERN Document Server

    Meyerhenke, Henning; Schulz, Christian

    2014-01-01

    Processing large complex networks like social networks or web graphs has recently attracted considerable interest. In order to do this in parallel, we need to partition them into pieces of about equal size. Unfortunately, previous parallel graph partitioners originally developed for more regular mesh-like networks do not work well for these networks. This paper addresses this problem by parallelizing and adapting the label propagation technique originally developed for graph clustering. By introducing size constraints, label propagation becomes applicable for both the coarsening and the refinement phase of multilevel graph partitioning. We obtain very high quality by applying a highly parallel evolutionary algorithm to the coarsened graph. The resulting system is both more scalable and achieves higher quality than state-of-the-art systems like ParMetis or PT-Scotch. For large complex networks the performance differences are very big. For example, our algorithm can partition a web graph with 3.3 billion edges ...

  8. Visualization and Analysis of Complex Covert Networks

    DEFF Research Database (Denmark)

    Memon, Bisharat

    systems that are covert and hence inherently complex. My Ph.D. is positioned within the wider framework of CrimeFighter project. The framework envisions a number of key knowledge management processes that are involved in the workflow, and the toolbox provides supporting tools to assist human end......This report discusses and summarize the results of my work so far in relation to my Ph.D. project entitled "Visualization and Analysis of Complex Covert Networks". The focus of my research is primarily on development of methods and supporting tools for visualization and analysis of networked......-users (intelligence analysts) in harvesting, filtering, storing, managing, structuring, mining, analyzing, interpreting, and visualizing data about offensive networks. The methods and tools proposed and discussed in this work can also be applied to analysis of more generic complex networks....

  9. Traffic congestion in interconnected complex networks

    CERN Document Server

    Tan, Fei; Xia, Yongxiang; Tse, Chi K

    2014-01-01

    Traffic congestion in isolated complex networks has been investigated extensively over the last decade. Coupled network models have recently been developed to facilitate further understanding of real complex systems. Analysis of traffic congestion in coupled complex networks, however, is yet to come. In this paper, we try to explore the effect of interconnections on traffic congestion in interconnected BA scale-free networks. We find that assortative coupling can alleviate traffic congestion better than disassortative and random coupling when the node processing capacity is allocated based on node usage probability. Furthermore, the optimal coupling probability can be found for assortative coupling. However, three types of coupling preferences achieve similar traffic performance if all nodes share the same processing capacity. We analyze interconnected Internet AS-level graphs of Japan and South Korea and obtain similar results. Some practical suggestions are presented to optimize such real-world interconnect...

  10. Epidemic spread over networks with agent awareness and social distancing

    KAUST Repository

    Paarporn, Keith

    2016-04-20

    We study an SIS epidemic model over an arbitrary connected network topology when the agents receive personalized information about the current epidemic state. The agents utilize their available information to either reduce interactions with their neighbors (social distancing) when they believe the epidemic is currently prevalent or resume normal interactions when they believe there is low risk of becoming infected. The information is a weighted combination of three sources: 1) the average states of nodes in contact neighborhoods 2) the average states of nodes in an information network 3) a global broadcast of the average epidemic state of the network. A 2n-state Markov Chain is first considered to model the disease dynamics with awareness, from which a mean-field discrete-time n-state dynamical system is derived, where each state corresponds to an agent\\'s probability of being infected. The nonlinear model is a lower bound of its linearized version about the origin. Hence, global stability of the origin (the diseasefree equilibrium) in the linear model implies global stability in the nonlinear model. When the origin is not stable, we show the existence of a nontrivial fixed point in the awareness model, which obeys a strict partial order in relation to the nontrivial fixed point of the dynamics without distancing. In simulations, we define two performance metrics to understand the effectiveness agent awareness has in reducing the spread of an epidemic. © 2015 IEEE.

  11. On infrastructure network design with agent-based modelling

    NARCIS (Netherlands)

    Chappin, E.J.L.; Heijnen, P.W.

    2014-01-01

    We have developed an agent-based model to optimize green-field network design in an industrial area. We aim to capture some of the deep uncertainties surrounding infrastructure design by modelling it developing specific ant colony optimizations. Hence, we propose a variety of extensions to our

  12. On infrastructure network design with agent-based modelling

    NARCIS (Netherlands)

    Chappin, E.J.L.; Heijnen, P.W.

    2014-01-01

    We have developed an agent-based model to optimize green-field network design in an industrial area. We aim to capture some of the deep uncertainties surrounding infrastructure design by modelling it developing specific ant colony optimizations. Hence, we propose a variety of extensions to our exist

  13. Agent-based Personal Network (PN) service architecture

    DEFF Research Database (Denmark)

    Jiang, Bo; Olesen, Henning

    2004-01-01

    In this paper we proposte a new concept for a centralized agent system as the solution for the PN service architecture, which aims to efficiently control and manage the PN resources and enable the PN based services to run seamlessly over different networks and devices. The working principle...

  14. Complex cooperative networks from evolutionary preferential attachment.

    Directory of Open Access Journals (Sweden)

    Julia Poncela

    Full Text Available In spite of its relevance to the origin of complex networks, the interplay between form and function and its role during network formation remains largely unexplored. While recent studies introduce dynamics by considering rewiring processes of a pre-existent network, we study network growth and formation by proposing an evolutionary preferential attachment model, its main feature being that the capacity of a node to attract new links depends on a dynamical variable governed in turn by the node interactions. As a specific example, we focus on the problem of the emergence of cooperation by analyzing the formation of a social network with interactions given by the Prisoner's Dilemma. The resulting networks show many features of real systems, such as scale-free degree distributions, cooperative behavior and hierarchical clustering. Interestingly, results such as the cooperators being located mostly on nodes of intermediate degree are very different from the observations of cooperative behavior on static networks. The evolutionary preferential attachment mechanism points to an evolutionary origin of scale-free networks and may help understand similar feedback problems in the dynamics of complex networks by appropriately choosing the game describing the interaction of nodes.

  15. Understanding Supply Networks from Complex Adaptive Systems

    Directory of Open Access Journals (Sweden)

    Jamur Johnas Marchi

    2014-10-01

    Full Text Available This theoretical paper is based on complex adaptive systems (CAS that integrate dynamic and holistic elements, aiming to discuss supply networks as complex systems and their dynamic and co-evolutionary processes. The CAS approach can give clues to understand the dynamic nature and co-evolution of supply networks because it consists of an approach that incorporates systems and complexity. This paper’s overall contribution is to reinforce the theoretical discussion of studies that have addressed supply chain issues, such as CAS.

  16. Information and material flows in complex networks

    Science.gov (United States)

    Helbing, Dirk; Armbruster, Dieter; Mikhailov, Alexander S.; Lefeber, Erjen

    2006-04-01

    In this special issue, an overview of the Thematic Institute (TI) on Information and Material Flows in Complex Systems is given. The TI was carried out within EXYSTENCE, the first EU Network of Excellence in the area of complex systems. Its motivation, research approach and subjects are presented here. Among the various methods used are many-particle and statistical physics, nonlinear dynamics, as well as complex systems, network and control theory. The contributions are relevant for complex systems as diverse as vehicle and data traffic in networks, logistics, production, and material flows in biological systems. The key disciplines involved are socio-, econo-, traffic- and bio-physics, and a new research area that could be called “biologistics”.

  17. The Kuramoto model in complex networks

    CERN Document Server

    Rodrigues, Francisco A; Ji, Peng; Kurths, Jürgen

    2016-01-01

    Synchronization of an ensemble of oscillators is an emergent phenomenon present in several complex systems, ranging from social and physical to biological and technological systems. The most successful approach to describe how coherent behavior emerges in these complex systems is given by the paradigmatic Kuramoto model. This model has been traditionally studied in complete graphs. However, besides being intrinsically dynamical, complex systems present very heterogeneous structure, which can be represented as complex networks. This report is dedicated to review main contributions in the field of synchronization in networks of Kuramoto oscillators. In particular, we provide an overview of the impact of network patterns on the local and global dynamics of coupled phase oscillators. We cover many relevant topics, which encompass a description of the most used analytical approaches and the analysis of several numerical results. Furthermore, we discuss recent developments on variations of the Kuramoto model in net...

  18. Low Computational Complexity Network Coding For Mobile Networks

    DEFF Research Database (Denmark)

    Heide, Janus

    2012-01-01

    Network Coding (NC) is a technique that can provide benefits in many types of networks, some examples from wireless networks are: In relay networks, either the physical or the data link layer, to reduce the number of transmissions. In reliable multicast, to reduce the amount of signaling and enable...... cooperation among receivers. In meshed networks, to simplify routing schemes and to increase robustness toward node failures. This thesis deals with implementation issues of one NC technique namely Random Linear Network Coding (RLNC) which can be described as a highly decentralized non-deterministic intra......-flow coding technique. One of the key challenges of this technique is its inherent computational complexity which can lead to high computational load and energy consumption in particular on the mobile platforms that are the target platform in this work. To increase the coding throughput several...

  19. Deterministic gathering of anonymous agents in arbitrary networks

    CERN Document Server

    Dieudonné, Yoann

    2011-01-01

    A team consisting of an unknown number of mobile agents, starting from different nodes of an unknown network, possibly at different times, have to meet at the same node. Agents are anonymous (identical), execute the same deterministic algorithm and move in synchronous rounds along links of the network. Which configurations are gatherable and how to gather all of them deterministically by the same algorithm? We give a complete solution of this gathering problem in arbitrary networks. We characterize all gatherable configurations and give two universal deterministic gathering algorithms, i.e., algorithms that gather all gatherable configurations. The first algorithm works under the assumption that an upper bound n on the size of the network is known. In this case our algorithm guarantees gathering with detection, i.e., the existence of a round for any gatherable configuration, such that all agents are at the same node and all declare that gathering is accomplished. If no upper bound on the size of the network i...

  20. Dynamic information routing in complex networks

    Science.gov (United States)

    Kirst, Christoph; Timme, Marc; Battaglia, Demian

    2016-01-01

    Flexible information routing fundamentally underlies the function of many biological and artificial networks. Yet, how such systems may specifically communicate and dynamically route information is not well understood. Here we identify a generic mechanism to route information on top of collective dynamical reference states in complex networks. Switching between collective dynamics induces flexible reorganization of information sharing and routing patterns, as quantified by delayed mutual information and transfer entropy measures between activities of a network's units. We demonstrate the power of this mechanism specifically for oscillatory dynamics and analyse how individual unit properties, the network topology and external inputs co-act to systematically organize information routing. For multi-scale, modular architectures, we resolve routing patterns at all levels. Interestingly, local interventions within one sub-network may remotely determine nonlocal network-wide communication. These results help understanding and designing information routing patterns across systems where collective dynamics co-occurs with a communication function. PMID:27067257

  1. Distributed multiple path routing in complex networks

    Science.gov (United States)

    Chen, Guang; Wang, San-Xiu; Wu, Ling-Wei; Mei, Pan; Yang, Xu-Hua; Wen, Guang-Hui

    2016-12-01

    Routing in complex transmission networks is an important problem that has garnered extensive research interest in the recent years. In this paper, we propose a novel routing strategy called the distributed multiple path (DMP) routing strategy. For each of the O-D node pairs in a given network, the DMP routing strategy computes and stores multiple short-length paths that overlap less with each other in advance. And during the transmission stage, it rapidly selects an actual routing path which provides low transmission cost from the pre-computed paths for each transmission task, according to the real-time network transmission status information. Computer simulation results obtained for the lattice, ER random, and scale-free networks indicate that the strategy can significantly improve the anti-congestion ability of transmission networks, as well as provide favorable routing robustness against partial network failures.

  2. Dynamic information routing in complex networks

    CERN Document Server

    Kirst, Christoph; Battaglia, Demian

    2015-01-01

    Flexible information routing fundamentally underlies the function of many biological and artificial networks. Yet, how such systems may specifically communicate and dynamically route information is not well understood. Here we identify a generic mechanism to route information on top of collective dynamical reference states in complex networks. Switching between collective dynamics induces flexible reorganization of information sharing and routing patterns, as quantified by delayed mutual information and transfer entropy measures between activities of a network's units. We demonstrate the power of this generic mechanism specifically for oscillatory dynamics and analyze how individual unit properties, the network topology and external inputs coact to systematically organize information routing. For multi-scale, modular architectures, we resolve routing patterns at all levels. Interestingly, local interventions within one sub-network may remotely determine non-local network-wide communication. These results help...

  3. Information sharing in Quantum Complex Networks

    CERN Document Server

    Cardillo, Alessio; Zueco, David; Gómez-Gardeñes, Jesús

    2013-01-01

    We introduce the use of entanglement entropy as a tool for studying the amount of information shared between the nodes of quantum complex networks. By considering the ground state of a network of coupled quantum harmonic oscillators, we compute the information that each node has on the rest of the system. We show that the nodes storing the largest amount of information are not the ones with the highest connectivity, but those with intermediate connectivity thus breaking down the usual hierarchical picture of classical networks. We show both numerically and analytically that the mutual information characterizes the network topology. As a byproduct, our results point out that the amount of information available for an external node connecting to a quantum network allows to determine the network topology.

  4. Random matrix analysis of complex networks.

    Science.gov (United States)

    Jalan, Sarika; Bandyopadhyay, Jayendra N

    2007-10-01

    We study complex networks under random matrix theory (RMT) framework. Using nearest-neighbor and next-nearest-neighbor spacing distributions we analyze the eigenvalues of the adjacency matrix of various model networks, namely, random, scale-free, and small-world networks. These distributions follow the Gaussian orthogonal ensemble statistic of RMT. To probe long-range correlations in the eigenvalues we study spectral rigidity via the Delta_{3} statistic of RMT as well. It follows RMT prediction of linear behavior in semilogarithmic scale with the slope being approximately 1pi;{2} . Random and scale-free networks follow RMT prediction for very large scale. A small-world network follows it for sufficiently large scale, but much less than the random and scale-free networks.

  5. Dynamic information routing in complex networks

    Science.gov (United States)

    Kirst, Christoph; Timme, Marc; Battaglia, Demian

    2016-04-01

    Flexible information routing fundamentally underlies the function of many biological and artificial networks. Yet, how such systems may specifically communicate and dynamically route information is not well understood. Here we identify a generic mechanism to route information on top of collective dynamical reference states in complex networks. Switching between collective dynamics induces flexible reorganization of information sharing and routing patterns, as quantified by delayed mutual information and transfer entropy measures between activities of a network's units. We demonstrate the power of this mechanism specifically for oscillatory dynamics and analyse how individual unit properties, the network topology and external inputs co-act to systematically organize information routing. For multi-scale, modular architectures, we resolve routing patterns at all levels. Interestingly, local interventions within one sub-network may remotely determine nonlocal network-wide communication. These results help understanding and designing information routing patterns across systems where collective dynamics co-occurs with a communication function.

  6. Consistently weighted measures for complex network topologies

    CERN Document Server

    Heitzig, Jobst; Zou, Yong; Marwan, Norbert; Kurths, Jürgen

    2011-01-01

    When network and graph theory are used in the study of complex systems, a typically finite set of nodes of the network under consideration is frequently either explicitly or implicitly considered representative of a much larger finite or infinite set of objects of interest. The selection procedure, e.g., formation of a subset or some kind of discretization or aggregation, typically results in individual nodes of the studied network representing quite differently sized parts of the domain of interest. This heterogeneity may induce substantial bias and artifacts in derived network statistics. To avoid this bias, we propose an axiomatic scheme based on the idea of {\\em node splitting invariance} to derive consistently weighted variants of various commonly used statistical network measures. The practical relevance and applicability of our approach is demonstrated for a number of example networks from different fields of research, and is shown to be of fundamental importance in particular in the study of climate n...

  7. Identifying Functional Modules in Complex Networks

    Institute of Scientific and Technical Information of China (English)

    2007-01-01

    In this paper, we propose a new method that enables us to detect and describe the functional modules in complex networks. Using the proposed method, we can classify the nodes of networks into different modules according to their pattern of intra- and extra-module links. We use our method to analyze the modular structures of the ER random networks. We find that different modules of networks have different structure properties, such as the clustering coefficient. Moreover, at the same time, many nodes of networks participate different modules. Remarkably, we find that in the ER random networks, when the probability p is small, different modules or different roles of nodes can be identified by different regionsin the c-p parameter space.

  8. Complex Network Characteristics and Invulnerability Simulating Analysis of Supply Chain

    OpenAIRE

    Hui-Huang Chen; Ai-Min Lin

    2012-01-01

    To study the characteristics of the complex supply chain, a invulnerability analysis method based on the complex network theory is proposed. The topological structure and dynamic characteristics of the complex supply chain network were analyzed. The fact was found that the network is with general characteristics of the complex network, and with the characteristics of small-world network and scale-free network. A simulation experiment was made on the invulnerability of the supply chain network...

  9. Opinion control in complex networks

    Science.gov (United States)

    Masuda, Naoki

    2015-03-01

    In many political elections, the electorate appears to be a composite of partisan and independent voters. Given that partisans are not likely to convert to a different party, an important goal for a political party could be to mobilize independent voters toward the party with the help of strong leadership, mass media, partisans, and the effects of peer-to-peer influence. Based on the exact solution of classical voter model dynamics in the presence of perfectly partisan voters (i.e., zealots), we propose a computational method that uses pinning control strategy to maximize the share of a party in a social network of independent voters. The party, corresponding to the controller or zealots, optimizes the nodes to be controlled given the information about the connectivity of independent voters and the set of nodes that the opposing party controls. We show that controlling hubs is generally a good strategy, but the optimized strategy is even better. The superiority of the optimized strategy is particularly eminent when the independent voters are connected as directed (rather than undirected) networks.

  10. Non-equilibrium dynamics of language games on complex networks

    CERN Document Server

    Dall'Asta, L; Barrat, A; Loreto, V; Asta, Luca Dall'; Baronchelli, Andrea; Barrat, Alain; Loreto, Vittorio

    2006-01-01

    The Naming Game is a model of non-equilibrium dynamics for the self-organized emergence of a linguistic convention or a communication system in a population of agents with pairwise local interactions. We present an extensive study of its dynamics on complex networks, that can be considered as the most natural topological embedding for agents involved in language games and opinion dynamics. Except for some community structured networks on which metastable phases can be observed, agents playing the Naming Game always manage to reach a global consensus. This convergence is obtained after a time generically scaling with the population's size $N$ as $t\\_{conv} \\sim N^{1.4 \\pm 0.1}$, i.e. much faster than for agents embedded on regular lattices. Moreover, the memory capacity required by the system scales only linearly with its size. Particular attention is given to heterogenous networks, in which the dynamical activity pattern of a node depends on its degree. High degree nodes have a fundamental role, but require l...

  11. Bank networks and firm credit: an agent based model approach

    OpenAIRE

    Teixeira, Henrique Oliveira

    2016-01-01

    Starting from the idea that economic systems fall into complexity theory, where its many agents interact with each other without a central control and that these interactions are able to change the future behavior of the agents and the entire system, similar to a chaotic system we increase the model of Russo et al. (2014) to carry out three experiments focusing on the interaction between Banks and Firms in an artificial economy. The first experiment is relative to Relationship Banking wher...

  12. Complex Network for Solar Active Regions

    Science.gov (United States)

    Daei, Farhad; Safari, Hossein; Dadashi, Neda

    2017-08-01

    In this paper we developed a complex network of solar active regions (ARs) to study various local and global properties of the network. The values of the Hurst exponent (0.8-0.9) were evaluated by both the detrended fluctuation analysis and the rescaled range analysis applied on the time series of the AR numbers. The findings suggest that ARs can be considered as a system of self-organized criticality (SOC). We constructed a growing network based on locations, occurrence times, and the lifetimes of 4227 ARs recorded from 1999 January 1 to 2017 April 14. The behavior of the clustering coefficient shows that the AR network is not a random network. The logarithmic behavior of the length scale has the characteristics of a so-called small-world network. It is found that the probability distribution of the node degrees for undirected networks follows the power law with exponents of about 3.7-4.2. This indicates the scale-free nature of the AR network. The scale-free and small-world properties of the AR network confirm that the system of ARs forms a system of SOC. Our results show that the occurrence probability of flares (classified by GOES class C> 5, M, and X flares) in the position of the AR network hubs takes values greater than that obtained for other nodes.

  13. Complex networks repair strategies: Dynamic models

    Science.gov (United States)

    Fu, Chaoqi; Wang, Ying; Gao, Yangjun; Wang, Xiaoyang

    2017-09-01

    Network repair strategies are tactical methods that restore the efficiency of damaged networks; however, unreasonable repair strategies not only waste resources, they are also ineffective for network recovery. Most extant research on network repair focuses on static networks, but results and findings on static networks cannot be applied to evolutionary dynamic networks because, in dynamic models, complex network repair has completely different characteristics. For instance, repaired nodes face more severe challenges, and require strategic repair methods in order to have a significant effect. In this study, we propose the Shell Repair Strategy (SRS) to minimize the risk of secondary node failures due to the cascading effect. Our proposed method includes the identification of a set of vital nodes that have a significant impact on network repair and defense. Our identification of these vital nodes reduces the number of switching nodes that face the risk of secondary failures during the dynamic repair process. This is positively correlated with the size of the average degree and enhances network invulnerability.

  14. Assembly of complex plant–fungus networks

    Science.gov (United States)

    Toju, Hirokazu; Guimarães, Paulo R.; Olesen, Jens M.; Thompson, John N.

    2014-01-01

    Species in ecological communities build complex webs of interaction. Although revealing the architecture of these networks is fundamental to understanding ecological and evolutionary dynamics in nature, it has been difficult to characterize the structure of most species-rich ecological systems. By overcoming this limitation through next-generation sequencing technology, we herein uncover the network architecture of below-ground plant–fungus symbioses, which are ubiquitous to terrestrial ecosystems. The examined symbiotic network of a temperate forest in Japan includes 33 plant species and 387 functionally and phylogenetically diverse fungal taxa, and the overall network architecture differs fundamentally from that of other ecological networks. In contrast to results for other ecological networks and theoretical predictions for symbiotic networks, the plant–fungus network shows moderate or relatively low levels of interaction specialization and modularity and an unusual pattern of ‘nested’ network architecture. These results suggest that species-rich ecological networks are more architecturally diverse than previously recognized. PMID:25327887

  15. Router Agent Technology for Policy-Based Network Management

    Science.gov (United States)

    Chow, Edward T.; Sudhir, Gurusham; Chang, Hsin-Ping; James, Mark; Liu, Yih-Chiao J.; Chiang, Winston

    2011-01-01

    This innovation can be run as a standalone network application on any computer in a networked environment. This design can be configured to control one or more routers (one instance per router), and can also be configured to listen to a policy server over the network to receive new policies based on the policy- based network management technology. The Router Agent Technology transforms the received policies into suitable Access Control List syntax for the routers it is configured to control. It commits the newly generated access control lists to the routers and provides feedback regarding any errors that were faced. The innovation also automatically generates a time-stamped log file regarding all updates to the router it is configured to control. This technology, once installed on a local network computer and started, is autonomous because it has the capability to keep listening to new policies from the policy server, transforming those policies to router-compliant access lists, and committing those access lists to a specified interface on the specified router on the network with any error feedback regarding commitment process. The stand-alone application is named RouterAgent and is currently realized as a fully functional (version 1) implementation for the Windows operating system and for CISCO routers.

  16. Social networks as embedded complex adaptive systems.

    Science.gov (United States)

    Benham-Hutchins, Marge; Clancy, Thomas R

    2010-09-01

    As systems evolve over time, their natural tendency is to become increasingly more complex. Studies in the field of complex systems have generated new perspectives on management in social organizations such as hospitals. Much of this research appears as a natural extension of the cross-disciplinary field of systems theory. This is the 15th in a series of articles applying complex systems science to the traditional management concepts of planning, organizing, directing, coordinating, and controlling. In this article, the authors discuss healthcare social networks as a hierarchy of embedded complex adaptive systems. The authors further examine the use of social network analysis tools as a means to understand complex communication patterns and reduce medical errors.

  17. Complex Dynamics in Information Sharing Networks

    Science.gov (United States)

    Cronin, Bruce

    This study examines the roll-out of an electronic knowledge base in a medium-sized professional services firm over a six year period. The efficiency of such implementation is a key business problem in IT systems of this type. Data from usage logs provides the basis for analysis of the dynamic evolution of social networks around the depository during this time. The adoption pattern follows an "s-curve" and usage exhibits something of a power law distribution, both attributable to network effects, and network position is associated with organisational performance on a number of indicators. But periodicity in usage is evident and the usage distribution displays an exponential cut-off. Further analysis provides some evidence of mathematical complexity in the periodicity. Some implications of complex patterns in social network data for research and management are discussed. The study provides a case study demonstrating the utility of the broad methodological approach.

  18. Reinforcement learning agents providing advice in complex video games

    Science.gov (United States)

    Taylor, Matthew E.; Carboni, Nicholas; Fachantidis, Anestis; Vlahavas, Ioannis; Torrey, Lisa

    2014-01-01

    This article introduces a teacher-student framework for reinforcement learning, synthesising and extending material that appeared in conference proceedings [Torrey, L., & Taylor, M. E. (2013)]. Teaching on a budget: Agents advising agents in reinforcement learning. {Proceedings of the international conference on autonomous agents and multiagent systems}] and in a non-archival workshop paper [Carboni, N., &Taylor, M. E. (2013, May)]. Preliminary results for 1 vs. 1 tactics in StarCraft. {Proceedings of the adaptive and learning agents workshop (at AAMAS-13)}]. In this framework, a teacher agent instructs a student agent by suggesting actions the student should take as it learns. However, the teacher may only give such advice a limited number of times. We present several novel algorithms that teachers can use to budget their advice effectively, and we evaluate them in two complex video games: StarCraft and Pac-Man. Our results show that the same amount of advice, given at different moments, can have different effects on student learning, and that teachers can significantly affect student learning even when students use different learning methods and state representations.

  19. Controlling edge dynamics in complex networks

    OpenAIRE

    Nepusz, Tamás; Vicsek, Tamás

    2012-01-01

    The interaction of distinct units in physical, social, biological and technological systems naturally gives rise to complex network structures. Networks have constantly been in the focus of research for the last decade, with considerable advances in the description of their structural and dynamical properties. However, much less effort has been devoted to studying the controllability of the dynamics taking place on them. Here we introduce and evaluate a dynamical process defined on the edges ...

  20. 2D pattern evolution constrained by complex network dynamics

    CERN Document Server

    Rocha, L E C; Costa, Luciano da Fontoura; Rocha, Luis Enrique Correa da

    2006-01-01

    Complex networks have established themselves along the last years as being particularly suitable and flexible for representing and modeling several complex natural and human-made systems. At the same time in which the structural intricacies of such networks are being revealed and understood, efforts have also been directed at investigating how such connectivity properties define and constrain the dynamics of systems unfolding on such structures. However, lesser attention has been focused on hybrid systems, \\textit{i.e.} involving more than one type of network and/or dynamics. Because several real systems present such an organization (\\textit{e.g.} the dynamics of a disease coexisting with the dynamics of the immune system), it becomes important to address such hybrid systems. The current paper investigates a specific system involving a diffusive (linear and non-linear) dynamics taking place in a regular network while interacting with a complex network of defensive agents following Erd\\"os-R\\'enyi and Barab\\'a...

  1. Emergence of bimodality in controlling complex networks

    CERN Document Server

    Jia, Tao; Csóka, Endre; Pósfai, Márton; Slotine, Jean-Jacques; Barabási, Albert-László

    2015-01-01

    Our ability to control complex systems is a fundamental challenge of contemporary science. Recently introduced tools to identify the driver nodes, nodes through which we can achieve full control, predict the existence of multiple control configurations, prompting us to classify each node in a network based on their role in control. Accordingly a node is critical, intermittent or redundant if it acts as a driver node in all, some or none of the control configurations. Here we develop an analytical framework to identify the category of each node, leading to the discovery of two distinct control modes in complex systems: centralized vs distributed control. We predict the control mode for an arbitrary network and show that one can alter it through small structural perturbations. The uncovered bimodality has implications from network security to organizational research and offers new insights into the dynamics and control of complex systems.

  2. Complex network analysis of time series

    Science.gov (United States)

    Gao, Zhong-Ke; Small, Michael; Kurths, Jürgen

    2016-12-01

    Revealing complicated behaviors from time series constitutes a fundamental problem of continuing interest and it has attracted a great deal of attention from a wide variety of fields on account of its significant importance. The past decade has witnessed a rapid development of complex network studies, which allow to characterize many types of systems in nature and technology that contain a large number of components interacting with each other in a complicated manner. Recently, the complex network theory has been incorporated into the analysis of time series and fruitful achievements have been obtained. Complex network analysis of time series opens up new venues to address interdisciplinary challenges in climate dynamics, multiphase flow, brain functions, ECG dynamics, economics and traffic systems.

  3. Intentional risk management through complex networks analysis

    CERN Document Server

    Chapela, Victor; Moral, Santiago; Romance, Miguel

    2015-01-01

    This book combines game theory and complex networks to examine intentional technological risk through modeling. As information security risks are in constant evolution,  the methodologies and tools to manage them must evolve to an ever-changing environment. A formal global methodology is explained  in this book, which is able to analyze risks in cyber security based on complex network models and ideas extracted from the Nash equilibrium. A risk management methodology for IT critical infrastructures is introduced which provides guidance and analysis on decision making models and real situations. This model manages the risk of succumbing to a digital attack and assesses an attack from the following three variables: income obtained, expense needed to carry out an attack, and the potential consequences for an attack. Graduate students and researchers interested in cyber security, complex network applications and intentional risk will find this book useful as it is filled with a number of models, methodologies a...

  4. Networks of networks the last frontier of complexity

    CERN Document Server

    Scala, Antonio

    2014-01-01

    The present work is meant as a reference to provide an organic and comprehensive view of the most relevant results in the exciting new field of Networks of Networks (NetoNets). Seminal papers have recently been published posing the basis to study what happens when different networks interact, thus providing evidence for the emergence of new, unexpected behaviors and vulnerabilities. From those seminal works, the awareness on the importance understanding Networks of Networks (NetoNets) has spread to the entire community of Complexity Science. The reader will benefit from the experience of some of the most well-recognized leaders in this field. The contents have been aggregated under four headings; General Theory, Phenomenology, Applications and Risk Assessment. The reader will be impressed by the different applications of the general paradigm that span from physiology, to financial risk, to transports. We are currently making the first steps to reduce the distance between the language and the way of thinking o...

  5. Community detection by signaling on complex networks

    Science.gov (United States)

    Hu, Yanqing; Li, Menghui; Zhang, Peng; Fan, Ying; di, Zengru

    2008-07-01

    Based on a signaling process of complex networks, a method for identification of community structure is proposed. For a network with n nodes, every node is assumed to be a system which can send, receive, and record signals. Each node is taken as the initial signal source to excite the whole network one time. Then the source node is associated with an n -dimensional vector which records the effects of the signaling process. By this process, the topological relationship of nodes on the network could be transferred into a geometrical structure of vectors in n -dimensional Euclidean space. Then the best partition of groups is determined by F statistics and the final community structure is given by the K -means clustering method. This method can detect community structure both in unweighted and weighted networks. It has been applied to ad hoc networks and some real networks such as the Zachary karate club network and football team network. The results indicate that the algorithm based on the signaling process works well.

  6. Measuring multiple evolution mechanisms of complex networks.

    Science.gov (United States)

    Zhang, Qian-Ming; Xu, Xiao-Ke; Zhu, Yu-Xiao; Zhou, Tao

    2015-01-01

    Numerous concise models such as preferential attachment have been put forward to reveal the evolution mechanisms of real-world networks, which show that real-world networks are usually jointly driven by a hybrid mechanism of multiplex features instead of a single pure mechanism. To get an accurate simulation for real networks, some researchers proposed a few hybrid models by mixing multiple evolution mechanisms. Nevertheless, how a hybrid mechanism of multiplex features jointly influence the network evolution is not very clear. In this study, we introduce two methods (link prediction and likelihood analysis) to measure multiple evolution mechanisms of complex networks. Through tremendous experiments on artificial networks, which can be controlled to follow multiple mechanisms with different weights, we find the method based on likelihood analysis performs much better and gives very accurate estimations. At last, we apply this method to some real-world networks which are from different domains (including technology networks and social networks) and different countries (e.g., USA and China), to see how popularity and clustering co-evolve. We find most of them are affected by both popularity and clustering, but with quite different weights.

  7. Opinion control in complex networks

    CERN Document Server

    Masuda, Naoki

    2014-01-01

    In many instances of election, the electorate appears to be a composite of partisan and independent voters. Given that partisans are not likely to convert to a different party, a main goal for a party could be to mobilize independent voters toward the party with the help of strong leadership, mass media, partisans, and effects of peer-to-peer influence. Based on the exact solution of the classical voter model dynamics in the presence of perfectly partisan voters (i.e., zealots), we propose a computational method to maximize the share of the party in a social network of independent voters by pinning control strategy. The party, corresponding to the controller or zealots, optimizes the nodes to be controlled given the information about the connectivity of independent voters and the set of nodes that the opponent party controls. We show that controlling hubs is generally a good strategy, whereas the optimized strategy is even better. The superiority of the optimized strategy is particularly eminent when the inde...

  8. Micro-macro analysis of complex networks.

    Science.gov (United States)

    Marchiori, Massimo; Possamai, Lino

    2015-01-01

    Complex systems have attracted considerable interest because of their wide range of applications, and are often studied via a "classic" approach: study a specific system, find a complex network behind it, and analyze the corresponding properties. This simple methodology has produced a great deal of interesting results, but relies on an often implicit underlying assumption: the level of detail on which the system is observed. However, in many situations, physical or abstract, the level of detail can be one out of many, and might also depend on intrinsic limitations in viewing the data with a different level of abstraction or precision. So, a fundamental question arises: do properties of a network depend on its level of observability, or are they invariant? If there is a dependence, then an apparently correct network modeling could in fact just be a bad approximation of the true behavior of a complex system. In order to answer this question, we propose a novel micro-macro analysis of complex systems that quantitatively describes how the structure of complex networks varies as a function of the detail level. To this extent, we have developed a new telescopic algorithm that abstracts from the local properties of a system and reconstructs the original structure according to a fuzziness level. This way we can study what happens when passing from a fine level of detail ("micro") to a different scale level ("macro"), and analyze the corresponding behavior in this transition, obtaining a deeper spectrum analysis. The obtained results show that many important properties are not universally invariant with respect to the level of detail, but instead strongly depend on the specific level on which a network is observed. Therefore, caution should be taken in every situation where a complex network is considered, if its context allows for different levels of observability.

  9. Learning Latent Structure in Complex Networks

    DEFF Research Database (Denmark)

    Mørup, Morten; Hansen, Lars Kai

    as in the previous Bayesian approaches and in addition allows learning of node specific link properties similar to that in the modularity objective. We employ a new relaxation method for efficient inference in these generative models that allows us to learn the behavior of very large networks. We compare the link...... such as the Modularity, it has recently been shown that latent structure in complex networks is learnable by Bayesian generative link distribution models (Airoldi et al., 2008, Hofman and Wiggins, 2008). In this paper we propose a new generative model that allows representation of latent community structure...... prediction performance of the learning based approaches and other widely used link prediction approaches in 14 networks ranging from medium size to large networks with more than a million nodes. While link prediction is typically well above chance for all networks, we find that the learning based mixed...

  10. Size reduction of complex networks preserving modularity

    Energy Technology Data Exchange (ETDEWEB)

    Arenas, A.; Duch, J.; Fernandez, A.; Gomez, S.

    2008-12-24

    The ubiquity of modular structure in real-world complex networks is being the focus of attention in many trials to understand the interplay between network topology and functionality. The best approaches to the identification of modular structure are based on the optimization of a quality function known as modularity. However this optimization is a hard task provided that the computational complexity of the problem is in the NP-hard class. Here we propose an exact method for reducing the size of weighted (directed and undirected) complex networks while maintaining invariant its modularity. This size reduction allows the heuristic algorithms that optimize modularity for a better exploration of the modularity landscape. We compare the modularity obtained in several real complex-networks by using the Extremal Optimization algorithm, before and after the size reduction, showing the improvement obtained. We speculate that the proposed analytical size reduction could be extended to an exact coarse graining of the network in the scope of real-space renormalization.

  11. Complexity, dynamic cellular network, and tumorigenesis.

    Science.gov (United States)

    Waliszewski, P

    1997-01-01

    A holistic approach to tumorigenesis is proposed. The main element of the model is the existence of dynamic cellular network. This network comprises a molecular and an energetistic structure of a cell connected through the multidirectional flow of information. The interactions within dynamic cellular network are complex, stochastic, nonlinear, and also involve quantum effects. From this non-reductionist perspective, neither tumorigenesis can be limited to the genetic aspect, nor the initial event must be of molecular nature, nor mutations and epigenetic factors are mutually exclusive, nor a link between cause and effect can be established. Due to complexity, an unstable stationary state of dynamic cellular network rather than a group of unrelated genes determines the phenotype of normal and transformed cells. This implies relativity of tumor suppressor genes and oncogenes. A bifurcation point is defined as an unstable state of dynamic cellular network leading to the other phenotype-stationary state. In particular, the bifurcation point may be determined by a change of expression of a single gene. Then, the gene is called bifurcation point gene. The unstable stationary state facilitates the chaotic dynamics. This may result in a fractal dimension of both normal and tumor tissues. The co-existence of chaotic dynamics and complexity is the essence of cellular processes and shapes differentiation, morphogenesis, and tumorigenesis. In consequence, tumorigenesis is a complex, unpredictable process driven by the interplay between self-organisation and selection.

  12. Controlling congestion on complex networks: fairness, efficiency and network structure.

    Science.gov (United States)

    Buzna, Ľuboš; Carvalho, Rui

    2017-08-22

    We consider two elementary (max-flow and uniform-flow) and two realistic (max-min fairness and proportional fairness) congestion control schemes, and analyse how the algorithms and network structure affect throughput, the fairness of flow allocation, and the location of bottleneck edges. The more realistic proportional fairness and max-min fairness algorithms have similar throughput, but path flow allocations are more unequal in scale-free than in random regular networks. Scale-free networks have lower throughput than their random regular counterparts in the uniform-flow algorithm, which is favoured in the complex networks literature. We show, however, that this relation is reversed on all other congestion control algorithms for a region of the parameter space given by the degree exponent γ and average degree 〈k〉. Moreover, the uniform-flow algorithm severely underestimates the network throughput of congested networks, and a rich phenomenology of path flow allocations is only present in the more realistic α-fair family of algorithms. Finally, we show that the number of paths passing through an edge characterises the location of a wide range of bottleneck edges in these algorithms. Such identification of bottlenecks could provide a bridge between the two fields of complex networks and congestion control.

  13. Spatial price dynamics: From complex network perspective

    Science.gov (United States)

    Li, Y. L.; Bi, J. T.; Sun, H. J.

    2008-10-01

    The spatial price problem means that if the supply price plus the transportation cost is less than the demand price, there exists a trade. Thus, after an amount of exchange, the demand price will decrease. This process is continuous until an equilibrium state is obtained. However, how the trade network structure affects this process has received little attention. In this paper, we give a evolving model to describe the levels of spatial price on different complex network structures. The simulation results show that the network with shorter path length is sensitive to the variation of prices.

  14. Does network complexity help organize Babel's library?

    CERN Document Server

    Cárdenas, Juan Pablo; Benito, Rosa María; Losada, Juan Carlos

    2014-01-01

    In this work, we study properties of texts from the perspective of complex network theory. Words in given texts are linked by co-occurrence and transformed into networks, and we observe that these display topological properties common to other complex systems. However, there are some properties that seem to be exclusive to texts; many of these properties depend on the frequency of words in the text, while others seem to be strictly determined by the grammar. Precisely, these properties allow for a categorization of texts as either with a sense and others encoded or senseless.

  15. Defining nodes in complex brain networks

    Directory of Open Access Journals (Sweden)

    Matthew Lawrence Stanley

    2013-11-01

    Full Text Available Network science holds great promise for expanding our understanding of the human brain in health, disease, development, and aging. Network analyses are quickly becoming the method of choice for analyzing functional MRI data. However, many technical issues have yet to be confronted in order to optimize results. One particular issue that remains controversial in functional brain network analyses is the definition of a network node. In functional brain networks a node represents some predefined collection of brain tissue, and an edge measures the functional connectivity between pairs of nodes. The characteristics of a node, chosen by the researcher, vary considerably in the literature. This manuscript reviews the current state of the art based on published manuscripts and highlights the strengths and weaknesses of three main methods for defining nodes. Voxel-wise networks are constructed by assigning a node to each, equally sized brain area (voxel. The fMRI time-series recorded from each voxel is then used to create the functional network. Anatomical methods utilize atlases to define the nodes based on brain structure. The fMRI time-series from all voxels within the anatomical area are averaged and subsequently used to generate the network. Functional activation methods rely on data from traditional fMRI activation studies, often from databases, to identify network nodes. Such methods identify the peaks or centers of mass from activation maps to determine the location of the nodes. Small (~10-20 millimeter diameter spheres located at the coordinates of the activation foci are then applied to the data being used in the network analysis. The fMRI time-series from all voxels in the sphere are then averaged, and the resultant time series is used to generate the network. We attempt to clarify the discussion and move the study of complex brain networks forward. While the correct method to be used remains an open, possibly unsolvable question that

  16. Dyeing wastewater treatment with a complex adsorption-coagulation agent

    Institute of Scientific and Technical Information of China (English)

    ZHAO Qing-jian; LIU Jun-liang; ZHAO Qing-liang; LIU Zhi-gang

    2005-01-01

    To remove effectively the pollutants from printing and dyeing wastewater, a new complex adsorptioncoagulation agent was developed and employed in dyeing wastewater treatment. The experimental results showed that better removals of COD, turbidity and color could be efficiently realized under the operating conditions of mixing at 150 r/min, reacting within 5 min and dosing at 15 g/L and 20 g/L, respectively. Combined with the settled sludge, the agent could be recycled for further adsorption and coagulation within 10 times. Compared to the conventional coagulants, the newly-developed agent had such merits as suitability for wide pH range of wastewater, less sludge production, reutilization of the condensed sludge and low operation cost.

  17. Multi-agent based controller for islanding operation of active distribution networks with distributed generation

    DEFF Research Database (Denmark)

    Cha, Seung-Tae; Wu, Qiuwei; Østergaard, Jacob

    2011-01-01

    are important, and the overall network synchronism must be ensured in the islanded distribution system. In this paper, a multi-agent based controller has been proposed to stabilize the frequency and voltages of an active distribution system after it enters into the islanding operation mode. The modified IEEE 9......-bus system was used to investigate the dynamic and steady state performance of the active distribution system during islanding operation. Case studies have been carried out using the Real-Time Digital Simulator (RTDS) based simulation platform. Case study results show that the proposed multi-agent......The increasing amount of distributed generation (DG) in today’s highly complex restructured power networks gives more options for distribution system operators (DSOs) under contingency conditions. A low voltage distribution network with a large amount of DG can be operated as an islanded system...

  18. Structural and dynamical properties of complex networks

    Science.gov (United States)

    Ghoshal, Gourab

    dissertation with a game theory model on social networks that tracks the dynamical evolution of a group of interacting agents such as diplomats or political lobbyists seeking to rise to a position of influence, by balancing competing interests.

  19. Modeling and Simulation of Complex Network Attributes on Coordinating Large Multiagent System

    Science.gov (United States)

    Li, Xiang; Liu, Ming

    2014-01-01

    With the expansion of distributed multiagent systems, traditional coordination strategy becomes a severe bottleneck when the system scales up to hundreds of agents. The key challenge is that in typical large multiagent systems, sparsely distributed agents can only communicate directly with very few others and the network is typically modeled as an adaptive complex network. In this paper, we present simulation testbed CoordSim built to model the coordination of network centric multiagent systems. Based on the token-based strategy, the coordination can be built as a communication decision problem that agents make decisions to target communications and pass them over to the capable agents who will potentially benefit the team most. We have theoretically analyzed that the characters of complex network make a significant difference with both random and intelligent coordination strategies, which may contribute to future multiagent algorithm design. PMID:24955399

  20. A Multi-Agent System Architecture for Sensor Networks

    Science.gov (United States)

    Fuentes-Fernández, Rubén; Guijarro, María; Pajares, Gonzalo

    2009-01-01

    The design of the control systems for sensor networks presents important challenges. Besides the traditional problems about how to process the sensor data to obtain the target information, engineers need to consider additional aspects such as the heterogeneity and high number of sensors, and the flexibility of these networks regarding topologies and the sensors in them. Although there are partial approaches for resolving these issues, their integration relies on ad hoc solutions requiring important development efforts. In order to provide an effective approach for this integration, this paper proposes an architecture based on the multi-agent system paradigm with a clear separation of concerns. The architecture considers sensors as devices used by an upper layer of manager agents. These agents are able to communicate and negotiate services to achieve the required functionality. Activities are organized according to roles related with the different aspects to integrate, mainly sensor management, data processing, communication and adaptation to changes in the available devices and their capabilities. This organization largely isolates and decouples the data management from the changing network, while encouraging reuse of solutions. The use of the architecture is facilitated by a specific modelling language developed through metamodelling. A case study concerning a generic distributed system for fire fighting illustrates the approach and the comparison with related work. PMID:22303172

  1. A multi-agent system architecture for sensor networks.

    Science.gov (United States)

    Fuentes-Fernández, Rubén; Guijarro, María; Pajares, Gonzalo

    2009-01-01

    The design of the control systems for sensor networks presents important challenges. Besides the traditional problems about how to process the sensor data to obtain the target information, engineers need to consider additional aspects such as the heterogeneity and high number of sensors, and the flexibility of these networks regarding topologies and the sensors in them. Although there are partial approaches for resolving these issues, their integration relies on ad hoc solutions requiring important development efforts. In order to provide an effective approach for this integration, this paper proposes an architecture based on the multi-agent system paradigm with a clear separation of concerns. The architecture considers sensors as devices used by an upper layer of manager agents. These agents are able to communicate and negotiate services to achieve the required functionality. Activities are organized according to roles related with the different aspects to integrate, mainly sensor management, data processing, communication and adaptation to changes in the available devices and their capabilities. This organization largely isolates and decouples the data management from the changing network, while encouraging reuse of solutions. The use of the architecture is facilitated by a specific modelling language developed through metamodelling. A case study concerning a generic distributed system for fire fighting illustrates the approach and the comparison with related work.

  2. A Multi-Agent System Architecture for Sensor Networks

    Directory of Open Access Journals (Sweden)

    María Guijarro

    2009-12-01

    Full Text Available The design of the control systems for sensor networks presents important challenges. Besides the traditional problems about how to process the sensor data to obtain the target information, engineers need to consider additional aspects such as the heterogeneity and high number of sensors, and the flexibility of these networks regarding topologies and the sensors in them. Although there are partial approaches for resolving these issues, their integration relies on ad hoc solutions requiring important development efforts. In order to provide an effective approach for this integration, this paper proposes an architecture based on the multi-agent system paradigm with a clear separation of concerns. The architecture considers sensors as devices used by an upper layer of manager agents. These agents are able to communicate and negotiate services to achieve the required functionality. Activities are organized according to roles related with the different aspects to integrate, mainly sensor management, data processing, communication and adaptation to changes in the available devices and their capabilities. This organization largely isolates and decouples the data management from the changing network, while encouraging reuse of solutions. The use of the architecture is facilitated by a specific modelling language developed through metamodelling. A case study concerning a generic distributed system for fire fighting illustrates the approach and the comparison with related work.

  3. The complex network of musical tastes

    Science.gov (United States)

    Buldú, Javier M.; Cano, P.; Koppenberger, M.; Almendral, Juan A.; Boccaletti, S.

    2007-06-01

    We present an empirical study of the evolution of a social network constructed under the influence of musical tastes. The network is obtained thanks to the selfless effort of a broad community of users who share playlists of their favourite songs with other users. When two songs co-occur in a playlist a link is created between them, leading to a complex network where songs are the fundamental nodes. In this representation, songs in the same playlist could belong to different musical genres, but they are prone to be linked by a certain musical taste (e.g. if songs A and B co-occur in several playlists, an user who likes A will probably like also B). Indeed, playlist collections such as the one under study are the basic material that feeds some commercial music recommendation engines. Since playlists have an input date, we are able to evaluate the topology of this particular complex network from scratch, observing how its characteristic parameters evolve in time. We compare our results with those obtained from an artificial network defined by means of a null model. This comparison yields some insight on the evolution and structure of such a network, which could be used as ground data for the development of proper models. Finally, we gather information that can be useful for the development of music recommendation engines and give some hints about how top-hits appear.

  4. Realizing Wisdom Theory in Complex Learning Networks

    Science.gov (United States)

    Kok, Ayse

    2009-01-01

    The word "wisdom" is rarely seen in contemporary technology and learning discourse. This conceptual paper aims to provide some clear principles that answer the question: How can we establish wisdom in complex learning networks? By considering the nature of contemporary calls for wisdom the paper provides a metatheoretial framework to evaluate the…

  5. Simulating complex calcium-calcineurin signaling network

    NARCIS (Netherlands)

    Cui, J.; Kaandorp, J.A.

    2008-01-01

    Understanding of processes in which calcium signaling is involved is of fundamental importance in systems biology and has many applications in medicine. In this paper we have studied the particular case of the complex calcium-calcineurin-MCIP-NFAT signaling network in cardiac myocytes, the understan

  6. A City Is a Complex Network

    CERN Document Server

    Jiang, Bin

    2015-01-01

    A city is not a tree but a semi-lattice. To use a more fashionable term, a city is a complex network. The complex network constitutes a unique topological perspective on cities and enables us to better understand the kind of problem a city is. The topological perspective differentiates it from the perspectives of Euclidean geometry and Gaussian statistics that deal with essentially regular shapes and more or less similar things. Many urban theories, such as the Central Place Theory, Zipf's Law, the Image of the City, and the Theory of Centers can be interpreted from the point of view of complex networks. A livable city consists of far more small things than large ones, and their shapes tend to be irregular and rough. This chapter illustrates the complex network view and argues that we must abandon the kind of thinking guided by Euclidean geometry and Gaussian statistics, and instead adopt fractal geometry, power-law statistics, and Alexander's living geometry to develop sustainable cities. Keywords: Scaling, ...

  7. The Kuramoto model in complex networks

    Science.gov (United States)

    Rodrigues, Francisco A.; Peron, Thomas K. DM.; Ji, Peng; Kurths, Jürgen

    2016-01-01

    Synchronization of an ensemble of oscillators is an emergent phenomenon present in several complex systems, ranging from social and physical to biological and technological systems. The most successful approach to describe how coherent behavior emerges in these complex systems is given by the paradigmatic Kuramoto model. This model has been traditionally studied in complete graphs. However, besides being intrinsically dynamical, complex systems present very heterogeneous structure, which can be represented as complex networks. This report is dedicated to review main contributions in the field of synchronization in networks of Kuramoto oscillators. In particular, we provide an overview of the impact of network patterns on the local and global dynamics of coupled phase oscillators. We cover many relevant topics, which encompass a description of the most used analytical approaches and the analysis of several numerical results. Furthermore, we discuss recent developments on variations of the Kuramoto model in networks, including the presence of noise and inertia. The rich potential for applications is discussed for special fields in engineering, neuroscience, physics and Earth science. Finally, we conclude by discussing problems that remain open after the last decade of intensive research on the Kuramoto model and point out some promising directions for future research.

  8. Phase transitions in Pareto optimal complex networks

    CERN Document Server

    Seoane, Luís F

    2015-01-01

    The organization of interactions in complex systems can be described by networks connecting different units. These graphs are useful representations of the local and global complexity of the underlying systems. The origin of their topological structure can be diverse, resulting from different mechanisms including multiplicative processes and optimization. In spatial networks or in graphs where cost constraints are at work, as it occurs in a plethora of situations from power grids to the wiring of neurons in the brain, optimization plays an important part in shaping their organization. In this paper we study network designs resulting from a Pareto optimization process, where different simultaneous constraints are the targets of selection. We analyze three variations on a problem finding phase transitions of different kinds. Distinct phases are associated to different arrangements of the connections; but the need of drastic topological changes does not determine the presence, nor the nature of the phase transit...

  9. 6th Workshop on Complex Networks

    CERN Document Server

    Simini, Filippo; Uzzo, Stephen; Wang, Dashun

    2015-01-01

    Elucidating the spatial and temporal dynamics of how things connect has become one of the most important areas of research in the 21st century. Network science now pervades nearly every science domain, resulting in new discoveries in a host of dynamic social and natural systems, including: how neurons connect and communicate in the brain, how information percolates within and among social networks, the evolution of science research through co-authorship networks, the spread of epidemics, and many other complex phenomena. Over the past decade, advances in computational power have put the tools of network analysis in the hands of increasing numbers of scientists, enabling more explorations of our world than ever before possible. Information science, social sciences, systems biology, ecosystems ecology, neuroscience and physics all benefit from this movement, which combines graph theory with data sciences to develop and validate theories about the world around us. This book brings together cutting-edge research ...

  10. Emergence of fractal scaling in complex networks

    Science.gov (United States)

    Wei, Zong-Wen; Wang, Bing-Hong

    2016-09-01

    Some real-world networks are shown to be fractal or self-similar. It is widespread that such a phenomenon originates from the repulsion between hubs or disassortativity. Here we show that this common belief fails to capture the causality. Our key insight to address it is to pinpoint links critical to fractality. Those links with small edge betweenness centrality (BC) constitute a special architecture called fractal reference system, which gives birth to the fractal structure of those reported networks. In contrast, a small amount of links with high BC enable small-world effects, hiding the intrinsic fractality. With enough of such links removed, fractal scaling spontaneously arises from nonfractal networks. Our results provide a multiple-scale view on the structure and dynamics and place fractality as a generic organizing principle of complex networks on a firmer ground.

  11. The success of complex networks at criticality

    CERN Document Server

    Hernandez-Urbina, Victor; Herrmann, J Michael

    2015-01-01

    In spiking neural networks an action potential could in principle trigger subsequent spikes in the neighbourhood of the initial neuron. A successful spike is that which trigger subsequent spikes giving rise to cascading behaviour within the system. In this study we introduce a metric to assess the success of spikes emitted by integrate-and-fire neurons arranged in complex topologies and whose collective behaviour is undergoing a phase transition that is identified by neuronal avalanches that become clusters of activation whose distribution of sizes can be approximated by a power-law. In numerical simulations we report that scale-free networks with the small-world property is the structure in which neurons possess more successful spikes. As well, we conclude both analytically and in numerical simulations that fully-connected networks are structures in which neurons perform worse. Additionally, we study how the small-world property affects spiking behaviour and its success in scale-free networks.

  12. Hierarchical community structure in complex (social) networks

    CERN Document Server

    Massaro, Emanuele

    2014-01-01

    The investigation of community structure in networks is a task of great importance in many disciplines, namely physics, sociology, biology and computer science where systems are often represented as graphs. One of the challenges is to find local communities from a local viewpoint in a graph without global information in order to reproduce the subjective hierarchical vision for each vertex. In this paper we present the improvement of an information dynamics algorithm in which the label propagation of nodes is based on the Markovian flow of information in the network under cognitive-inspired constraints \\cite{Massaro2012}. In this framework we have introduced two more complex heuristics that allow the algorithm to detect the multi-resolution hierarchical community structure of networks from a source vertex or communities adopting fixed values of model's parameters. Experimental results show that the proposed methods are efficient and well-behaved in both real-world and synthetic networks.

  13. Community Detection in Quantum Complex Networks

    CERN Document Server

    Faccin, Mauro; Johnson, Tomi; Biamonte, Jacob; Bergholm, Ville

    2013-01-01

    Determining community structure in interacting systems, ranging from technological to social, from biological to chemical, is a topic of central importance in the study of networks. Extending this concept to apply to quantum systems represents an open challenge and a crucial missing component towards a theory of complex networks based on quantum mechanics. Here we accomplish this goal by introducing methods for identifying the community structure of a network governed by quantum dynamics. To illustrate our approach we turn to a host of examples, including a naturally occurring light-harvesting network, where from first principles we determine a consistent community structure. In certain regimes the communities we determine agree with a partitioning currently done by hand in the quantum chemistry literature. In other regimes, we uncover a new community structure. The difference stems from defining measures to determine distances between nodes in quantum systems, and then determining optimal modularity. Merging...

  14. Transient Synchronization in Complex Neuronal Networks

    CERN Document Server

    Costa, Luciano da Fontoura

    2008-01-01

    Transient synchronization in complex neuronal networks as a consequence of activation-conserved dynamics induced by having sources placed at specific neurons is investigated. The basic integrate-and-fire neuron is adopted, and the dynamics is estimated computationally so as to obtain the activation at each node along each instant of time. The dynamics is implemented so as to conserve the total activation entering the system, which is a distinctive feature of the current work. The synchronization of the activation of the network is then quantified along time in terms of its normalized instantaneous entropy. The potential of such concepts and measurements is explored with respect to 6 theoretical models, as well as for the neuronal network of \\emph{C. elegans}. A series of interesting results are obtained and discussed, including the fact that all models led to a transient period of synchronization, whose specific features depend heavily on the topological features of the networks.

  15. Disease Surveillance on Complex Social Networks.

    Directory of Open Access Journals (Sweden)

    Jose L Herrera

    2016-07-01

    Full Text Available As infectious disease surveillance systems expand to include digital, crowd-sourced, and social network data, public health agencies are gaining unprecedented access to high-resolution data and have an opportunity to selectively monitor informative individuals. Contact networks, which are the webs of interaction through which diseases spread, determine whether and when individuals become infected, and thus who might serve as early and accurate surveillance sensors. Here, we evaluate three strategies for selecting sensors-sampling the most connected, random, and friends of random individuals-in three complex social networks-a simple scale-free network, an empirical Venezuelan college student network, and an empirical Montreal wireless hotspot usage network. Across five different surveillance goals-early and accurate detection of epidemic emergence and peak, and general situational awareness-we find that the optimal choice of sensors depends on the public health goal, the underlying network and the reproduction number of the disease (R0. For diseases with a low R0, the most connected individuals provide the earliest and most accurate information about both the onset and peak of an outbreak. However, identifying network hubs is often impractical, and they can be misleading if monitored for general situational awareness, if the underlying network has significant community structure, or if R0 is high or unknown. Taking a theoretical approach, we also derive the optimal surveillance system for early outbreak detection but find that real-world identification of such sensors would be nearly impossible. By contrast, the friends-of-random strategy offers a more practical and robust alternative. It can be readily implemented without prior knowledge of the network, and by identifying sensors with higher than average, but not the highest, epidemiological risk, it provides reasonably early and accurate information.

  16. The Dynamics of Coalition Formation on Complex Networks

    Science.gov (United States)

    Auer, S.; Heitzig, J.; Kornek, U.; Schöll, E.; Kurths, J.

    2015-08-01

    Complex networks describe the structure of many socio-economic systems. However, in studies of decision-making processes the evolution of the underlying social relations are disregarded. In this report, we aim to understand the formation of self-organizing domains of cooperation (“coalitions”) on an acquaintance network. We include both the network’s influence on the formation of coalitions and vice versa how the network adapts to the current coalition structure, thus forming a social feedback loop. We increase complexity from simple opinion adaptation processes studied in earlier research to more complex decision-making determined by costs and benefits, and from bilateral to multilateral cooperation. We show how phase transitions emerge from such coevolutionary dynamics, which can be interpreted as processes of great transformations. If the network adaptation rate is high, the social dynamics prevent the formation of a grand coalition and therefore full cooperation. We find some empirical support for our main results: Our model develops a bimodal coalition size distribution over time similar to those found in social structures. Our detection and distinguishing of phase transitions may be exemplary for other models of socio-economic systems with low agent numbers and therefore strong finite-size effects.

  17. Kinetic analysis of complex metabolic networks

    Energy Technology Data Exchange (ETDEWEB)

    Stephanopoulos, G. [MIT, Cambridge, MA (United States)

    1996-12-31

    A new methodology is presented for the analysis of complex metabolic networks with the goal of metabolite overproduction. The objective is to locate a small number of reaction steps in a network that have maximum impact on network flux amplification and whose rate can also be increased without functional network derangement. This method extends the concepts of Metabolic Control Analysis to groups of reactions and offers the means for calculating group control coefficients as measures of the control exercised by groups of reactions on the overall network fluxes and intracellular metabolite pools. It is further demonstrated that the optimal strategy for the effective increase of network fluxes, while maintaining an uninterrupted supply of intermediate metabolites, is through the coordinated amplification of multiple (as opposed to a single) reaction steps. Satisfying this requirement invokes the concept of the concentration control to coefficient, which emerges as a critical parameter in the identification of feasible enzymatic modifications with maximal impact on the network flux. A case study of aromatic aminoacid production is provided to illustrate these concepts.

  18. Factors Determining Nestedness in Complex Networks

    Science.gov (United States)

    Jonhson, Samuel; Domínguez-García, Virginia; Muñoz, Miguel A.

    2013-01-01

    Understanding the causes and effects of network structural features is a key task in deciphering complex systems. In this context, the property of network nestedness has aroused a fair amount of interest as regards ecological networks. Indeed, Bastolla et al. introduced a simple measure of network nestedness which opened the door to analytical understanding, allowing them to conclude that biodiversity is strongly enhanced in highly nested mutualistic networks. Here, we suggest a slightly refined version of such a measure of nestedness and study how it is influenced by the most basic structural properties of networks, such as degree distribution and degree-degree correlations (i.e. assortativity). We find that most of the empirically found nestedness stems from heterogeneity in the degree distribution. Once such an influence has been discounted – as a second factor – we find that nestedness is strongly correlated with disassortativity and hence – as random networks have been recently found to be naturally disassortative – they also tend to be naturally nested just as the result of chance. PMID:24069264

  19. Load Balancing on Open Networks: A Mobile Agent Approach

    Directory of Open Access Journals (Sweden)

    R. B. Patel

    2006-01-01

    Full Text Available In order to disperse the load on a Web server, generally the server cluster is configured to distribute access requests, or mirror servers are distributed geographically on different networks. Use of the Internet and the World-Wide-Web (WWW has become widespread in recent years and mobile agent technology has proliferated at an equally rapid rate to evenly distribute the requests to web servers through load balancing. There are various loads balancing policies came into picture. Primitive one is Message Passing Interface (MPI. Its wide availability and portability make it an attractive choice, however the communication requirements are sometimes inconventior and inefficient when implementing the primitives provided by MPI. Mobile agent (MA based approach have the merits of high flexibility, efficiency, low network traffic, less communication latency as well as highly asynchronous. In this study we present dynamic load balancing using mobile agent technology in which when a node is overloaded, task migrates to less utilized nodes so as to share the workload. However, the decision of which nodes receive migrating task is made in real-time by design and implementation of a framework called Platform for Load balancing (PLB. It is implemented on PMADE (A Platform for Mobile Agent Distribution and Execution. PLB integrated web servers can dispatch MAs to retrieve load information and accomplish load redistribution on all servers. The performance evaluation demonstrates that the PLB framework provides a foundation to develop efficient load balancing schemes on wide range of web server systems from cluster to open network and the results of a comparison of PLB, with some existing ones, is also reported.

  20. Other-regarding preference and the evolutionary prisoner’s dilemma on complex networks

    Science.gov (United States)

    Bo, Xianyu

    2010-03-01

    Prevailing models of the evolutionary prisoner’s game on networks always assume that agents are pursuing their own profit maximization. But the results from experimental games show that many agents have other-regarding preference. In this paper, we study the emergence of cooperation from the prisoner’s dilemma game on complex networks while some agents exhibit other-regarding preference such as inequality aversion, envious and guilty emotions. Contrary to common ideas, the simulation results show that the existence of inequality aversion agents does not promote cooperation emergence on a BA (Barabási and Albert) scale-free network in most situations. If the defection attraction is big and agents exhibit strong preference for inequality aversion, the frequency of cooperators will be lower than in situations where no inequality aversion agents exist. In some cases, the existence of the inequality agents will even induce the frequency of cooperators to zero, a feature which is not observed in previous research on the prisoner’s dilemma game when the underlying interaction topology is a BA scale-free network. This means that if an agent cares about equality too much, it will be difficult for cooperation to emerge and the frequency of cooperators will be low on BA networks. The research on the effect of envy or guilty emotions on the emergence of cooperation in the prisoner’s dilemma game on BA networks obtains similar results, though some differences exist. However, simulation results on a WS (Watts and Strogatz) small-world network display another scenario. If agents care about the inequality of agents very much, the WS network favors cooperation emergence in the prisoners’ dilemma game when other-regarding agents exist. If the agent weight on other-regarding is lowered, the cooperation frequencies emerging on a WS network are not much different from those in situations without other-regarding agents, although the frequency of cooperators is lower than

  1. Multi-agent-based bio-network for systems biology: protein-protein interaction network as an example.

    Science.gov (United States)

    Ren, Li-Hong; Ding, Yong-Sheng; Shen, Yi-Zhen; Zhang, Xiang-Feng

    2008-10-01

    Recently, a collective effort from multiple research areas has been made to understand biological systems at the system level. This research requires the ability to simulate particular biological systems as cells, organs, organisms, and communities. In this paper, a novel bio-network simulation platform is proposed for system biology studies by combining agent approaches. We consider a biological system as a set of active computational components interacting with each other and with an external environment. Then, we propose a bio-network platform for simulating the behaviors of biological systems and modelling them in terms of bio-entities and society-entities. As a demonstration, we discuss how a protein-protein interaction (PPI) network can be seen as a society of autonomous interactive components. From interactions among small PPI networks, a large PPI network can emerge that has a remarkable ability to accomplish a complex function or task. We also simulate the evolution of the PPI networks by using the bio-operators of the bio-entities. Based on the proposed approach, various simulators with different functions can be embedded in the simulation platform, and further research can be done from design to development, including complexity validation of the biological system.

  2. Dynamic analysis of biochemical network using complex network method

    Directory of Open Access Journals (Sweden)

    Wang Shuqiang

    2015-01-01

    Full Text Available In this study, the stochastic biochemical reaction model is proposed based on the law of mass action and complex network theory. The dynamics of biochemical reaction system is presented as a set of non-linear differential equations and analyzed at the molecular-scale. Given the initial state and the evolution rules of the biochemical reaction system, the system can achieve homeostasis. Compared with random graph, the biochemical reaction network has larger information capacity and is more efficient in information transmission. This is consistent with theory of evolution.

  3. Process and data fragmentation-oriented enterprise network integration with collaboration modelling and collaboration agents

    Science.gov (United States)

    Li, Qing; Wang, Ze-yuan; Cao, Zhi-chao; Du, Rui-yang; Luo, Hao

    2015-08-01

    With the process of globalisation and the development of management models and information technology, enterprise cooperation and collaboration has developed from intra-enterprise integration, outsourcing and inter-enterprise integration, and supply chain management, to virtual enterprises and enterprise networks. Some midfielder enterprises begin to serve for different supply chains. Therefore, they combine related supply chains into a complex enterprise network. The main challenges for enterprise network's integration and collaboration are business process and data fragmentation beyond organisational boundaries. This paper reviews the requirements of enterprise network's integration and collaboration, as well as the development of new information technologies. Based on service-oriented architecture (SOA), collaboration modelling and collaboration agents are introduced to solve problems of collaborative management for service convergence under the condition of process and data fragmentation. A model-driven methodology is developed to design and deploy the integrating framework. An industrial experiment is designed and implemented to illustrate the usage of developed technologies in this paper.

  4. COMPLEX NETWORKS IN CLIMATE SCIENCE: PROGRESS, OPPORTUNITIES AND CHALLENGES

    Data.gov (United States)

    National Aeronautics and Space Administration — COMPLEX NETWORKS IN CLIMATE SCIENCE: PROGRESS, OPPORTUNITIES AND CHALLENGES KARSTEN STEINHAEUSER, NITESH V. CHAWLA, AND AUROOP R. GANGULY Abstract. Networks have...

  5. Community Detection in Quantum Complex Networks

    Science.gov (United States)

    Faccin, Mauro; Migdał, Piotr; Johnson, Tomi H.; Bergholm, Ville; Biamonte, Jacob D.

    2014-10-01

    Determining community structure is a central topic in the study of complex networks, be it technological, social, biological or chemical, static or in interacting systems. In this paper, we extend the concept of community detection from classical to quantum systems—a crucial missing component of a theory of complex networks based on quantum mechanics. We demonstrate that certain quantum mechanical effects cannot be captured using current classical complex network tools and provide new methods that overcome these problems. Our approaches are based on defining closeness measures between nodes, and then maximizing modularity with hierarchical clustering. Our closeness functions are based on quantum transport probability and state fidelity, two important quantities in quantum information theory. To illustrate the effectiveness of our approach in detecting community structure in quantum systems, we provide several examples, including a naturally occurring light-harvesting complex, LHCII. The prediction of our simplest algorithm, semiclassical in nature, mostly agrees with a proposed partitioning for the LHCII found in quantum chemistry literature, whereas our fully quantum treatment of the problem uncovers a new, consistent, and appropriately quantum community structure.

  6. Benford’s Distribution in Complex Networks

    Science.gov (United States)

    Morzy, Mikołaj; Kajdanowicz, Tomasz; Szymański, Bolesław K.

    2016-10-01

    Many collections of numbers do not have a uniform distribution of the leading digit, but conform to a very particular pattern known as Benford’s distribution. This distribution has been found in numerous areas such as accounting data, voting registers, census data, and even in natural phenomena. Recently it has been reported that Benford’s law applies to online social networks. Here we introduce a set of rigorous tests for adherence to Benford’s law and apply it to verification of this claim, extending the scope of the experiment to various complex networks and to artificial networks created by several popular generative models. Our findings are that neither for real nor for artificial networks there is sufficient evidence for common conformity of network structural properties with Benford’s distribution. We find very weak evidence suggesting that three measures, degree centrality, betweenness centrality and local clustering coefficient, could adhere to Benford’s law for scalefree networks but only for very narrow range of their parameters.

  7. Robust Multiobjective Controllability of Complex Neuronal Networks.

    Science.gov (United States)

    Tang, Yang; Gao, Huijun; Du, Wei; Lu, Jianquan; Vasilakos, Athanasios V; Kurths, Jurgen

    2016-01-01

    This paper addresses robust multiobjective identification of driver nodes in the neuronal network of a cat's brain, in which uncertainties in determination of driver nodes and control gains are considered. A framework for robust multiobjective controllability is proposed by introducing interval uncertainties and optimization algorithms. By appropriate definitions of robust multiobjective controllability, a robust nondominated sorting adaptive differential evolution (NSJaDE) is presented by means of the nondominated sorting mechanism and the adaptive differential evolution (JaDE). The simulation experimental results illustrate the satisfactory performance of NSJaDE for robust multiobjective controllability, in comparison with six statistical methods and two multiobjective evolutionary algorithms (MOEAs): nondominated sorting genetic algorithms II (NSGA-II) and nondominated sorting composite differential evolution. It is revealed that the existence of uncertainties in choosing driver nodes and designing control gains heavily affects the controllability of neuronal networks. We also unveil that driver nodes play a more drastic role than control gains in robust controllability. The developed NSJaDE and obtained results will shed light on the understanding of robustness in controlling realistic complex networks such as transportation networks, power grid networks, biological networks, etc.

  8. Control of Synchronization Regimes in Networks of Mobile Interacting Agents

    Science.gov (United States)

    Perez-Diaz, Fernando; Zillmer, Ruediger; Groß, Roderich

    2017-05-01

    We investigate synchronization in a population of mobile pulse-coupled agents with a view towards implementations in swarm-robotics systems and mobile sensor networks. Previous theoretical approaches dealt with range and nearest-neighbor interactions. In the latter case, a synchronization-hindering regime for intermediate agent mobility is found. We investigate the robustness of this intermediate regime under practical scenarios. We show that synchronization in the intermediate regime can be predicted by means of a suitable metric of the phase response curve. Furthermore, we study more-realistic K -nearest-neighbor and cone-of-vision interactions, showing that it is possible to control the extent of the synchronization-hindering region by appropriately tuning the size of the neighborhood. To assess the effect of noise, we analyze the propagation of perturbations over the network and draw an analogy between the response in the hindering regime and stable chaos. Our findings reveal the conditions for the control of clock or activity synchronization of agents with intermediate mobility. In addition, the emergence of the intermediate regime is validated experimentally using a swarm of physical robots interacting with cone-of-vision interactions.

  9. Neural network analysis of terahertz spectra of explosives and bio-agents

    Science.gov (United States)

    Oliveira, Felipe; Barat, Robert; Shulkin, Brian; Federici, John F.; Gary, Dale; Zimdars, David A.

    2003-08-01

    A proposed, non-invasive, means to detect and characterize concealed biological and explosive agents in near real-time with a wide field-of-view uses spatial imaging of their characteristic transmission or reflectivity wavelength spectrum in the Terahertz (THz) electro-magnetic range (0.1-3 THz). Neural network analyses of the THz spectra and images will provide the specificity of agent detection and reduce the frequency of false alarms. Artificial neural networks are mathematical devices for modeling complex, non-linear functionalities. The key to a successful neural network is adequate training with known input-output data. Important challenges in the research include identification of the preferred network structure (e.g. multi-layer perceptron), number of hidden nodes, training algorithm (e.g. back propagation), and determination of what type of THz spectral image pre-processing is needed prior to application of the network. Detector array images containing both spectral and spatial information are analyzed with the aid of the Neurosolutions(TM) commercial neural network software package.

  10. Defining nodes in complex brain networks.

    Science.gov (United States)

    Stanley, Matthew L; Moussa, Malaak N; Paolini, Brielle M; Lyday, Robert G; Burdette, Jonathan H; Laurienti, Paul J

    2013-11-22

    Network science holds great promise for expanding our understanding of the human brain in health, disease, development, and aging. Network analyses are quickly becoming the method of choice for analyzing functional MRI data. However, many technical issues have yet to be confronted in order to optimize results. One particular issue that remains controversial in functional brain network analyses is the definition of a network node. In functional brain networks a node represents some predefined collection of brain tissue, and an edge measures the functional connectivity between pairs of nodes. The characteristics of a node, chosen by the researcher, vary considerably in the literature. This manuscript reviews the current state of the art based on published manuscripts and highlights the strengths and weaknesses of three main methods for defining nodes. Voxel-wise networks are constructed by assigning a node to each, equally sized brain area (voxel). The fMRI time-series recorded from each voxel is then used to create the functional network. Anatomical methods utilize atlases to define the nodes based on brain structure. The fMRI time-series from all voxels within the anatomical area are averaged and subsequently used to generate the network. Functional activation methods rely on data from traditional fMRI activation studies, often from databases, to identify network nodes. Such methods identify the peaks or centers of mass from activation maps to determine the location of the nodes. Small (~10-20 millimeter diameter) spheres located at the coordinates of the activation foci are then applied to the data being used in the network analysis. The fMRI time-series from all voxels in the sphere are then averaged, and the resultant time series is used to generate the network. We attempt to clarify the discussion and move the study of complex brain networks forward. While the "correct" method to be used remains an open, possibly unsolvable question that deserves extensive

  11. Therapeutic treatment of Alzheimer's disease using metal complexing agents.

    Science.gov (United States)

    Price, Katherine A; Crouch, Peter J; White, Anthony R

    2007-11-01

    Alzheimer's disease (AD) is a progressive neurodegenerative disorder characterized by deposition of extracellular amyloid plaques, formation of intracellular neurofibrillary tangles and neuronal dysfunction in the brain. A growing body of evidence indicates a central role for biometals such as copper in many critical aspects of AD. The amyloid beta (Abeta) peptide and its parental molecule, the amyloid precursor protein (APP) both modulate Cu and Zn metabolism in the brain. Therefore, aberrant changes to APP or Abeta metabolism could potentially alter biometal homoestasis in AD, leading to increased free radical production and neuronal oxidative stress. Modulation of metal bioavailability in the brain has been proposed as a potential therapeutic strategy for treatment of AD patients. The lipid permeable metal complexing agent, clioquinol (CQ), has shown promising results in animal models of AD and in small clinical trials involving AD patients. Moreover, a new generation of metal-ligand based therapeutics is currently under development. Patents now cover the generation of novel metal ligand structures designed to modulate metal binding to Abeta and quench metal-mediated free radical generation. However, the mechanism by which CQ and other metal complexing agents slows cognitive decline in AD animal models and patients is unknown. Increasing evidence suggests that ligand-mediated redistribution of metals at a cellular level in the brain may be important. Further research will be necessary to fully understand the complex pathways associated with efficacious metal-based pharmaceuticals for treatment of AD.

  12. Research on Evolutionary Mechanism of Agile Supply Chain Network via Complex Network Theory

    Directory of Open Access Journals (Sweden)

    Nai-Ru Xu

    2016-01-01

    Full Text Available The paper establishes the evolutionary mechanism model of agile supply chain network by means of complex network theory which can be used to describe the growth process of the agile supply chain network and analyze the complexity of the agile supply chain network. After introducing the process and the suitability of taking complex network theory into supply chain network research, the paper applies complex network theory into the agile supply chain network research, analyzes the complexity of agile supply chain network, presents the evolutionary mechanism of agile supply chain network based on complex network theory, and uses Matlab to simulate degree distribution, average path length, clustering coefficient, and node betweenness. Simulation results show that the evolution result displays the scale-free property. It lays the foundations of further research on agile supply chain network based on complex network theory.

  13. Complex networks analysis of obstructive nephropathy data

    Science.gov (United States)

    Zanin, M.; Boccaletti, S.

    2011-09-01

    Congenital obstructive nephropathy (ON) is one of the most frequent and complex diseases affecting children, characterized by an abnormal flux of the urine, due to a partial or complete obstruction of the urinary tract; as a consequence, urine may accumulate in the kidney and disturb the normal operation of the organ. Despite important advances, pathological mechanisms are not yet fully understood. In this contribution, the topology of complex networks, based on vectors of features of control and ON subjects, is related with the severity of the pathology. Nodes in these networks represent genetic and metabolic profiles, while connections between them indicate an abnormal relation between their expressions. Resulting topologies allow discriminating ON subjects and detecting which genetic or metabolic elements are responsible for the malfunction.

  14. The complex channel networks of bone structure

    CERN Document Server

    Costa, Luciano da Fontoura; Beletti, Marcelo E

    2006-01-01

    Bone structure in mammals involves a complex network of channels (Havers and Volkmann channels) required to nourish the bone marrow cells. This work describes how three-dimensional reconstructions of such systems can be obtained and represented in terms of complex networks. Three important findings are reported: (i) the fact that the channel branching density resembles a power law implies the existence of distribution hubs; (ii) the conditional node degree density indicates a clear tendency of connection between nodes with degrees 2 and 4; and (iii) the application of the recently introduced concept of hierarchical clustering coefficient allows the identification of typical scales of channel redistribution. A series of important biological insights is drawn and discussed

  15. Preferential urn model and nongrowing complex networks.

    Science.gov (United States)

    Ohkubo, Jun; Yasuda, Muneki; Tanaka, Kazuyuki

    2005-12-01

    A preferential urn model, which is based on the concept "the rich get richer," is proposed. From a relationship between a nongrowing model for complex networks and the preferential urn model in regard to degree distributions, it is revealed that a fitness parameter in the nongrowing model is interpreted as an inverse local temperature in the preferential urn model. Furthermore, it is clarified that the preferential urn model with randomness generates a fat-tailed occupation distribution; the concept of the local temperature enables us to understand the fat-tailed occupation distribution intuitively. Since the preferential urn model is a simple stochastic model, it can be applied to research on not only the nongrowing complex networks, but also many other fields such as econophysics and social sciences.

  16. Mobile Agent-Based Directed Diffusion in Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Victor C. M. Leung

    2007-01-01

    Full Text Available In the environments where the source nodes are close to one another and generate a lot of sensory data traffic with redundancy, transmitting all sensory data by individual nodes not only wastes the scarce wireless bandwidth, but also consumes a lot of battery energy. Instead of each source node sending sensory data to its sink for aggregation (the so-called client/server computing, Qi et al. in 2003 proposed a mobile agent (MA-based distributed sensor network (MADSN for collaborative signal and information processing, which considerably reduces the sensory data traffic and query latency as well. However, MADSN is based on the assumption that the operation of mobile agent is only carried out within one hop in a clustering-based architecture. This paper considers MA in multihop environments and adopts directed diffusion (DD to dispatch MA. The gradient in DD gives a hint to efficiently forward the MA among target sensors. The mobile agent paradigm in combination with the DD framework is dubbed mobile agent-based directed diffusion (MADD. With appropriate parameters set, extensive simulation shows that MADD exhibits better performance than original DD (in the client/server paradigm in terms of packet delivery ratio, energy consumption, and end-to-end delivery latency.

  17. On the Influence of Informed Agents on Learning and Adaptation over Networks

    CERN Document Server

    Tu, Sheng-Yuan

    2012-01-01

    Adaptive networks consist of a collection of agents with adaptation and learning abilities. The agents interact with each other on a local level and diffuse information across the network through their collaborations. In this work, we consider two types of agents: informed agents and uninformed agents. The former receive new data regularly and perform consultation and in-network tasks, while the latter do not collect data and only participate in the consultation tasks. We examine the performance of adaptive networks as a function of the proportion of informed agents and their distribution in space. The results reveal some interesting and surprising trade-offs between convergence rate and mean-square performance. In particular, among other results, it is shown that the performance of adaptive networks does not necessarily improve with a larger proportion of informed agents. Instead, it is established that the larger the proportion of informed agents is, the faster the convergence rate of the network becomes al...

  18. Cascade of links in complex networks

    Energy Technology Data Exchange (ETDEWEB)

    Feng, Yeqian; Sun, Bihui [Department of Management Science, School of Government, Beijing Normal University, 100875 Beijing (China); Zeng, An, E-mail: anzeng@bnu.edu.cn [School of Systems Science, Beijing Normal University, 100875 Beijing (China)

    2017-01-30

    Cascading failure is an important process which has been widely used to model catastrophic events such as blackouts and financial crisis in real systems. However, so far most of the studies in the literature focus on the cascading process on nodes, leaving the possibility of link cascade overlooked. In many real cases, the catastrophic events are actually formed by the successive disappearance of links. Examples exist in the financial systems where the firms and banks (i.e. nodes) still exist but many financial trades (i.e. links) are gone during the crisis, and the air transportation systems where the airports (i.e. nodes) are still functional but many airlines (i.e. links) stop operating during bad weather. In this letter, we develop a link cascade model in complex networks. With this model, we find that both artificial and real networks tend to collapse even if a few links are initially attacked. However, the link cascading process can be effectively terminated by setting a few strong nodes in the network which do not respond to any link reduction. Finally, a simulated annealing algorithm is used to optimize the location of these strong nodes, which significantly improves the robustness of the networks against the link cascade. - Highlights: • We propose a link cascade model in complex networks. • Both artificial and real networks tend to collapse even if a few links are initially attacked. • The link cascading process can be effectively terminated by setting a few strong nodes. • A simulated annealing algorithm is used to optimize the location of these strong nodes.

  19. Diffusion and Contagion in Networks with Heterogeneous Agents and Homophily

    CERN Document Server

    Jackson, Matthew O

    2011-01-01

    We study how a behavior (an idea, buying a product, having a disease, adopting a cultural fad or a technology) spreads among agents in an a social network that exhibits segregation or homophily (the tendency of agents to associate with others similar to themselves). Individuals are distinguished by their types (e.g., race, gender, age, wealth, religion, profession, etc.) which, together with biased interaction patterns, induce heterogeneous rates of adoption. We identify the conditions under which a behavior diffuses and becomes persistent in the population. These conditions relate to the level of homophily in a society, the underlying proclivities of various types for adoption or infection, as well as how each type interacts with its own type. In particular, we show that homophily can facilitate diffusion from a small initial seed of adopters.

  20. Complexity and agent-based modelling in urban research

    DEFF Research Database (Denmark)

    Fertner, Christian

    Urbanisation processes are results of a broad variety of actors or actor groups and their behaviour and decisions based on different experiences, knowledge, resources, values etc. The decisions done are often on a micro/individual level but resulting in macro/collective behaviour. In urban research...... influence on the bigger system. Traditional scientific methods or theories often tried to simplify, not accounting complex relations of actors and decision-making. The introduction of computers in simulation made new approaches in modelling, as for example agent-based modelling (ABM), possible, dealing...

  1. Multiscaling of soils as heterogeneous complex networks

    OpenAIRE

    Santiago Andrés, Antonio; Cardenas Villalobos, Juan Pablo; Losada González, Juan Carlos; Benito Zafrilla, Rosa Maria; Tarquis Alfonso, Ana Maria; Borondo Rodríguez, Florentino

    2008-01-01

    In this paper we present a complex network model based on a heterogeneous preferential attachment scheme to quantify the structure of porous soils. Under this perspective pores are represented by nodes and the space for the flow of fluids between them is represented by links. Pore properties such as position and size are described by fixed states in a metric space, while an affinity function is introduced to bias the attachment probabilities of links according to these properties. We perform ...

  2. Fermi-Dirac Statistics of Complex Networks

    Institute of Scientific and Technical Information of China (English)

    SHEN Yi; ZHU Di-Ling; LIU Wei-Ming

    2005-01-01

    @@ We investigate phenomena of decline of complex networks by employing and analysing an illness model. Its intrinsic relation with the Fermi distribution is shown and a mapping to Fermi gas is established. The results of numerical simulations are obtained in two ways. We also compare the model with other models, including the dual relationship with the fitness model, and its difference from the Cayley tree model.

  3. Neural Networks with Complex and Quaternion Inputs

    OpenAIRE

    Rishiyur, Adityan

    2006-01-01

    This article investigates Kak neural networks, which can be instantaneously trained, for complex and quaternion inputs. The performance of the basic algorithm has been analyzed and shown how it provides a plausible model of human perception and understanding of images. The motivation for studying quaternion inputs is their use in representing spatial rotations that find applications in computer graphics, robotics, global navigation, computer vision and the spatial orientation of instruments. ...

  4. Universal resilience patterns in complex networks

    Science.gov (United States)

    Gao, Jianxi; Barzel, Baruch; Barabási, Albert-László

    2016-02-01

    Resilience, a system’s ability to adjust its activity to retain its basic functionality when errors, failures and environmental changes occur, is a defining property of many complex systems. Despite widespread consequences for human health, the economy and the environment, events leading to loss of resilience—from cascading failures in technological systems to mass extinctions in ecological networks—are rarely predictable and are often irreversible. These limitations are rooted in a theoretical gap: the current analytical framework of resilience is designed to treat low-dimensional models with a few interacting components, and is unsuitable for multi-dimensional systems consisting of a large number of components that interact through a complex network. Here we bridge this theoretical gap by developing a set of analytical tools with which to identify the natural control and state parameters of a multi-dimensional complex system, helping us derive effective one-dimensional dynamics that accurately predict the system’s resilience. The proposed analytical framework allows us systematically to separate the roles of the system’s dynamics and topology, collapsing the behaviour of different networks onto a single universal resilience function. The analytical results unveil the network characteristics that can enhance or diminish resilience, offering ways to prevent the collapse of ecological, biological or economic systems, and guiding the design of technological systems resilient to both internal failures and environmental changes.

  5. Sampling of Complex Networks: A Datamining Approach

    Science.gov (United States)

    Loecher, Markus; Dohrmann, Jakob; Bauer, Gernot

    2007-03-01

    Efficient and accurate sampling of big complex networks is still an unsolved problem. As the degree distribution is one of the most commonly used attributes to characterize a network, there have been many attempts in recent papers to derive the original degree distribution from the data obtained during a traceroute- like sampling process. This talk describes a strategy for predicting the original degree of a node using the data obtained from a network by traceroute-like sampling making use of datamining techniques. Only local quantities (the sampled degree k, the redundancy of node detection r, the time of the first discovery of a node t and the distance to the sampling source d) are used as input for the datamining models. Global properties like the betweenness centrality are ignored. These local quantities are examined theoretically and in simulations to increase their value for the predictions. The accuracy of the models is discussed as a function of the number of sources used in the sampling process and the underlying topology of the network. The purpose of this work is to introduce the techniques of the relatively young field of datamining to the discussion on network sampling.

  6. Ag+ complexes as potential therapeutic agents in medicine and pharmacy.

    Science.gov (United States)

    Hecel, Aleksandra; Kolkowska, Paulina; Krzywoszynska, Karolina; Szebesczyk, Agnieszka; Rowinska-Zyrek, Magdalena; Kozlowski, Henryk

    2017-09-20

    Silver is a non-essential element, with promising antimicrobial and anticancer properties. This work is a detailed summary of the newest findings on the bioinorganic chemistry of silver, with a special focus on the applications of Ag+ complexes and nanoparticles. The coordination chemistry of silver is given a reasonable amount of attention, summarizing the most common silver binding sites and giving examples of such binding motifs in biologically important proteins. Possible applications of this metal and its complexes in medicine, in particular as antibacterial and antifungal agents and in cancer therapy is discussed in detail. The most recent data on silver nanoparticles are also summarized. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

  7. Complexity and agent-based modelling in urban research

    DEFF Research Database (Denmark)

    Fertner, Christian

    Urbanisation processes are results of a broad variety of actors or actor groups and their behaviour and decisions based on different experiences, knowledge, resources, values etc. The decisions done are often on a micro/individual level but resulting in macro/collective behaviour. In urban research...... influence on the bigger system. Traditional scientific methods or theories often tried to simplify, not accounting complex relations of actors and decision-making. The introduction of computers in simulation made new approaches in modelling, as for example agent-based modelling (ABM), possible, dealing...... of complexity for a majority of science, there exists a huge number of scientific articles, books, tutorials etc. to these topics which doesn’t make it easy for a novice in the field to find the right literature. The literature used gives an optimistic outlook for the future of this methodology, although ABM...

  8. Organo-platinum complexes as antitumor agents (review).

    Science.gov (United States)

    Hill, J M; Speer, R J

    1982-01-01

    Rosenberg et al discovered in the coordination complexes of platinum a new, novel type of potential antitumor agent. Cisplatin [cis-dichlorodiammine platinum (II)4 proved active against a variety of rodent tumors and acted synergistically when combined with other chemotherapeutic agents. Initial clinical tests by Hill et al in 1971, showed cisplatin to be active against malignant lymphoma, Hodgkin's disease, and certain other malignancies. Significant nephrotoxicity, nausea, and vomiting were noted. Since then, cisplatin has been tested alone and in combination chemotherapy and has proven an efficacious anticancer agent in squamous cell carcinoma of head and neck, ovarian carcinoma, disseminated testicular cancer, and others. Its therapeutic value was acknowledged when approved in 1978 by the U.S. FDA for treatment of the latter cancer. The current clinical literature indicates clearly that the full potential of this drug has not yet been realized. Hydration and diuresis have served to mitigate much of the nephrotoxicity, while significant strides toward amelioration of the nausea and vomiting have also been achieved. Literally, thousands of chemically-related congeners have been synthesized, and many have shown marked potency against rodent tumors. Very few, however, have been evaluated clinically, vis-a-vis malonato trans(-)-1,2-diaminocyclohexane platinum(II); this appears a most promising and fertile area of future investigation.

  9. NITRD LSN Workshop Report on Complex Engineered Networks

    Data.gov (United States)

    Networking and Information Technology Research and Development, Executive Office of the President — Complex engineered networks are everywhere: power grids, Internet, transportation networks, and more. They are being used more than ever before, and yet our...

  10. Multi-agent based control of large-scale complex systems employing distributed dynamic inference engine

    Science.gov (United States)

    Zhang, Daili

    are made for critical agents and are organized into logical rings. This architecture maintains clear guidelines for complexity decomposition and also increases the robustness of the whole system. Multiple Sectioned Dynamic Bayesian Networks (MSDBNs) as a distributed dynamic probabilistic inference engine, can be embedded into the control architecture to handle uncertainties of general large-scale complex systems. MSDBNs decomposes a large knowledge-based system into many agents. Each agent holds its partial perspective of a large problem domain by representing its knowledge as a Dynamic Bayesian Network (DBN). Each agent accesses local evidence from its corresponding local sensors and communicates with other agents through finite message passing. If the distributed agents can be organized into a tree structure, satisfying the running intersection property and d-sep set requirements, globally consistent inferences are achievable in a distributed way. By using different frequencies for local DBN agent belief updating and global system belief updating, it balances the communication cost with the global consistency of inferences. In this dissertation, a fully factorized Boyen-Koller (BK) approximation algorithm is used for local DBN agent belief updating, and the static Junction Forest Linkage Tree (JFLT) algorithm is used for global system belief updating. MSDBNs assume a static structure and a stable communication network for the whole system. However, for a real system, sub-Bayesian networks as nodes could be lost, and the communication network could be shut down due to partial damage in the system. Therefore, on-line and automatic MSDBNs structure formation is necessary for making robust state estimations and increasing survivability of the whole system. A Distributed Spanning Tree Optimization (DSTO) algorithm, a Distributed D-Sep Set Satisfaction (DDSSS) algorithm, and a Distributed Running Intersection Satisfaction (DRIS) algorithm are proposed in this dissertation

  11. Role of bulking agents in bladder exstrophy-epispadias complexes

    Directory of Open Access Journals (Sweden)

    Seyed Mohammad Vahid Hosseini

    2013-01-01

    Full Text Available Background: Role of pelvic osteotomy in surgical management of bladder exstrophy is controversial But pelvic rim closure importantly. Bulking agents have been used for perineal and pelvic dysfunction in adults. In this study, bladder extrophy repair was performed without pubic closure And bulking agent injections were used as the strut of anterior pelvis for prevention of Organ prolapse and other functions in this series. Patients and Methods: During the period 2008-2012, twenty-five exstrophy-epispadias complex patients with a mean age of 14 months underwent surgical reconstruction. Rectus abdominis Muscle was detached from the superior pubis and sutured to each other in the midline and Re-anchored at the pubis and 8-9 month later urethra was constructed and placed between prineal muscles. Bladder neck repair and intersyphyseal reconstruction was done With bulking agents one year after primary bladder closure when in our series bladder Prolapse mainly occurred. One to 4 mL of bulking agents polyacrylate (vantris/promedon was injected at the level of the intersymphyseal area and opening on either sides of the urethra. Results: Mean urinary continence score, before, 3 and 6months after injection Were (2.65 ± 074,(1.95 ± 082,(1.75 ± 0.78, respectively.(p < 0.001. The correlation factor Between before injection, 3 and 6 months were % 82, % 74 spectively. Meancapacity of bladder before, 3, 6 months after injection were (31 ± 14.01, (41 ± 12.81, (56 ± 11.98 mml, respectively. The correlation factor before and after injection were 59%. Comparing the CS and CB between male and female before and after Injection were significant. (p < 0.001 but correlation factor in male 99% and Female 74%. Three out of five girls had improved bladder prolapse. There was no Complication, infection or migration of bulking agents. Patients had increased in soft tissue according to MRI. Conclusion: Using bulking agents is a good alternative to sling pelvic floor not

  12. Complex Networks in and beyond Physics

    CERN Document Server

    Volchenkov, D

    2007-01-01

    Physicists study a wide variety of phenomena creating new interdisciplinary research fields by applying theories and methods originally developed in physics in order to solve problems in economics, social science, biology, medicine, technology, etc. In their turn, these different branches of science inspire the invention of new concepts in physics. A basic tool of analysis, in such a context, is the mathematical theory of complexity concerned with the study of complex systems including human economies, climate, nervous systems, cells and living things, including human beings, as well as modern energy or communication infrastructures which are all networks of some kind. Recently, complexity has become a natural domain of interest of the real world socio-cognitive systems, linguistics, and emerging systemics research. The phenomena to be studied and understood arise from neither the physical laws nor the abstraction of mathematics. The challenge is to discern and formulate plausible mathematical structures to d...

  13. Improved Time Complexities for Learning Boolean Networks

    Directory of Open Access Journals (Sweden)

    Chee Keong Kwoh

    2013-09-01

    Full Text Available Existing algorithms for learning Boolean networks (BNs have time complexities of at least O(N · n0:7(k+1, where n is the number of variables, N is the number of samples and k is the number of inputs in Boolean functions. Some recent studies propose more efficient methods with O(N · n2 time complexities. However, these methods can only be used to learn monotonic BNs, and their performances are not satisfactory when the sample size is small. In this paper, we mathematically prove that OR/AND BNs, where the variables are related with logical OR/AND operations, can be found with the time complexity of O(k·(N+ logn·n2, if there are enough noiseless training samples randomly generated from a uniform distribution. We also demonstrate that our method can successfully learn most BNs, whose variables are not related with exclusive OR and Boolean equality operations, with the same order of time complexity for learning OR/AND BNs, indicating our method has good efficiency for learning general BNs other than monotonic BNs. When the datasets are noisy, our method can still successfully identify most BNs with the same efficiency. When compared with two existing methods with the same settings, our method achieves a better comprehensive performance than both of them, especially for small training sample sizes. More importantly, our method can be used to learn all BNs. However, of the two methods that are compared, one can only be used to learn monotonic BNs, and the other one has a much worse time complexity than our method. In conclusion, our results demonstrate that Boolean networks can be learned with improved time complexities.

  14. Complex network analysis of state spaces for random Boolean networks

    Energy Technology Data Exchange (ETDEWEB)

    Shreim, Amer [Complexity Science Group, Department of Physics and Astronomy, University of Calgary, Calgary, AB, T2N 1N4 (Canada); Berdahl, Andrew [Complexity Science Group, Department of Physics and Astronomy, University of Calgary, Calgary, AB, T2N 1N4 (Canada); Sood, Vishal [Complexity Science Group, Department of Physics and Astronomy, University of Calgary, Calgary, AB, T2N 1N4 (Canada); Grassberger, Peter [Complexity Science Group, Department of Physics and Astronomy, University of Calgary, Calgary, AB, T2N 1N4 (Canada); Paczuski, Maya [Complexity Science Group, Department of Physics and Astronomy, University of Calgary, Calgary, AB, T2N 1N4 (Canada)

    2008-01-15

    We apply complex network analysis to the state spaces of random Boolean networks (RBNs). An RBN contains N Boolean elements each with K inputs. A directed state space network (SSN) is constructed by linking each dynamical state, represented as a node, to its temporal successor. We study the heterogeneity of these SSNs at both local and global scales, as well as sample to-sample fluctuations within an ensemble of SSNs. We use in-degrees of nodes as a local topological measure, and the path diversity (Shreim A et al 2007 Phys. Rev. Lett. 98 198701) of an SSN as a global topological measure. RBNs with 2 {<=} K {<=} 5 exhibit non-trivial fluctuations at both local and global scales, while K = 2 exhibits the largest sample-to-sample (possibly non-self-averaging) fluctuations. We interpret the observed 'multi scale' fluctuations in the SSNs as indicative of the criticality and complexity of K = 2 RBNs. 'Garden of Eden' (GoE) states are nodes on an SSN that have in-degree zero. While in-degrees of non-GoE nodes for K > 1 SSNs can assume any integer value between 0 and 2{sup N}, for K = 1 all the non-GoE nodes in a given SSN have the same in-degree which is always a power of two.

  15. Synchronization in node of complex networks consist of complex chaotic system

    Directory of Open Access Journals (Sweden)

    Qiang Wei

    2014-07-01

    Full Text Available A new synchronization method is investigated for node of complex networks consists of complex chaotic system. When complex networks realize synchronization, different component of complex state variable synchronize up to different scaling complex function by a designed complex feedback controller. This paper change synchronization scaling function from real field to complex field for synchronization in node of complex networks with complex chaotic system. Synchronization in constant delay and time-varying coupling delay complex networks are investigated, respectively. Numerical simulations are provided to show the effectiveness of the proposed method.

  16. Spreading to localized targets in complex networks

    Science.gov (United States)

    Sun, Ye; Ma, Long; Zeng, An; Wang, Wen-Xu

    2016-12-01

    As an important type of dynamics on complex networks, spreading is widely used to model many real processes such as the epidemic contagion and information propagation. One of the most significant research questions in spreading is to rank the spreading ability of nodes in the network. To this end, substantial effort has been made and a variety of effective methods have been proposed. These methods usually define the spreading ability of a node as the number of finally infected nodes given that the spreading is initialized from the node. However, in many real cases such as advertising and news propagation, the spreading only aims to cover a specific group of nodes. Therefore, it is necessary to study the spreading ability of nodes towards localized targets in complex networks. In this paper, we propose a reversed local path algorithm for this problem. Simulation results show that our method outperforms the existing methods in identifying the influential nodes with respect to these localized targets. Moreover, the influential spreaders identified by our method can effectively avoid infecting the non-target nodes in the spreading process.

  17. Phase transitions in Pareto optimal complex networks.

    Science.gov (United States)

    Seoane, Luís F; Solé, Ricard

    2015-09-01

    The organization of interactions in complex systems can be described by networks connecting different units. These graphs are useful representations of the local and global complexity of the underlying systems. The origin of their topological structure can be diverse, resulting from different mechanisms including multiplicative processes and optimization. In spatial networks or in graphs where cost constraints are at work, as it occurs in a plethora of situations from power grids to the wiring of neurons in the brain, optimization plays an important part in shaping their organization. In this paper we study network designs resulting from a Pareto optimization process, where different simultaneous constraints are the targets of selection. We analyze three variations on a problem, finding phase transitions of different kinds. Distinct phases are associated with different arrangements of the connections, but the need of drastic topological changes does not determine the presence or the nature of the phase transitions encountered. Instead, the functions under optimization do play a determinant role. This reinforces the view that phase transitions do not arise from intrinsic properties of a system alone, but from the interplay of that system with its external constraints.

  18. The noisy voter model on complex networks

    CERN Document Server

    Carro, Adrián; Miguel, Maxi San

    2016-01-01

    We propose a new analytical method to study stochastic, binary-state models on complex networks. Moving beyond the usual mean-field theories, this alternative approach is based on the introduction of an uncorrelated network approximation, allowing to deal with the network structure as parametric heterogeneity. As an illustration, we study the noisy voter model, a modification of the original voter model including random changes of state. The proposed method is able to unfold the dependence of the model not only on the mean degree (the mean-field prediction) but also on more complex averages over the degree distribution. In particular, we find that the degree heterogeneity ---variance of the underlying degree distribution--- has a strong influence on the location of the critical point of a noise-induced, finite-size transition occurring in the model, on the local ordering of the system, and on the functional form of its temporal correlations. Finally, we show how this latter point opens the possibility of infe...

  19. Statistically validated networks in bipartite complex systems

    CERN Document Server

    Tumminello, Michele; Lillo, Fabrizio; Piilo, Jyrki; Mantegna, Rosario N

    2010-01-01

    Many complex systems present an intrinsic bipartite nature and are often described and modeled in terms of networks [1-5]. Examples include movies and actors [1, 2, 4], authors and scientific papers [6-9], email accounts and emails [10], plants and animals that pollinate them [11, 12]. Bipartite networks are often very heterogeneous in the number of relationships that the elements of one set establish with the elements of the other set. When one constructs a projected network with nodes from only one set, the system heterogeneity makes it very difficult to identify preferential links between the elements. Here we introduce an unsupervised method to statistically validate each link of the projected network against a null hypothesis taking into account the heterogeneity of the system. We apply our method to three different systems, namely the set of clusters of orthologous genes (COG) in completely sequenced genomes [13, 14], a set of daily returns of 500 US financial stocks, and the set of world movies of the ...

  20. Complexation of buffer constituents with neutral complexation agents: part I. Impact on common buffer properties.

    Science.gov (United States)

    Riesová, Martina; Svobodová, Jana; Tošner, Zdeněk; Beneš, Martin; Tesařová, Eva; Gaš, Bohuslav

    2013-09-17

    The complexation of buffer constituents with the complexation agent present in the solution can very significantly influence the buffer properties, such as pH, ionic strength, or conductivity. These parameters are often crucial for selection of the separation conditions in capillary electrophoresis or high-pressure liquid chromatography (HPLC) and can significantly affect results of separation, particularly for capillary electrophoresis as shown in Part II of this paper series (Beneš, M.; Riesová, M.; Svobodová, J.; Tesařová, E.; Dubský, P.; Gaš, B. Anal. Chem. 2013, DOI: 10.1021/ac401381d). In this paper, the impact of complexation of buffer constituents with a neutral complexation agent is demonstrated theoretically as well as experimentally for the model buffer system composed of benzoic acid/LiOH or common buffers (e.g., CHES/LiOH, TAPS/LiOH, Tricine/LiOH, MOPS/LiOH, MES/LiOH, and acetic acid/LiOH). Cyclodextrins as common chiral selectors were used as model complexation agents. We were not only able to demonstrate substantial changes of pH but also to predict the general complexation characteristics of selected compounds. Because of the zwitterion character of the common buffer constituents, their charged forms complex stronger with cyclodextrins than the neutral ones do. This was fully proven by NMR measurements. Additionally complexation constants of both forms of selected compounds were determined by NMR and affinity capillary electrophoresis with a very good agreement of obtained values. These data were advantageously used for the theoretical descriptions of variations in pH, depending on the composition and concentration of the buffer. Theoretical predictions were shown to be a useful tool for deriving some general rules and laws for complexing systems.

  1. Unveiling causal activity of complex networks

    Science.gov (United States)

    Williams-García, Rashid V.; Beggs, John M.; Ortiz, Gerardo

    2017-07-01

    We introduce a novel tool for analyzing complex network dynamics, allowing for cascades of causally-related events, which we call causal webs (c-webs), to be separated from other non-causally-related events. This tool shows that traditionally-conceived avalanches may contain mixtures of spatially-distinct but temporally-overlapping cascades of events, and dynamical disorder or noise. In contrast, c-webs separate these components, unveiling previously hidden features of the network and dynamics. We apply our method to mouse cortical data with resulting statistics which demonstrate for the first time that neuronal avalanches are not merely composed of causally-related events. The original version of this article was uploaded to the arXiv on March 17th, 2016 [1].

  2. Burstiness and fractional diffusion on complex networks

    Science.gov (United States)

    de Nigris, Sarah; Hastir, Anthony; Lambiotte, Renaud

    2016-04-01

    Many dynamical processes on real world networks display complex temporal patterns as, for instance, a fat-tailed distribution of inter-events times, leading to heterogeneous waiting times between events. In this work, we focus on distributions whose average inter-event time diverges, and study its impact on the dynamics of random walkers on networks. The process can naturally be described, in the long time limit, in terms of Riemann-Liouville fractional derivatives. We show that all the dynamical modes possess, in the asymptotic regime, the same power law relaxation, which implies that the dynamics does not exhibit time-scale separation between modes, and that no mode can be neglected versus another one, even for long times. Our results are then confirmed by numerical simulations.

  3. Complex networks renormalization: flows and fixed points.

    Science.gov (United States)

    Radicchi, Filippo; Ramasco, José J; Barrat, Alain; Fortunato, Santo

    2008-10-03

    Recently, it has been claimed that some complex networks are self-similar under a convenient renormalization procedure. We present a general method to study renormalization flows in graphs. We find that the behavior of some variables under renormalization, such as the maximum number of connections of a node, obeys simple scaling laws, characterized by critical exponents. This is true for any class of graphs, from random to scale-free networks, from lattices to hierarchical graphs. Therefore, renormalization flows for graphs are similar as in the renormalization of spin systems. An analysis of classic renormalization for percolation and the Ising model on the lattice confirms this analogy. Critical exponents and scaling functions can be used to classify graphs in universality classes, and to uncover similarities between graphs that are inaccessible to a standard analysis.

  4. Identifying modular relations in complex brain networks

    DEFF Research Database (Denmark)

    Andersen, Kasper Winther; Mørup, Morten; Siebner, Hartwig

    2012-01-01

    We evaluate the infinite relational model (IRM) against two simpler alternative nonparametric Bayesian models for identifying structures in multi subject brain networks. The models are evaluated for their ability to predict new data and infer reproducible structures. Prediction and reproducibility...... are measured within the data driven NPAIRS split-half framework. Using synthetic data drawn from each of the generative models we show that the IRM model outperforms the two competing models when data contain relational structure. For data drawn from the other two simpler models the IRM does not overfit...... and obtains comparable reproducibility and predictability. For resting state functional magnetic resonance imaging data from 30 healthy controls the IRM model is also superior to the two simpler alternatives, suggesting that brain networks indeed exhibit universal complex relational structure...

  5. Burstiness and fractional diffusion on complex networks

    CERN Document Server

    De Nigris, Sarah; Lambiotte, Renaud

    2016-01-01

    Many dynamical processes on real world networks display complex temporal patterns as, for instance, a fat-tailed distribution of inter-events times, leading to heterogeneous waiting times between events. In this work, we focus on distributions whose average inter-event time diverges, and study its impact on the dynamics of random walkers on networks. The process can naturally be described, in the long time limit, in terms of Riemann-Liouville fractional derivatives. We show that all the dynamical modes possess, in the asymptotic regime, the same power law relaxation, which implies that the dynamics does not exhibit time-scale separation between modes, and that no mode can be neglected versus another one, even for long times. Our results are then confirmed by numerical simulations.

  6. Actinide-specific complexing agents: their structural and solution chemistry

    Energy Technology Data Exchange (ETDEWEB)

    Raymond, K.N.; Freeman, G.E.; Kappel, M.J.

    1983-07-01

    The synthesis of a series of tetracatecholate ligands designed to be specific for Pu(IV) and other actinide(IV) ions has been achieved. Although these compounds are very effective as in vivo plutonium removal agents, potentiometric and voltammetric data indicate that at neutral pH full complexation of the Pu(IV) ion by all four catecholate groups does not occur. Spectroscopic results indicate that the tetracatecholates, 3,4,3-LICAMS and 3,4,3-LICAMC, complex Am(III). The Am(IV)/(III)-catecholate couple (where catecholate = 3,4,3-LICAMS or 3,4,3-LICAMC) is not observed, but may not be observable due to the large currents associated with ligand oxidation. However, within the potential range where ligand oxidation does not occur, these experiments indicate that the reduction potential of free Am(IV)/(III) is probably greater than or equal to + 2.6 V vs NHE or higher. Proof of the complexation of americium in the trivalent oxidation state by 3,4,3-LICAMS and 3,4,3-LICAMC elimates the possibility of tetracatholates stabilizing Am(IV) in vivo.

  7. NHC-manganese(i) complexes as carbene transfer agents.

    Science.gov (United States)

    Ruiz, Javier; Berros, Angela; Perandones, Bernabé F; Vivanco, Marilín

    2009-09-21

    Tautomerization of coordinated azoles to their corresponding N-heterocyclic carbenes (NHCs) has been carried out by reaction of complexes fac-[Mn(L)(CO)(3)(dppe)](+) (L = N-phenylimidazole) and fac-[Mn(L)(CO)(3)(bipy)](+) (L = N-methylbenzimidazole, benzoxazole, benzothiazole) with KO(t)Bu and subsequent protonation of the azolyl intermediates with NH(4)PF(6). Several NHC-manganese(i) complexes bearing an N-H residue of general formula fac-[Mn(NHC)(CO)(3)(dppe)](+) and fac-[Mn(NHC)(CO)(3)(bipy)](+) have been tested as carbene transfer agents to the gold fragments [Au(L)](+) (L = PPh(3), CNPh, CNXylyl), allowing isolation or spectroscopic detection of various Mn(i)/Au(i) heterometallic intermediates containing azolyl bridging ligands, which liberate the gold(i) carbene complexes [Au(NHC)(L)](+) by means of acid hydrolysis. By contrast, when using the silver(i) fragment [Ag(PPh(3))](+) as carbene acceptor no transmetallation process occurred but instead inverse tautomerization of the NHC to the corresponding imidazole ligand was observed.

  8. Constrained Traffic of Particles on Complex Networks

    Institute of Scientific and Technical Information of China (English)

    MENG Qing-Kuan; ZHU Jian-Yang

    2011-01-01

    We study the traffic of particles on complex networks under constraints. The constraints we propose are the different interactions between particles and the limited capability of node holding particles. We give the grand partition function of the system and find the distributions of particles at the dynamically balanced point.Then,we investigate the internal relations among the theories of classical statistics,quantum statistics and the zero range process.Finally,we find the finite temperature of Bose-Einstein condensation.Numerical results verify our theoretical expectations.

  9. Intervality and coherence in complex networks

    Science.gov (United States)

    Domínguez-García, Virginia; Johnson, Samuel; Muñoz, Miguel A.

    2016-06-01

    Food webs—networks of predators and prey—have long been known to exhibit "intervality": species can generally be ordered along a single axis in such a way that the prey of any given predator tend to lie on unbroken compact intervals. Although the meaning of this axis—usually identified with a "niche" dimension—has remained a mystery, it is assumed to lie at the basis of the highly non-trivial structure of food webs. With this in mind, most trophic network modelling has for decades been based on assigning species a niche value by hand. However, we argue here that intervality should not be considered the cause but rather a consequence of food-web structure. First, analysing a set of 46 empirical food webs, we find that they also exhibit predator intervality: the predators of any given species are as likely to be contiguous as the prey are, but in a different ordering. Furthermore, this property is not exclusive of trophic networks: several networks of genes, neurons, metabolites, cellular machines, airports, and words are found to be approximately as interval as food webs. We go on to show that a simple model of food-web assembly which does not make use of a niche axis can nevertheless generate significant intervality. Therefore, the niche dimension (in the sense used for food-web modelling) could in fact be the consequence of other, more fundamental structural traits. We conclude that a new approach to food-web modelling is required for a deeper understanding of ecosystem assembly, structure, and function, and propose that certain topological features thought to be specific of food webs are in fact common to many complex networks.

  10. Biodegradability of ethylenediamine-based complexing agents and related compounds.

    Science.gov (United States)

    Pitter, P; Sýkora, V

    2001-08-01

    The biological degradability (Zahn-Wellens test) of ethylenediamine derivatives with carboxymethyl and 2-hydroxyethyl groups was investigated. Mixed bacterial culture (activated sludge) was used as inoculum (non-adapted sludge and sludge adapted at different mean biomass retention time, the so-called sludge age). Biodegradability of ethylene(propylene)di(tri)amine-based complexing agents depends on the character and number of substituents and nitrogen atoms in the molecule. Tetra(penta)substituted derivatives with two or more tertiary nitrogen atoms and carboxymethyl or 2-hydroxyethyl groups in the molecule (EDTA, DTPA, PDTA, HEDTA) are very stable from an environmental point of view. On the contrary, disubstituted derivatives with two secondary nitrogen atoms in the molecule (e.g., EDDA) are potentially degradable.

  11. Removal of Chromium with The Complexing Agents from Industrial Effluents

    Directory of Open Access Journals (Sweden)

    J. L. Prameena Sheeja

    2016-08-01

    Full Text Available Human activities and consequent developments have brought about the spectre of an overwhelming degradation of all facets of the natural environment-physical, chemical, biological and social. Environmental pollution, especially by chemicals, is one of the most significant factors in the degradation of the biosphere components. Among all chemical contaminants, heavy metals are believed to be of special ecological, biological and health significance. Unlike organic pollutants, the majority of which are susceptible to biological degradation, metal ions do not degrade into harmless end products. Chemical precipitation is a simple and economical method, and hence, has been widely used. The reduction of chromium (VI to chromium (III can be done with the help of ferrous sulphate. The precipitation was carried out in the presence and absence of complexing agents such as ammonium chloride, tartrate and citrate.

  12. Imaging complex nutrient dynamics in mycelial networks.

    Science.gov (United States)

    Fricker, M D; Lee, J A; Bebber, D P; Tlalka, M; Hynes, J; Darrah, P R; Watkinson, S C; Boddy, L

    2008-08-01

    Transport networks are vital components of multi-cellular organisms, distributing nutrients and removing waste products. Animal cardiovascular and respiratory systems, and plant vasculature, are branching trees whose architecture is thought to determine universal scaling laws in these organisms. In contrast, the transport systems of many multi-cellular fungi do not fit into this conceptual framework, as they have evolved to explore a patchy environment in search of new resources, rather than ramify through a three-dimensional organism. These fungi grow as a foraging mycelium, formed by the branching and fusion of threadlike hyphae, that gives rise to a complex network. To function efficiently, the mycelial network must both transport nutrients between spatially separated source and sink regions and also maintain its integrity in the face of continuous attack by mycophagous insects or random damage. Here we review the development of novel imaging approaches and software tools that we have used to characterise nutrient transport and network formation in foraging mycelia over a range of spatial scales. On a millimetre scale, we have used a combination of time-lapse confocal imaging and fluorescence recovery after photobleaching to quantify the rate of diffusive transport through the unique vacuole system in individual hyphae. These data then form the basis of a simulation model to predict the impact of such diffusion-based movement on a scale of several millimetres. On a centimetre scale, we have used novel photon-counting scintillation imaging techniques to visualize radiolabel movement in small microcosms. This approach has revealed novel N-transport phenomena, including rapid, preferential N-resource allocation to C-rich sinks, induction of simultaneous bi-directional transport, abrupt switching between different pre-existing transport routes, and a strong pulsatile component to transport in some species. Analysis of the pulsatile transport component using Fourier

  13. Combinatorial Laplacian and entropy of simplicial complexes associated with complex networks

    Science.gov (United States)

    Maletić, S.; Rajković, M.

    2012-09-01

    Simplicial complexes represent useful and accurate models of complex networks and complex systems in general. We explore the properties of spectra of combinatorial Laplacian operator of simplicial complexes and show its relationship with connectivity properties of the Q-vector and with connectivities of cliques in the simplicial clique complex. We demonstrate the need for higher order analysis in complex networks and compare the results with ordinary graph spectra. Methods and results are obtained using social network of the Zachary karate club.

  14. Traffic of indistinguishable particles in complex networks

    Institute of Scientific and Technical Information of China (English)

    Meng Qing-Kuan; Zhu Jian-Yang

    2009-01-01

    In this paper,we apply a simple walk mechanism to the study of the traffic of many indistinguishable particles in complex networks. The network with particles stands for a particle system,and every vertex in the network stands for a quantum state with the corresponding energy determined by the vertex degree. Although the particles are indistinguishable,the quantum states can be distinguished. When the many indistinguishable particles walk randomly in the system for a long enough time and the system reaches dynamic equilibrium,we find that under different restrictive conditions the particle distributions satisfy different forms,including the Bose-Einstein distribution,the Fermi-Dirac distribution and the non-Fermi distribution (as we temporarily call it). As for the Bose-Einstein distribution,we find that only if the particle density is larger than zero,with increasing particle density,do more and more particles condense in the lowest energy level. While the particle density is very low,the particle distribution transforms from the quantum statistical form to the classically statistical form,I.e.,transforms from the Bose distribution or the Fermi distribution to the Boltzmann distribution. The numerical results fit well with the analytical predictions.

  15. A complex systems approach to planning, optimization and decision making for energy networks

    Energy Technology Data Exchange (ETDEWEB)

    Beck, Jessica; Kempener, Ruud [School of Chemical and Biomolecular Engineering, Building J01, University of Sydney, NSW 2006 (Australia); Cohen, Brett [Department of Chemical Engineering, University of Cape Town, Rondebosch (South Africa); Petrie, Jim [School of Chemical and Biomolecular Engineering, Building J01, University of Sydney, NSW 2006 (Australia); Department of Chemical Engineering, University of Cape Town, Rondebosch (South Africa)

    2008-08-15

    This paper explores a new approach to planning and optimization of energy networks, using a mix of global optimization and agent-based modeling tools. This approach takes account of techno-economic, environmental and social criteria, and engages explicitly with inherent network complexity in terms of the autonomous decision-making capability of individual agents within the network, who may choose not to act as economic rationalists. This is an important consideration from the standpoint of meeting sustainable development goals. The approach attempts to set targets for energy planning, by determining preferred network development pathways through multi-objective optimization. The viability of such plans is then explored through agent-based models. The combined approach is demonstrated for a case study of regional electricity generation in South Africa, with biomass as feedstock. (author)

  16. Quantized Dissensus in Networks of Agents subject to Death and Duplication

    CERN Document Server

    Bauso, D; Pesenti, R

    2009-01-01

    Dissensus is a modeling framework for networks of dynamic agents in competition for scarce resources. Originally inspired by biological cells behaviors, it fits also marketing, finance and many other application areas. Competition is often unstable in the sense that strong agents, those having access to large resources, gain more and more resources at the expense of weak agents. Thus, strong agents duplicate when reaching a critical amount of resources, whereas weak agents die when loosing all their resources. To capture all these phenomena we introduce systems with a discrete time gossip and unstable state dynamics interrupted by discrete events affecting the network topology. Invariancy of states and topologies and network connectivity are explored.

  17. Big Data Processing in Complex Hierarchical Network Systems

    CERN Document Server

    Polishchuk, Olexandr; Tyutyunnyk, Maria; Yadzhak, Mykhailo

    2016-01-01

    This article covers the problem of processing of Big Data that describe process of complex networks and network systems operation. It also introduces the notion of hierarchical network systems combination into associations and conglomerates alongside with complex networks combination into multiplexes. The analysis is provided for methods of global network structures study depending on the purpose of the research. Also the main types of information flows in complex hierarchical network systems being the basic components of associations and conglomerates are covered. Approaches are proposed for creation of efficient computing environments, distributed computations organization and information processing methods parallelization at different levels of system hierarchy.

  18. Hybrid synchronization of two independent chaotic systems on complex network

    Indian Academy of Sciences (India)

    NIAN FUZHONG; LIU WEILONG

    2016-06-01

    The real network nodes are always interfered by other messages. So, how to realize the hybrid synchronization of two independent chaotic systems based on the complex network is very important. To solve this problem, two other problems should be considered. One is how the same network node of the complex network was affected by different information sources. Another is how to achieve hybrid synchronization on the network. In this paper, the theoretical analysis andnumerical simulation on various complex networks are implemented. The results indicate that the hybrid synchronization of two independent chaotic systems is feasible.

  19. A Complex-Valued Projection Neural Network for Constrained Optimization of Real Functions in Complex Variables.

    Science.gov (United States)

    Zhang, Songchuan; Xia, Youshen; Wang, Jun

    2015-12-01

    In this paper, we present a complex-valued projection neural network for solving constrained convex optimization problems of real functions with complex variables, as an extension of real-valued projection neural networks. Theoretically, by developing results on complex-valued optimization techniques, we prove that the complex-valued projection neural network is globally stable and convergent to the optimal solution. Obtained results are completely established in the complex domain and thus significantly generalize existing results of the real-valued projection neural networks. Numerical simulations are presented to confirm the obtained results and effectiveness of the proposed complex-valued projection neural network.

  20. PREFACE: Complex Networks: from Biology to Information Technology

    Science.gov (United States)

    Barrat, A.; Boccaletti, S.; Caldarelli, G.; Chessa, A.; Latora, V.; Motter, A. E.

    2008-06-01

    Folksonomies and clustering in the collaborative system CiteULike, analyse an online collaborative tagging system where users bookmark and annotate scientific papers. Such a system can be naturally represented as a tripartite graph whose nodes represent papers, users and tags connected by individual tag assignments. The semantics of tags is studied in order to uncover hidden relationships between tags. The authors find that the clustering coefficient reflects the semantical patterns among tags. Lambiotte's contribution, Majority rule on heterogeneous networks, focuses on the majority rule model for opinion formation when the agents interact through a complex network. It is shown that on networks with modular structures the system may exhibit an asymmetric regime, where nodes in different communities reach opposite average opinions. In addition, the node degree heterogeneity is shown to play an important role in the emergence of collective behaviour. In Structural analysis of behavioural networks from the Internet, Meiss et al analyse the structure of the Internet. The authors present a characterisation of the properties of the behavioural networks generated by several million users of the Abilene (Internet2) network. Structural features of these networks offer new insights into scaling properties of network activity and ways of distinguishing particular patterns of traffic. The final contribution, A social network's changing statistical properties and the quality of human innovation by Uzzi, is an analysis of the collaboration network of artists that made Broadway musicals in the post World War II period. It is shown that when the clustering coefficient in this network is low or high, the financial and artistic success of the industry is low while an intermediate level of clustering is associated with successful shows. We hope that this special issue will serve as a reference of the state of the knowledge in this exciting area of interdisciplinary research and that it will

  1. Fuzzy Entropy Method for Quantifying Supply Chain Networks Complexity

    Science.gov (United States)

    Zhang, Jihui; Xu, Junqin

    Supply chain is a special kind of complex network. Its complexity and uncertainty makes it very difficult to control and manage. Supply chains are faced with a rising complexity of products, structures, and processes. Because of the strong link between a supply chain’s complexity and its efficiency the supply chain complexity management becomes a major challenge of today’s business management. The aim of this paper is to quantify the complexity and organization level of an industrial network working towards the development of a ‘Supply Chain Network Analysis’ (SCNA). By measuring flows of goods and interaction costs between different sectors of activity within the supply chain borders, a network of flows is built and successively investigated by network analysis. The result of this study shows that our approach can provide an interesting conceptual perspective in which the modern supply network can be framed, and that network analysis can handle these issues in practice.

  2. Epidemic spreading on dual-structure networks with mobile agents

    Science.gov (United States)

    Yao, Yiyang; Zhou, Yinzuo

    2017-02-01

    The rapid development of modern society continually transforms the social structure which leads to an increasingly distinct dual structure of higher population density in urban areas and lower density in rural areas. Such structure may induce distinctive spreading behavior of epidemics which does not happen in a single type structure. In this paper, we study the epidemic spreading of mobile agents on dual structure networks based on SIRS model. First, beyond the well known epidemic threshold for generic epidemic model that when the infection rate is below the threshold a pertinent infectious disease will die out, we find the other epidemic threshold which appears when the infection rate of a disease is relatively high. This feature of two thresholds for the SIRS model may lead to the elimination of infectious disease when social network has either high population density or low population density. Interestingly, however, we find that when a high density area is connected to a low density may cause persistent spreading of the infectious disease, even though the same disease will die out when it spreads in each single area. This phenomenon indicates the critical role of the connection between the two areas which could radically change the behavior of spreading dynamics. Our findings, therefore, provide new understanding of epidemiology pertinent to the characteristic modern social structure and have potential to develop controlling strategies accordingly.

  3. ELASTICITY:Topological characterization of robustness in complex networks

    NARCIS (Netherlands)

    Sydney, A.; Scoglio, C.; Schumm, P.; Kooij, R.E.

    2008-01-01

    Just as a herd of animals relies on its robust social structure to survive in the wild, similarly robustness is a crucial characteristic for the survival of a complex network under attack. The capacity to measure robustness in complex networks defines a network's survivability in the advent of class

  4. ELASTICITY:Topological characterization of robustness in complex networks

    NARCIS (Netherlands)

    Sydney, A.; Scoglio, C.; Schumm, P.; Kooij, R.E.

    2008-01-01

    Just as a herd of animals relies on its robust social structure to survive in the wild, similarly robustness is a crucial characteristic for the survival of a complex network under attack. The capacity to measure robustness in complex networks defines a network's survivability in the advent of class

  5. Efficient inference of overlapping communities in complex networks

    DEFF Research Database (Denmark)

    Fruergaard, Bjarne Ørum; Herlau, Tue

    2014-01-01

    We discuss two views on extending existing methods for complex network modeling which we dub the communities first and the networks first view, respectively. Inspired by the networks first view that we attribute to White, Boorman, and Breiger (1976)[1], we formulate the multiple-networks stochastic...... sampling. The result is an effective multiple-membership model without the drawbacks of introducing complex definitions of "groups" and how they interact. We demonstrate results on the recovery of planted structure in synthetic networks and show very encouraging results on link prediction performances...... using multiple-networks models on a number of real-world network data sets....

  6. Agent-based simulations of emotion spreading in online social networks

    CERN Document Server

    Šuvakov, Milovan; Schweitzer, Frank; Tadić, Bosiljka

    2012-01-01

    Quantitative analysis of empirical data from online social networks reveals group dynamics in which emotions are involved (\\v{S}uvakov et al). Full understanding of the underlying mechanisms, however, remains a challenging task. Using agent-based computer simulations, in this paper we study dynamics of emotional communications in online social networks. The rules that guide how the agents interact are motivated, and the realistic network structure and some important parameters are inferred from the empirical dataset of \\texttt{MySpace} social network. Agent's emotional state is characterized by two variables representing psychological arousal---reactivity to stimuli, and valence---attractiveness or aversiveness, by which common emotions can be defined. Agent's action is triggered by increased arousal. High-resolution dynamics is implemented where each message carrying agent's emotion along the network link is identified and its effect on the recipient agent is considered as continuously aging in time. Our res...

  7. Synchronization of High-order Discrete-time Linear Complex Networks with Time-varying Delays

    Institute of Scientific and Technical Information of China (English)

    HaiLong Li; JianXiang Xi; YaoQing Cao; DuoSheng Wu

    2014-01-01

    Synchronization of high-order discrete-time complex networks with undirected topologies is studied and the impacts of time delays are investigated. Firstly, by the state decomposition, synchronization problems are transformed into asymptotic stability ones of multiple lower dimensional time-delayed subsystems. Then, linear matrix inequality ( LMI) criteria for synchronization are given, which can guarantee the scalability of complex networks since they only include three LMI constraints independent of the number of agents. Moreover, an explicit expression of the synchronization function is presented, which can describe the synchronization behavior of all agents in complex networks. Finally, a numerical example is given to demonstrate the theoretical results, where it is shown that if the gain matrices of synchronization protocols satisfy LMI criteria for synchronization, synchronization can be achieved.

  8. Simulation and evaluation of urban rail transit network based on multi-agent approach

    Directory of Open Access Journals (Sweden)

    Xiangming Yao

    2013-03-01

    Full Text Available Purpose: Urban rail transit is a complex and dynamic system, which is difficult to be described in a global mathematical model for its scale and interaction. In order to analyze the spatial and temporal characteristics of passenger flow distribution and evaluate the effectiveness of transportation strategies, a new and comprehensive method depicted such dynamic system should be given. This study therefore aims at using simulation approach to solve this problem for subway network. Design/methodology/approach: In this thesis a simulation model based on multi-agent approach has been proposed, which is a well suited method to design complex systems. The model includes the specificities of passengers’ travelling behaviors and takes into account of interactions between travelers and trains. Findings: Research limitations/implications: We developed an urban rail transit simulation tool for verification of the validity and accuracy of this model, using real passenger flow data of Beijing subway network to take a case study, results show that our simulation tool can be used to analyze the characteristic of passenger flow distribution and evaluate operation strategies well. Practical implications: The main implications of this work are to provide decision support for traffic management, making train operation plan and dispatching measures in emergency. Originality/value: A new and comprehensive method to analyze and evaluate subway network is presented, accuracy and computational efficiency of the model has been confirmed and meet with the actual needs for large-scale network.

  9. 5th International Workshop on Complex Networks and their Applications

    CERN Document Server

    Gaito, Sabrina; Quattrociocchi, Walter; Sala, Alessandra

    2017-01-01

    This book highlights cutting-edge research in the field of network science, offering scientists, researchers and graduate students a unique opportunity to catch up on the latest advances in theory and a multitude of applications. It presents the peer-reviewed proceedings of the fifth International Workshop on Complex Networks & their Applications (COMPLEX NETWORKS 2016), which took place in Milan during the last week of November 2016. The carefully selected papers are divided into 11 sections reflecting the diversity and richness of research areas in the field. More specifically, the following topics are covered: Network models; Network measures; Community structure; Network dynamics; Diffusion, epidemics and spreading processes; Resilience and control; Network visualization; Social and political networks; Networks in finance and economics; Biological and ecological networks; and Network analysis.

  10. An Information Theoretic Investigation Of Complex Adaptive Supply Networks With Organizational Topologies

    Science.gov (United States)

    2016-12-22

    self-organized industrial symbiosis networks: an agent- based simulation study," Journal of Cleaner Production , vol. 112, pp. 4353- 4366, 2016. 104...networks: a complex adaptive systems perspective," International Journal of Production Research 43.20, pp. 4235-4265, 2005. [4] P. Anderson...34 International Journal of Production Economics 124.2, pp. 310-330, 2010. [24] S. D. Pathak, J. M. Day, A. Nair, W. J. Sawaya and M. M. Kristal

  11. Complex networks of earthquakes and aftershocks

    Directory of Open Access Journals (Sweden)

    M. Baiesi

    2005-01-01

    Full Text Available We invoke a metric to quantify the correlation between any two earthquakes. This provides a simple and straightforward alternative to using space-time windows to detect aftershock sequences and obviates the need to distinguish main shocks from aftershocks. Directed networks of earthquakes are constructed by placing a link, directed from the past to the future, between pairs of events that are strongly correlated. Each link has a weight giving the relative strength of correlation such that the sum over the incoming links to any node equals unity for aftershocks, or zero if the event had no correlated predecessors. A correlation threshold is set to drastically reduce the size of the data set without losing significant information. Events can be aftershocks of many previous events, and also generate many aftershocks. The probability distribution for the number of incoming and outgoing links are both scale free, and the networks are highly clustered. The Omori law holds for aftershock rates up to a decorrelation time that scales with the magnitude, m, of the initiating shock as tcutoff~10β m with β~-3/4. Another scaling law relates distances between earthquakes and their aftershocks to the magnitude of the initiating shock. Our results are inconsistent with the hypothesis of finite aftershock zones. We also find evidence that seismicity is dominantly triggered by small earthquakes. Our approach, using concepts from the modern theory of complex networks, together with a metric to estimate correlations, opens up new avenues of research, as well as new tools to understand seismicity.

  12. A complex network approach to cloud computing

    CERN Document Server

    Travieso, Gonzalo; Bruno, Odemir Martinez; Costa, Luciano da Fontoura

    2015-01-01

    Cloud computing has become an important means to speed up computing. One problem influencing heavily the performance of such systems is the choice of nodes as servers responsible for executing the users' tasks. In this article we report how complex networks can be used to model such a problem. More specifically, we investigate the performance of the processing respectively to cloud systems underlain by Erdos-Renyi and Barabasi-Albert topology containing two servers. Cloud networks involving two communities not necessarily of the same size are also considered in our analysis. The performance of each configuration is quantified in terms of two indices: the cost of communication between the user and the nearest server, and the balance of the distribution of tasks between the two servers. Regarding the latter index, the ER topology provides better performance than the BA case for smaller average degrees and opposite behavior for larger average degrees. With respect to the cost, smaller values are found in the BA ...

  13. Advances in dynamic network modeling in complex transportation systems

    CERN Document Server

    Ukkusuri, Satish V

    2013-01-01

    This book focuses on the latest in dynamic network modeling, including route guidance and traffic control in transportation systems and other complex infrastructure networks. Covers dynamic traffic assignment, flow modeling, mobile sensor deployment and more.

  14. Identifying Social Communities in Complex Communications for Network Efficiency

    Science.gov (United States)

    Hui, Pan; Yoneki, Eiko; Crowcroft, Jon; Chan, Shu-Yan

    Complex communication networks, more particular Mobile Ad Hoc Networks (MANET) and Pocket Switched Networks (PSN), rely on short range radio and device mobility to transfer data across the network. These kind of mobile networks contain duality in nature: they are radio networks at the same time also human networks, and hence knowledge from social networks can be also applicable here. In this paper, we demonstrate how identifying social communities can significantly improve the forwarding efficiencies in term of delivery ratio and delivery cost. We verify our hypothesis using data from five human mobility experiments and test on two application scenarios, asynchronous messaging and publish/subscribe service.

  15. A Multi-Agent Framework for Execution of Complex Applications

    Directory of Open Access Journals (Sweden)

    Alexandru Cicortas

    2006-07-01

    Full Text Available Complex applications execution needs a lot of conditions starting with hardwareand software resources until the task sequencing and verifying the results of the execution.The needed resources can be found locally or on the Web and Grid. For an efficient usagethe needed resources application and the effective resources found must be described in anappropriate and way and we propose the XML. The matching between the resources of theapplication and the Web/Grid resources is done in our proposal by the agents. As a newapproach in the last years is the Service Oriented Architecture (SOA that is developed asan efficient solution. The services are furnished by the providers and these are used by theclients in some specific conditions. The realization of the SOA technology presents a realopportunity to improve effectiveness. On the Web and Grid we dispose for services andthese can be used in a given contest. SOA provides the application of well-foundedconcepts that exploits the ability of modern system resources to collaborate, independent oflocation across heterogeneous technologies.

  16. Mean Square Synchronization of Stochastic Nonlinear Delayed Coupled Complex Networks

    Directory of Open Access Journals (Sweden)

    Chengrong Xie

    2013-01-01

    Full Text Available We investigate the problem of adaptive mean square synchronization for nonlinear delayed coupled complex networks with stochastic perturbation. Based on the LaSalle invariance principle and the properties of the Weiner process, the controller and adaptive laws are designed to ensure achieving stochastic synchronization and topology identification of complex networks. Sufficient conditions are given to ensure the complex networks to be mean square synchronization. Furthermore, numerical simulations are also given to demonstrate the effectiveness of the proposed scheme.

  17. A quantitative method for determining the robustness of complex networks

    Science.gov (United States)

    Qin, Jun; Wu, Hongrun; Tong, Xiaonian; Zheng, Bojin

    2013-06-01

    Most current studies estimate the invulnerability of complex networks using a qualitative method that analyzes the decay rate of network performance. This method results in confusion over the invulnerability of various types of complex networks. By normalizing network performance and defining a baseline, this paper defines the invulnerability index as the integral of the normalized network performance curve minus the baseline. This quantitative method seeks to measure network invulnerability under both edge and node attacks and provides a definition on the distinguishment of the robustness and fragility of networks. To demonstrate the proposed method, three small-world networks were selected as test beds. The simulation results indicate that the proposed invulnerability index can effectively and accurately quantify network resilience and can deal with both the node and edge attacks. The index can provide a valuable reference for determining network invulnerability in future research.

  18. Low-level Control of Network Elements from an Agent Platform

    DEFF Research Database (Denmark)

    Hansen, Mads Stenhuus; Jensen, P.; Soldatos, J.;

    1999-01-01

    An important issue for the implementation of an agent system, which controls a telecommunications network, is to enable low-level access of the network devices by the agent platform, bypassing the control logic inherent in them. This issue has been coped with successfully in the IMPACT project...

  19. Effects of Competition and Cooperation Interaction between Agents on Networks in Presence of a "Market Capacity"

    CERN Document Server

    Sonubi, A; Stefani, S; Ausloos, M

    2016-01-01

    A network effect is introduced taking into account competition, cooperation and mixed-type interaction amongst agents along a generalized Verhulst-Lotka-Volterra model. It is also argued that the presence of a market capacity enforces an indubious limit on the agent's size growth. The state stability of triadic agents, i.e., the most basic network plaquette, is investigated analytically for possible scenarios, through a fixed point analysis. It is discovered that: (i) \\market" demand is only satisfied for full competition when one agent monopolizes the market; (ii) growth of agent size is encouraged in full cooperation; (iii) collaboration amongst agents to compete against one single agent may result in the disappearance of this single agent out of the market, and (iv) cooperating with two rivals may become a growth strategy for an intelligent agent.

  20. Synchronization of general complex networks via adaptive control schemes

    Indian Academy of Sciences (India)

    Ping He; Chun-Guo Jing; Chang-Zhong Chen; Tao Fan; Hassan Saberi Nik

    2014-03-01

    In this paper, the synchronization problem of general complex networks is investigated by using adaptive control schemes. Time-delay coupling, derivative coupling, nonlinear coupling etc. exist universally in real-world complex networks. The adaptive synchronization scheme is designed for the complex network with multiple class of coupling terms. A criterion guaranteeing synchronization of such complex networks is established by employing the Lyapunov stability theorem and adaptive control schemes. Finally, an illustrative example with numerical simulation is given to show the feasibility and efficiency of theoretical results.

  1. Complex network approach for recurrence analysis of time series

    Energy Technology Data Exchange (ETDEWEB)

    Marwan, Norbert, E-mail: marwan@pik-potsdam.d [Potsdam Institute for Climate Impact Research, PO Box 601203, 14412 Potsdam (Germany); Donges, Jonathan F. [Potsdam Institute for Climate Impact Research, PO Box 601203, 14412 Potsdam (Germany)] [Department of Physics, Humboldt University Berlin, Newtonstr. 15, 12489 Berlin (Germany); Zou Yong [Potsdam Institute for Climate Impact Research, PO Box 601203, 14412 Potsdam (Germany); Donner, Reik V. [Potsdam Institute for Climate Impact Research, PO Box 601203, 14412 Potsdam (Germany)] [Institute for Transport and Economics, Dresden University of Technology, Andreas-Schubert-Str. 23, 01062 Dresden (Germany)] [Graduate School of Science, Osaka Prefecture University, 1-1 Gakuencho, Naka-ku, Sakai 599-8531 (Japan); Kurths, Juergen [Potsdam Institute for Climate Impact Research, PO Box 601203, 14412 Potsdam (Germany)] [Department of Physics, Humboldt University Berlin, Newtonstr. 15, 12489 Berlin (Germany)

    2009-11-09

    We propose a novel approach for analysing time series using complex network theory. We identify the recurrence matrix (calculated from time series) with the adjacency matrix of a complex network and apply measures for the characterisation of complex networks to this recurrence matrix. By using the logistic map, we illustrate the potential of these complex network measures for the detection of dynamical transitions. Finally, we apply the proposed approach to a marine palaeo-climate record and identify the subtle changes to the climate regime.

  2. On the Evolution of Complex Network Topology Under Network Churn

    OpenAIRE

    Karyotis, Vasileios; Stai, Eleni; Papavassiliou, Symeon

    2016-01-01

    Part 6: Network Modeling; International audience; The future Internet is becoming more diverse, incorporating heterogeneous access networks. The latter are characterized by numerous devices that join/leave the network dynamically, creating intense churn patterns. New approaches to analyze and quantify churn-induced network evolution are required. In this paper, we address such need by introducing a new analysis framework that maps network evolution into trajectories in multi-dimensional vecto...

  3. Fundamentals of complex networks models, structures and dynamics

    CERN Document Server

    Chen, Guanrong; Li, Xiang

    2014-01-01

    Complex networks such as the Internet, WWW, transportationnetworks, power grids, biological neural networks, and scientificcooperation networks of all kinds provide challenges for futuretechnological development. In particular, advanced societies havebecome dependent on large infrastructural networks to an extentbeyond our capability to plan (modeling) and to operate (control).The recent spate of collapses in power grids and ongoing virusattacks on the Internet illustrate the need for knowledge aboutmodeling, analysis of behaviors, optimized planning and performancecontrol in such networks. F

  4. Multi-agents Based Modelling for Distribution Network Operation with Electric Vehicle Integration

    DEFF Research Database (Denmark)

    Hu, Junjie; Morais, Hugo; Zong, Yi

    2014-01-01

    Electric vehicles (EV) can become integral part of a smart grid because instead of just consuming power they are capable of providing valuable services to power systems. To integrate EVs smoothly into the power systems, a multi-agents system (MAS) with hierarchical organization structure...... is proposed in this paper. The proposed MAS system consists of three types of agents: distribution system operator agent (DSO agent), electric vehicle fleet operator agent (EV FO agent or alternatively called virtual power plant agent) and EV agent. A DSO agent belongs to the top level of the hierarchy...... and its role is to manage the distribution network safely by avoiding grid congestions and using congestion prices to coordinate the energy schedule of VPPs. VPP agents belong to the middle level and their roles are to manage the charge periods of the EVs. EV agents sit in the bottom level...

  5. Complex network perspective on structure and function of Staphylococcus aureus metabolic network

    Indian Academy of Sciences (India)

    L Ying; D W Ding

    2013-02-01

    With remarkable advances in reconstruction of genome-scale metabolic networks, uncovering complex network structure and function from these networks is becoming one of the most important topics in system biology. This work aims at studying the structure and function of Staphylococcus aureus (S. aureus) metabolic network by complex network methods. We first generated a metabolite graph from the recently reconstructed high-quality S. aureus metabolic network model. Then, based on `bow tie' structure character, we explain and discuss the global structure of S. aureus metabolic network. The functional significance, global structural properties, modularity and centrality analysis of giant strong component in S. aureus metabolic networks are studied.

  6. Study of the Security in Network Management Based on Mobile Agents

    Institute of Scientific and Technical Information of China (English)

    CHEN Zhi; WANG Ru-chuan

    2004-01-01

    Security of mobile-agent based network management must be considered due to the widespread adoption of mobile agents in network management, which involves the protections of mobile agents, management station and managed devices. The integrated security model proposed in our paper incorporates the effective security countermeasures of these entities into a trusted execution environment and two security protection layers. Sandbox based on Java virtual machine and Java card independent on the network devices also with the cryptography technology in this model together protect the network management process.

  7. [Methodological novelties applied to the anthropology of food: agent-based models and social networks analysis].

    Science.gov (United States)

    Díaz Córdova, Diego

    2016-01-01

    The aim of this article is to introduce two methodological strategies that have not often been utilized in the anthropology of food: agent-based models and social networks analysis. In order to illustrate these methods in action, two cases based in materials typical of the anthropology of food are presented. For the first strategy, fieldwork carried out in Quebrada de Humahuaca (province of Jujuy, Argentina) regarding meal recall was used, and for the second, elements of the concept of "domestic consumption strategies" applied by Aguirre were employed. The underlying idea is that, given that eating is recognized as a "total social fact" and, therefore, as a complex phenomenon, the methodological approach must also be characterized by complexity. The greater the number of methods utilized (with the appropriate rigor), the better able we will be to understand the dynamics of feeding in the social environment.

  8. Optimization-based topology identification of complex networks

    Institute of Scientific and Technical Information of China (English)

    Tang Sheng-Xue; Chen Li; He Yi-Gang

    2011-01-01

    In many cases,the topological structures of a complex network are unknown or uncertain,and it is of significance to identify the exact topological structure.An optimization-based method of identifying the topological structure of a complex network is proposed in this paper.Identification of the exact network topological structure is converted into a minimal optimization problem by using the estimated network.Then,an improved quantum-behaved particle swarm optimization algorithm is used to solve the optimization problem.Compared with the previous adaptive synchronizationbased method,the proposed method is simple and effective and is particularly valid to identify the topological structure of synchronization complex networks.In some cases where the states of a complex network are only partially observable,the exact topological structure of a network can also be identified by using the proposed method.Finally,numerical simulations are provided to show the effectiveness of the proposed method.

  9. Identification of hybrid node and link communities in complex networks

    Science.gov (United States)

    He, Dongxiao; Jin, Di; Chen, Zheng; Zhang, Weixiong

    2015-03-01

    Identifying communities in complex networks is an effective means for analyzing complex systems, with applications in diverse areas such as social science, engineering, biology and medicine. Finding communities of nodes and finding communities of links are two popular schemes for network analysis. These schemes, however, have inherent drawbacks and are inadequate to capture complex organizational structures in real networks. We introduce a new scheme and an effective approach for identifying complex mixture structures of node and link communities, called hybrid node-link communities. A central piece of our approach is a probabilistic model that accommodates node, link and hybrid node-link communities. Our extensive experiments on various real-world networks, including a large protein-protein interaction network and a large network of semantically associated words, illustrated that the scheme for hybrid communities is superior in revealing network characteristics. Moreover, the new approach outperformed the existing methods for finding node or link communities separately.

  10. Optimizing controllability of complex networks by minimum structural perturbations.

    Science.gov (United States)

    Wang, Wen-Xu; Ni, Xuan; Lai, Ying-Cheng; Grebogi, Celso

    2012-02-01

    To drive a large, complex, networked dynamical system toward some desired state using as few external signals as possible is a fundamental issue in the emerging field of controlling complex networks. Optimal control is referred to the situation where such a network can be fully controlled using only one driving signal. We propose a general approach to optimizing the controllability of complex networks by judiciously perturbing the network structure. The principle of our perturbation method is validated theoretically and demonstrated numerically for homogeneous and heterogeneous random networks and for different types of real networks as well. The applicability of our method is discussed in terms of the relative costs of establishing links and imposing external controllers. Besides the practical usage of our approach, its implementation elucidates, interestingly, the intricate relationship between certain structural properties of the network and its controllability.

  11. A Functional Complexity Framework for the Analysis of Telecommunication Networks

    CERN Document Server

    Dzaferagic, Merim; Macaluso, Irene; Marchetti, Nicola

    2016-01-01

    The rapid evolution of network services demands new paradigms for studying and designing networks. In order to understand the underlying mechanisms that provide network functions, we propose a framework which enables the functional analysis of telecommunication networks. This framework allows us to isolate and analyse a network function as a complex system. We propose functional topologies to visualise the relationships between system entities and enable the systematic study of interactions between them. We also define a complexity metric $C_F$ (functional complexity) which quantifies the variety of structural patterns and roles of nodes in the topology. This complexity metric provides a wholly new approach to study the operation of telecommunication networks. We study the relationship between $C_F$ and different graph structures by analysing graph theory metrics in order to recognize complex organisations. $C_F$ is equal to zero for both a full mesh topology and a disconnected topology. We show that complexi...

  12. Ranking important nodes in complex networks by simulated annealing

    Science.gov (United States)

    Sun, Yu; Yao, Pei-Yang; Wan, Lu-Jun; Shen, Jian; Zhong, Yun

    2017-02-01

    In this paper, based on simulated annealing a new method to rank important nodes in complex networks is presented. First, the concept of an importance sequence (IS) to describe the relative importance of nodes in complex networks is defined. Then, a measure used to evaluate the reasonability of an IS is designed. By comparing an IS and the measure of its reasonability to a state of complex networks and the energy of the state, respectively, the method finds the ground state of complex networks by simulated annealing. In other words, the method can construct a most reasonable IS. The results of experiments on real and artificial networks show that this ranking method not only is effective but also can be applied to different kinds of complex networks. Project supported by the National Natural Science Foundation of China (Grant No. 61573017) and the Natural Science Foundation of Shaanxi Province, China (Grant No. 2016JQ6062).

  13. Key Management and Authentication in Ad Hoc Network based on Mobile Agent

    Directory of Open Access Journals (Sweden)

    Yi Zhang

    2009-08-01

    Full Text Available Key management and authentication is important to security of Mobile Ad Hoc network (MANET. Based on the (t, n threshold cryptography, this paper introduced mobile agents to exchange private key and network topological information with nodes in the network. This method avoids a centralized certification authority to distribute the public keys and the certificates, thus enhances security. Carrying private key and some state variables, mobile agents navigate in the network according to visitsbalance policy, namely, node with the least visits would be first visited by mobile agent. Any t nodes in the network can cooperate to perform an authentication upon a new node wanting to join the network. Experimental results show that the mobile agent performs very well for improving the success ratio of authentication and enhance security while reducing the communication overhead and resource consumption.

  14. Automatic self-configuration of the logical network using distributed software agents

    OpenAIRE

    Marzo i Lázaro, Josep Lluís; Vilà Talleda, Pere; Bueno Delgado, Antonio; Fàbrega i Soler, Lluís; Calle Ortega, Eusebi

    2004-01-01

    We present a system for dynamic network resource configuration in environments with bandwidth reservation. The proposed system is completely distributed and automates the mechanisms for adapting the logical network to the offered load. The system is able to manage dynamically a logical network such as a virtual path network in ATM or a label switched path network in MPLS or GMPLS. The system design and implementation is based on a multi-agent system (MAS) which make the decisions of when and ...

  15. Distributed Agent-Based Networks in Support of Advanced Marine Corps Command and Control Concept

    Science.gov (United States)

    2012-09-01

    capabilities that Mobile Ad Hoc Networking ( MANET ) technologies can provide to the Marine Corps are just fully coming into view. These new...Management System, NMS, Tactical Mobile Ad hoc Networks, MANET , Agent-based, Policy-Based, Distributed Networks, Autonomic Networks 15. NUMBER OF...ABSTRACT The capabilities that Mobile Ad Hoc Networking ( MANET ) technologies can provide to the Marine Corps are just fully coming into view. These

  16. Complex between lignin and a Ti-based coupling agent

    DEFF Research Database (Denmark)

    Rasmussen, Jonas Stensgaard; Barsberg, Søren Talbro; Felby, Claus

    2014-01-01

    coating formulations would have a better performance if the adhesion to wood could be improved. In the present work, the chemical interaction between a titanium-based coupling agent, isopropyl triisostearoyl titanate (titanium agent, TA) and lignin has been studied by means of attenuated total reflectance...

  17. Complexity in Simplicity: Flexible Agent-based State Space Exploration

    DEFF Research Database (Denmark)

    Rasmussen, Jacob Illum; Larsen, Kim Guldstrand

    2007-01-01

    In this paper, we describe a new flexible framework for state space exploration based on cooperating agents. The idea is to let various agents with different search patterns explore the state space individually and communicate information about fruitful subpaths of the search tree to each other...

  18. Complexity in Simplicity: Flexible Agent-based State Space Exploration

    DEFF Research Database (Denmark)

    Rasmussen, Jacob Illum; Larsen, Kim Guldstrand

    2007-01-01

    In this paper, we describe a new flexible framework for state space exploration based on cooperating agents. The idea is to let various agents with different search patterns explore the state space individually and communicate information about fruitful subpaths of the search tree to each other...

  19. The complexity of older adults' social support networks.

    Science.gov (United States)

    Chaichanawirote, Uraiwan; Higgins, Patricia A

    2013-10-01

    The purpose of this study was to provide a detailed snapshot of the diversity of social support networks of 95 independent-living older adults (mean age = 76). Participants in the convenience sample were recruited from senior centers and a retirement community. Using the Arizona Social Support Interview Schedule and egocentric network analysis, participants' networks are described in terms of patterns, density, size of positive networks (available and utilized), size of negative networks (available and utilized), support need, and support satisfaction. Each participant and the identified members of his or her network were considered a complex adaptive system. Network boundary was 7 members; average network size was 6.22 members (SD = 1.50); network density was moderate (mean = 0.53, SD = 0.33); positive interaction networks were larger than negative networks; and overall, participants reported moderate support need (mean = 2.5, SD = 0.7) and high support satisfaction (mean = 5.9, SD = 1.0).

  20. Random representation of spatially embedded complex transportation networks

    CERN Document Server

    Hackl, Jürgen

    2016-01-01

    Random networks are increasingly used to analyse complex transportation networks, such as airline routes, roads and rail networks. So far, this research has been focused on describing the properties of the networks with the help of random networks, often without considering their spatial properties. In this article, a methodology is proposed to create random networks conserving their spatial properties. The produced random networks are not intended to be an accurate model of the real-world network being investigated, but are to be used to gain insight into the functioning of the network taking into consideration its spatial properties, which has potential to be useful in many types of analysis, e.g. estimating the network related risk. The proposed methodology combines a spatial non-homogeneous point process for vertex creation, which accounts for the spatial distribution of vertices, considering clustering effects of the network and a hybrid connection model for the edge creation. To illustrate the ability o...

  1. Multiple Partial Attacks on Complex Networks

    Institute of Scientific and Technical Information of China (English)

    YIN Yan-Ping; ZHANG Duan-Ming; TAN Jin; PAN Gui-Jun; HE Min-Hua

    2008-01-01

    We numerically investigate the effect of four kinds of partial attacks of multiple targets on the Barabási-Albert (BA) scale-free network and the Erd(o)s-Rényi (ER) random network.Comparing with the effect of single target complete knockout we find that partial attacks of multiple targets may produce an effect higher than the complete knockout of a single target on both BA scale-free network and ER random network.We also find that the BA ecale-free network seems to be more susceptible to multi-target partial attacks than the ER random network.

  2. Missing and spurious interactions and the reconstruction of complex networks

    CERN Document Server

    Guimera, R; 10.1073/pnas.0908366106

    2010-01-01

    Network analysis is currently used in a myriad of contexts: from identifying potential drug targets to predicting the spread of epidemics and designing vaccination strategies, and from finding friends to uncovering criminal activity. Despite the promise of the network approach, the reliability of network data is a source of great concern in all fields where complex networks are studied. Here, we present a general mathematical and computational framework to deal with the problem of data reliability in complex networks. In particular, we are able to reliably identify both missing and spurious interactions in noisy network observations. Remarkably, our approach also enables us to obtain, from those noisy observations, network reconstructions that yield estimates of the true network properties that are more accurate than those provided by the observations themselves. Our approach has the potential to guide experiments, to better characterize network data sets, and to drive new discoveries.

  3. Analysis and perturbation of degree correlation in complex networks

    CERN Document Server

    Xiang, Ju; Hu, Tao; Zhang, Yan

    2015-01-01

    Degree correlation is an important topological property common to many real-world networks. In this paper, the statistical measures for characterizing the degree correlation in networks are investigated analytically. We give an exact proof of the consistency for the statistical measures, reveal the general linear relation in the degree correlation, which provide a simple and interesting perspective on the analysis of the degree correlation in complex networks. By using the general linear analysis, we investigate the perturbation of the degree correlation in complex networks caused by the addition of few nodes and the rich club. The results show that the assortativity of homogeneous networks such as the ER graphs is easily to be affected strongly by the simple structural changes, while it has only slight variation for heterogeneous networks with broad degree distribution such as the scale-free networks. Clearly, the homogeneous networks are more sensitive for the perturbation than the heterogeneous networks.

  4. Research and Design of Network Management Construction Based on Mobile AGENT

    Institute of Scientific and Technical Information of China (English)

    2007-01-01

    The technical characters of mobile agent (MA) originated in the distributional artificial intelligence domain is introduced. A network management construc- tion based on agent (NMCA) is then proposed. The NMCA structure features are elaborated in detail. A prototype design of NMCA is given by using the jKQML programming. The establishment of NMCA platform will be helpful to reduce the correspondence load of network management and improves the efficiency and the expansion ability of network management systems.

  5. Collective navigation of complex networks: Participatory greedy routing

    CERN Document Server

    Kleineberg, Kaj-Kolja

    2016-01-01

    Many networks are used to transfer information or goods, in other words, they are navigated. The larger the network, the more difficult it is to navigate efficiently. Indeed, information routing in the Internet faces serious scalability problems due to its rapid growth, recently accelerated by the rise of the Internet of Things. Large networks like the Internet can be navigated efficiently if nodes, or agents, actively forward information based on hidden maps underlying these systems. However, in reality most agents will deny to forward messages, which has a cost, and navigation is impossible. Can we design appropriate incentives that lead to participation and global navigability? Here, we present an evolutionary game where agents share the value generated by successful delivery of information or goods. We show that global navigability can emerge, but its complete breakdown is possible as well. Furthermore, we show that the system tends to self-organize into local clusters of agents who participate in the nav...

  6. Leveraging Social Networks to Motivate Humans to Train Agents

    NARCIS (Netherlands)

    G. Li; H. Hung; S. Whiteson; W.B. Knox

    2014-01-01

    Learning from rewards generated by a human trainer observing the agent in action has been demonstrated to be an effective method for humans to teach an agent to perform challenging tasks. However, how to make the agent learn most efficiently from these kinds of human reward is still under-addressed.

  7. Analysis of Semantic Networks using Complex Networks Concepts

    DEFF Research Database (Denmark)

    Ortiz-Arroyo, Daniel

    2013-01-01

    In this paper we perform a preliminary analysis of semantic networks to determine the most important terms that could be used to optimize a summarization task. In our experiments, we measure how the properties of a semantic network change, when the terms in the network are removed. Our preliminar...

  8. Network resources management in a multi-agent system: A simulative approach

    Directory of Open Access Journals (Sweden)

    Ganiyu A. Aderounmu

    2010-09-01

    Full Text Available Multi-agent systems (i.e. systems comprising many agents have been proposed for many Internet and distributed applications. The proposed systems have little or no consideration of the effects of this multi-agent approach on network resources. In this paper, we presented a simulation assessment of the effect of multi-agent systems on network resources. The routing scheme of the agents was formulated based on the travelling salesman problem. Lightweight agent (LWA controller was modelled using a fuzzy logic toolbox in the MATLAB environment. The performance metrics of bandwidth usage, response time and throughput were used to compare the network resources usage by different groups of LWAs (10 LWAs, 40 LWAs, 100 LWAs, 150 LWAs during their computational task on the network. Java programs were written for the implementation of lightweight agents in the simulation. The inputs to the system were realised by multiplicative pseudorandom number generation during the simulation. The simulation result analysis was carried out based on the performance metrics stated above for the four groups of agents. Increasing the number of LWAs in a simulated multi-agent system decreased the response time but increased the throughput and the bandwidth usage. All these performance measures should be considered for developing countries with bandwidth shortages, because having too many agents in a multi-agent system could result in bandwidth wastages.

  9. Active defense scheme against DDoS based on mobile agent and network control in network confrontation

    Science.gov (United States)

    Luo, Rong; Li, Junshan; Ye, Xia; Wang, Rui

    2013-03-01

    In order to effective defend DDoS attacks in network confrontation, an active defense scheme against DDoS is built based on Mobile Agent and network control. A distributed collaborative active defense model is constructed by using mobile agent technology and encapsulating a variety of DDoS defense techniques. Meanwhile the network control theory is applied to establish a network confrontation's control model for DDoS to control the active defense process. It provides a new idea to solve the DDoS problem.

  10. Collective Almost Synchronisation in Complex Networks

    Science.gov (United States)

    Baptista, Murilo S.; Ren, Hai-Peng; Swarts, Johen C. M.; Carareto, Rodrigo; Nijmeijer, Henk; Grebogi, Celso

    2012-01-01

    This work introduces the phenomenon of Collective Almost Synchronisation (CAS), which describes a universal way of how patterns can appear in complex networks for small coupling strengths. The CAS phenomenon appears due to the existence of an approximately constant local mean field and is characterised by having nodes with trajectories evolving around periodic stable orbits. Common notion based on statistical knowledge would lead one to interpret the appearance of a local constant mean field as a consequence of the fact that the behaviour of each node is not correlated to the behaviours of the others. Contrary to this common notion, we show that various well known weaker forms of synchronisation (almost, time-lag, phase synchronisation, and generalised synchronisation) appear as a result of the onset of an almost constant local mean field. If the memory is formed in a brain by minimising the coupling strength among neurons and maximising the number of possible patterns, then the CAS phenomenon is a plausible explanation for it. PMID:23144851

  11. Collective almost synchronisation in complex networks.

    Directory of Open Access Journals (Sweden)

    Murilo S Baptista

    Full Text Available This work introduces the phenomenon of Collective Almost Synchronisation (CAS, which describes a universal way of how patterns can appear in complex networks for small coupling strengths. The CAS phenomenon appears due to the existence of an approximately constant local mean field and is characterised by having nodes with trajectories evolving around periodic stable orbits. Common notion based on statistical knowledge would lead one to interpret the appearance of a local constant mean field as a consequence of the fact that the behaviour of each node is not correlated to the behaviours of the others. Contrary to this common notion, we show that various well known weaker forms of synchronisation (almost, time-lag, phase synchronisation, and generalised synchronisation appear as a result of the onset of an almost constant local mean field. If the memory is formed in a brain by minimising the coupling strength among neurons and maximising the number of possible patterns, then the CAS phenomenon is a plausible explanation for it.

  12. Collective almost synchronisation in complex networks.

    Science.gov (United States)

    Baptista, Murilo S; Ren, Hai-Peng; Swarts, Johen C M; Carareto, Rodrigo; Nijmeijer, Henk; Grebogi, Celso

    2012-01-01

    This work introduces the phenomenon of Collective Almost Synchronisation (CAS), which describes a universal way of how patterns can appear in complex networks for small coupling strengths. The CAS phenomenon appears due to the existence of an approximately constant local mean field and is characterised by having nodes with trajectories evolving around periodic stable orbits. Common notion based on statistical knowledge would lead one to interpret the appearance of a local constant mean field as a consequence of the fact that the behaviour of each node is not correlated to the behaviours of the others. Contrary to this common notion, we show that various well known weaker forms of synchronisation (almost, time-lag, phase synchronisation, and generalised synchronisation) appear as a result of the onset of an almost constant local mean field. If the memory is formed in a brain by minimising the coupling strength among neurons and maximising the number of possible patterns, then the CAS phenomenon is a plausible explanation for it.

  13. How can social networks ever become complex? Modelling the emergence of complex networks from local social exchanges

    NARCIS (Netherlands)

    Pujol, Josep M.; Flache, Andreas; Delgado, Jordi; Sangüesa, Ramon; Sanguessa, R.

    2005-01-01

    Small-world and power-law network structures have been prominently proposed as models of large networks. However, the assumptions of these models usually-lack sociological grounding. We present a computational model grounded in social exchange theory. Agents search attractive exchange partners in a

  14. Prediction Model of Antibacterial Activities for Inorganic Antibacterial Agents Based on Artificial Neural Networks

    Institute of Scientific and Technical Information of China (English)

    刘雪峰; 张利; 涂铭旌

    2004-01-01

    Quantitatively evaluation of antibacterial activities of inorganic antibacterial agents is an urgent problem to be solved. Using experimental data by an orthogonal design, a prediction model of the relation between conditions of preparing inorganic antibacterial agents and their antibacterial activities has been developed. This is accomplished by introducing BP artificial neural networks in the study of inorganic antibacterial agents..It provides a theoretical support for the development and research on inorganic antibacterial agents.

  15. Stochastic simulation of HIV population dynamics through complex network modelling

    NARCIS (Netherlands)

    Sloot, P.M.A.; Ivanov, S.V.; Boukhanovsky, A.V.; van de Vijver, D.A.M.C.; Boucher, C.A.B.

    2008-01-01

    We propose a new way to model HIV infection spreading through the use of dynamic complex networks. The heterogeneous population of HIV exposure groups is described through a unique network degree probability distribution. The time evolution of the network nodes is modelled by a Markov process and

  16. Stochastic simulation of HIV population dynamics through complex network modelling

    NARCIS (Netherlands)

    Sloot, P. M. A.; Ivanov, S. V.; Boukhanovsky, A. V.; van de Vijver, D. A. M. C.; Boucher, C. A. B.

    We propose a new way to model HIV infection spreading through the use of dynamic complex networks. The heterogeneous population of HIV exposure groups is described through a unique network degree probability distribution. The time evolution of the network nodes is modelled by a Markov process and

  17. Distance metric learning for complex networks: Towards size-independent comparison of network structures

    Science.gov (United States)

    Aliakbary, Sadegh; Motallebi, Sadegh; Rashidian, Sina; Habibi, Jafar; Movaghar, Ali

    2015-02-01

    Real networks show nontrivial topological properties such as community structure and long-tail degree distribution. Moreover, many network analysis applications are based on topological comparison of complex networks. Classification and clustering of networks, model selection, and anomaly detection are just some applications of network comparison. In these applications, an effective similarity metric is needed which, given two complex networks of possibly different sizes, evaluates the amount of similarity between the structural features of the two networks. Traditional graph comparison approaches, such as isomorphism-based methods, are not only too time consuming but also inappropriate to compare networks with different sizes. In this paper, we propose an intelligent method based on the genetic algorithms for integrating, selecting, and weighting the network features in order to develop an effective similarity measure for complex networks. The proposed similarity metric outperforms state of the art methods with respect to different evaluation criteria.

  18. Recent Progress in Some Active Topics on Complex Networks

    Science.gov (United States)

    Gu, J.; Zhu, Y.; Guo, L.; Jiang, J.; Chi, L.; Li, W.; Wang, Q. A.; Cai, X.

    2015-04-01

    Complex networks have been extensively studied across many fields, especially in interdisciplinary areas. It has since long been recognized that topological structures and dynamics are important aspects for capturing the essence of complex networks. The recent years have also witnessed the emergence of several new elements which play important roles in network study. By combining the results of different research orientations in our group, we provide here a review of the recent advances in regards to spectral graph theory, opinion dynamics, interdependent networks, graph energy theory and temporal networks. We hope this will be helpful for the newcomers of those fields to discover new intriguing topics.

  19. Riemannian-geometric entropy for measuring network complexity

    Science.gov (United States)

    Franzosi, Roberto; Felice, Domenico; Mancini, Stefano; Pettini, Marco

    2016-06-01

    A central issue in the science of complex systems is the quantitative characterization of complexity. In the present work we address this issue by resorting to information geometry. Actually we propose a constructive way to associate with a—in principle, any—network a differentiable object (a Riemannian manifold) whose volume is used to define the entropy. The effectiveness of the latter in measuring network complexity is successfully proved through its capability of detecting a classical phase transition occurring in both random graphs and scale-free networks, as well as of characterizing small exponential random graphs, configuration models, and real networks.

  20. Classes of feedforward neural networks and their circuit complexity

    NARCIS (Netherlands)

    Shawe-Taylor, John S.; Anthony, Martin H.G.; Kern, Walter

    1992-01-01

    This paper aims to place neural networks in the context of boolean circuit complexity. We define appropriate classes of feedforward neural networks with specified fan-in, accuracy of computation and depth and using techniques of communication complexity proceed to show that the classes fit into a

  1. Knowledge spillover processes as complex networks

    Science.gov (United States)

    Konno, Tomohiko

    2016-11-01

    We introduce the model of knowledge spillover on networks. Knowledge spillover is a major source of economic growth; and is a representative externality in economic phenomena. We show that the model has the following four characteristics: (1) the long-run growth rate is not relevant to the mean degree, but is determined by the mean degree of the nearest neighbors; (2) the productivity level of a firm is proportional to the degree of the firm; (3) the long-run growth rate increases with the increasing heterogeneity of the network; and (4) of three representative networks, the largest growth rate is in scale-free networks and the least in regular networks.

  2. Communication and control for networked complex systems

    CERN Document Server

    Peng, Chen; Han, Qing-Long

    2015-01-01

    This book reports on the latest advances in the study of Networked Control Systems (NCSs). It highlights novel research concepts on NCSs; the analysis and synthesis of NCSs with special attention to their networked character; self- and event-triggered communication schemes for conserving limited network resources; and communication and control co-design for improving the efficiency of NCSs. The book will be of interest to university researchers, control and network engineers, and graduate students in the control engineering, communication and network sciences interested in learning the core principles, methods, algorithms and applications of NCSs.

  3. Vulnerability Analysis for Complex Networks Using Aggressive Abstraction

    CERN Document Server

    Colbaugh, Richard

    2010-01-01

    Large, complex networks are ubiquitous in nature and society, and there is great interest in developing rigorous, scalable methods for identifying and characterizing their vulnerabilities. This paper presents an approach for analyzing the dynamics of complex networks in which the network of interest is first abstracted to a much simpler, but mathematically equivalent, representation, the required analysis is performed on the abstraction, and analytic conclusions are then mapped back to the original network and interpreted there. We begin by identifying a broad and important class of complex networks which admit vulnerability-preserving, finite state abstractions, and develop efficient algorithms for computing these abstractions. We then propose a vulnerability analysis methodology which combines these finite state abstractions with formal analytics from theoretical computer science to yield a comprehensive vulnerability analysis process for networks of realworld scale and complexity. The potential of the prop...

  4. Robustness of Complex Networks under Attack and Repair

    Institute of Scientific and Technical Information of China (English)

    HU Bin; LI Fang; ZHOU Hou-Shun

    2009-01-01

    To study the robustness of complex networks under attack and repair,we introduce a repair model of complex networks.Based on the model,we introduce two new quantities,i.e.attack fraction f_a and the maximum degree of the nodes that have never been attacked K_a,to study analytically the critical attack fraction and the relati ve size of the giant component of complex networks under attack and repair,using the method of generating function.We show analytically and numerically that the repair strategy significantly enhances the robustness of the scale-free network and the effect of robustness improvement is better for the scale-free networks with a smaller degree exponent.We discuss the application of our theory in relation to the understanding of robustness of complex networks with reparability.

  5. Reconstructing complex networks with binary-state dynamics

    CERN Document Server

    Li, Jingwen; Lai, Ying-Cheng; Grebogi, Celso

    2015-01-01

    The prerequisite for our understanding of many complex networked systems lies in the reconstruction of network structure from measurable data. Although binary-state dynamics occurring in a broad class of complex networked systems in nature and society and has been intensively investigated, a general framework for reconstructing complex networks from binary states, the inverse problem, is lacking. Here we offer a general solution to the reconstruction problem by developing a data-based linearization approach for binary-state dynamics with linear, nonlinear, discrete and stochastic switching functions. The linearization allows us to convert the network reconstruction problem into a sparse signal reconstruction problem that can be resolved efficiently and credibly by convex optimization based on compressed sensing. The completely data-based linearization method and the sparse signal reconstruction constitutes a general framework for reconstructing complex networks without any knowledge of the binary-state dynami...

  6. Universal structural estimator and dynamics approximator for complex networks

    CERN Document Server

    Chen, Yu-Zhong

    2016-01-01

    Revealing the structure and dynamics of complex networked systems from observed data is of fundamental importance to science, engineering, and society. Is it possible to develop a universal, completely data driven framework to decipher the network structure and different types of dynamical processes on complex networks, regardless of their details? We develop a Markov network based model, sparse dynamical Boltzmann machine (SDBM), as a universal network structural estimator and dynamics approximator. The SDBM attains its topology according to that of the original system and is capable of simulating the original dynamical process. We develop a fully automated method based on compressive sensing and machine learning to find the SDBM. We demonstrate, for a large variety of representative dynamical processes on model and real world complex networks, that the equivalent SDBM can recover the network structure of the original system and predicts its dynamical behavior with high precision.

  7. Multi-Agent Framework in Visual Sensor Networks

    Directory of Open Access Journals (Sweden)

    J. M. Molina

    2007-01-01

    Full Text Available The recent interest in the surveillance of public, military, and commercial scenarios is increasing the need to develop and deploy intelligent and/or automated distributed visual surveillance systems. Many applications based on distributed resources use the so-called software agent technology. In this paper, a multi-agent framework is applied to coordinate videocamera-based surveillance. The ability to coordinate agents improves the global image and task distribution efficiency. In our proposal, a software agent is embedded in each camera and controls the capture parameters. Then coordination is based on the exchange of high-level messages among agents. Agents use an internal symbolic model to interpret the current situation from the messages from all other agents to improve global coordination.

  8. Recent Progress on the Resilience of Complex Networks

    Directory of Open Access Journals (Sweden)

    Jianxi Gao

    2015-10-01

    Full Text Available Many complex systems in the real world can be modeled as complex networks, which has captured in recent years enormous attention from researchers of diverse fields ranging from natural sciences to engineering. The extinction of species in ecosystems and the blackouts of power girds in engineering exhibit the vulnerability of complex networks, investigated by empirical data and analyzed by theoretical models. For studying the resilience of complex networks, three main factors should be focused on: the network structure, the network dynamics and the failure mechanism. In this review, we will introduce recent progress on the resilience of complex networks based on these three aspects. For the network structure, increasing evidence shows that biological and ecological networks are coupled with each other and that diverse critical infrastructures interact with each other, triggering a new research hotspot of “networks of networks” (NON, where a network is formed by interdependent or interconnected networks. The resilience of complex networks is deeply influenced by its interdependence with other networks, which can be analyzed and predicted by percolation theory. This review paper shows that the analytic framework for Energies 2015, 8 12188 NON yields novel percolation laws for n interdependent networks and also shows that the percolation theory of a single network studied extensively in physics and mathematics in the last 60 years is a specific limited case of the more general case of n interacting networks. Due to spatial constraints inherent in critical infrastructures, including the power gird, we also review the progress on the study of spatially-embedded interdependent networks, exhibiting extreme vulnerabilities compared to their non-embedded counterparts, especially in the case of localized attack. For the network dynamics, we illustrate the percolation framework and methods using an example of a real transportation system, where the

  9. Resilient distributed control in the presence of misbehaving agents in networked control systems.

    Science.gov (United States)

    Zeng, Wente; Chow, Mo-Yuen

    2014-11-01

    In this paper, we study the problem of reaching a consensus among all the agents in the networked control systems (NCS) in the presence of misbehaving agents. A reputation-based resilient distributed control algorithm is first proposed for the leader-follower consensus network. The proposed algorithm embeds a resilience mechanism that includes four phases (detection, mitigation, identification, and update), into the control process in a distributed manner. At each phase, every agent only uses local and one-hop neighbors' information to identify and isolate the misbehaving agents, and even compensate their effect on the system. We then extend the proposed algorithm to the leaderless consensus network by introducing and adding two recovery schemes (rollback and excitation recovery) into the current framework to guarantee the accurate convergence of the well-behaving agents in NCS. The effectiveness of the proposed method is demonstrated through case studies in multirobot formation control and wireless sensor networks.

  10. Research of Network Security Situational Assessment Quantization Based on Mobile Agent

    Science.gov (United States)

    Xiaorong, Cheng; Su, Lang; Mingxuan, Li

    As the security situational assessment widely applying to the computer network field, scholars have designed and implemented a large number of network security situational assessment methods. However, most works are based on local area network and single host, which is hardly to meet the demand of large-scale network security assessment. In this paper, we based on quantitative hierarchical network security situational assessment model, introduced the mobile agent technology, designed the distributed computing for large-scale network and evaluated the whole network security situation for future prediction.

  11. Unification of theoretical approaches for epidemic spreading on complex networks

    Science.gov (United States)

    Wang, Wei; Tang, Ming; Stanley, H. Eugene; Braunstein, Lidia A.

    2017-03-01

    Models of epidemic spreading on complex networks have attracted great attention among researchers in physics, mathematics, and epidemiology due to their success in predicting and controlling scenarios of epidemic spreading in real-world scenarios. To understand the interplay between epidemic spreading and the topology of a contact network, several outstanding theoretical approaches have been developed. An accurate theoretical approach describing the spreading dynamics must take both the network topology and dynamical correlations into consideration at the expense of increasing the complexity of the equations. In this short survey we unify the most widely used theoretical approaches for epidemic spreading on complex networks in terms of increasing complexity, including the mean-field, the heterogeneous mean-field, the quench mean-field, dynamical message-passing, link percolation, and pairwise approximation. We build connections among these approaches to provide new insights into developing an accurate theoretical approach to spreading dynamics on complex networks.

  12. Complex network representation of multiagent systems with cooperative and competitive interactions

    Directory of Open Access Journals (Sweden)

    Leonidas Facundo Caram

    2014-04-01

    Full Text Available The dynamic behavior of Multi-Agent Systems (MAS is analyzed in the context of a modified Lotka-Volterra model. The interaction strength is determined by the difference of agent sizes: as the difference increases, the interaction is weaker. Competitive and cooperative scenarios are analyzed, showing clusters of agents in the stationary state. However, meantime in the competitive scenario the agent sizes are constrained to be non greater than the capacity value (beta = 1, in the cooperative scenario, they are allowed to exceed such capacity making clear the advantages of cooperation. The complex network representation is introduced in order to enhance the role of agent sizes and their one-on-one interactions in the dynamic behavior of the system.

  13. Mechanisms and dynamics of cooperation and competition emergence in complex networked systems

    Science.gov (United States)

    Gianetto, David A.

    Cooperative behavior is a pervasive phenomenon in human interactions and yet how it can evolve and become established, through the selfish process of natural selection, is an enduring puzzle. These behaviors emerge when agents interact in a structured manner; even so, the key structural factors that affect cooperation are not well understood. Moreover, the literature often considers cooperation a single attribute of primitive agents who do not react to environmental changes but real-world actors are more perceptive. The present work moves beyond these assumptions by evolving more realistic game participants, with memories of the past, on complex networks. Agents play repeated games with a three-part Markovian strategy that allows us to separate the cooperation phenomenon into trust, reciprocity, and forgiveness characteristics. Our results show that networks matter most when agents gain the most by acting in a selfish manner, irrespective of how much they may lose by cooperating; since the context provided by neighborhoods inhibits greedy impulses that agents otherwise succumb to in isolation. Network modularity is the most important driver of cooperation emergence in these high-stakes games. However, modularity fails to tell the complete story. Modular scale-free graphs impede cooperation when close coordination is required, partially due to the acyclic nature of scale-free network models. To achieve the highest cooperation in diverse social conditions, both high modularity, low connectivity within modules, and a rich network of long cycles become important. With these findings in hand, we study the influence of networks on coordination and competition within the federal health care insurance exchange. In this applied study, we show that systemic health care coordination is encouraged by the emergent insurance network. The network helps underpin the viability of the exchange and provides an environment of stronger competition once a critical-mass of insurers have

  14. Temporal node centrality in complex networks

    Science.gov (United States)

    Kim, Hyoungshick; Anderson, Ross

    2012-02-01

    Many networks are dynamic in that their topology changes rapidly—on the same time scale as the communications of interest between network nodes. Examples are the human contact networks involved in the transmission of disease, ad hoc radio networks between moving vehicles, and the transactions between principals in a market. While we have good models of static networks, so far these have been lacking for the dynamic case. In this paper we present a simple but powerful model, the time-ordered graph, which reduces a dynamic network to a static network with directed flows. This enables us to extend network properties such as vertex degree, closeness, and betweenness centrality metrics in a very natural way to the dynamic case. We then demonstrate how our model applies to a number of interesting edge cases, such as where the network connectivity depends on a small number of highly mobile vertices or edges, and show that our centrality definition allows us to track the evolution of connectivity. Finally we apply our model and techniques to two real-world dynamic graphs of human contact networks and then discuss the implication of temporal centrality metrics in the real world.

  15. Scaling Behavior and Phase Change in Complex Network

    Directory of Open Access Journals (Sweden)

    Wei Cheng

    2013-11-01

    Full Text Available Scaling behavior is a extremely typical phenomenon in complex system research, as well as it can act that many Macro indicators in system or distribution function of some variables meet exactly power-law behavior, which possesses different kinds of Exponents. In this article, according to Phase Change concept in Physics, it is researched that the nature in critical state of complex network with Seepage model, and it is totally stated that the basic reason of Self-similar behavior, Fractal behavior, and so on, and also Phase Change in complex network in critical state of complex network in accord with power-law distribution.    

  16. Complex-valued neural networks advances and applications

    CERN Document Server

    Hirose, Akira

    2013-01-01

    Presents the latest advances in complex-valued neural networks by demonstrating the theory in a wide range of applications Complex-valued neural networks is a rapidly developing neural network framework that utilizes complex arithmetic, exhibiting specific characteristics in its learning, self-organizing, and processing dynamics. They are highly suitable for processing complex amplitude, composed of amplitude and phase, which is one of the core concepts in physical systems to deal with electromagnetic, light, sonic/ultrasonic waves as well as quantum waves, namely, electron and

  17. Network medicine approaches to the genetics of complex diseases.

    Science.gov (United States)

    Silverman, Edwin K; Loscalzo, Joseph

    2012-08-01

    Complex diseases are caused by perturbations of biological networks. Genetic analysis approaches focused on individual genetic determinants are unlikely to characterize the network architecture of complex diseases comprehensively. Network medicine, which applies systems biology and network science to complex molecular networks underlying human disease, focuses on identifying the interacting genes and proteins which lead to disease pathogenesis. The long biological path between a genetic risk variant and development of a complex disease involves a range of biochemical intermediates, including coding and non-coding RNA, proteins, and metabolites. Transcriptomics, proteomics, metabolomics, and other -omics technologies have the potential to provide insights into complex disease pathogenesis, especially if they are applied within a network biology framework. Most previous efforts to relate genetics to -omics data have focused on a single -omics platform; the next generation of complex disease genetics studies will require integration of multiple types of -omics data sets in a network context. Network medicine may also provide insight into complex disease heterogeneity, serve as the basis for new disease classifications that reflect underlying disease pathogenesis, and guide rational therapeutic and preventive strategies.

  18. Natural Time Analysis and Complex Networks

    Science.gov (United States)

    Sarlis, Nicholas; Skordas, Efthimios; Lazaridou, Mary; Varotsos, Panayiotis

    2013-04-01

    Here, we review the analysis of complex time series in a new time domain, termed natural time, introduced by our group [1,2]. This analysis conforms to the desire to reduce uncertainty and extract signal information as much as possible [3]. It enables [4] the distinction between the two origins of self-similarity when analyzing data from complex systems, i.e., whether self-similarity solely results from long-range temporal correlations (the process's memory only) or solely from the process's increments infinite variance (heavy tails in their distribution). Natural time analysis captures the dynamical evolution of a complex system and identifies [5] when the system enters a critical stage. Hence, this analysis plays a key role in predicting forthcoming catastrophic events in general. Relevant examples, compiled in a recent monograph [6], have been presented in diverse fields, including Solid State Physics [7], Statistical Physics (for example systems exhibiting self-organized criticality [8]), Cardiology [9,10], Earth Sciences [11] (Geophysics, Seismology), Environmental Sciences (e.g. see Ref. [12]), etc. Other groups have proposed and developed a network approach to earthquake events with encouraging results. A recent study [13] reveals that this approach is strengthened if we combine it with natural time analysis. In particular, we find [13,14] that the study of the spatial distribution of the variability [15] of the order parameter fluctuations, defined in natural time, provides important information on the dynamical evolution of the system. 1. P. Varotsos, N. Sarlis, and E. Skordas, Practica of Athens Academy, 76, 294-321, 2001. 2. P.A. Varotsos, N.V. Sarlis, and E.S. Skordas, Phys. Rev. E, 66, 011902 , 2002. 3. S. Abe, N.V. Sarlis, E.S. Skordas, H.K. Tanaka and P.A. Varotsos, Phys. Rev. Lett. 94, 170601, 2005. 4. P.A. Varotsos, N.V. Sarlis, E.S. Skordas, H.K. Tanaka and M.S. Lazaridou, Phys. Rev. E, 74, 021123, 2006. 5. P.Varotsos, N. V. Sarlis, E. S. Skordas

  19. Bypass rewiring and robustness of complex networks

    Science.gov (United States)

    Park, Junsang; Hahn, Sang Geun

    2016-08-01

    A concept of bypass rewiring is introduced, and random bypass rewiring is analytically and numerically investigated with simulations. Our results show that bypass rewiring makes networks robust against removal of nodes including random failures and attacks. In particular, random bypass rewiring connects all nodes except the removed nodes on an even degree infinite network and makes the percolation threshold 0 for arbitrary occupation probabilities. In our example, the even degree network is more robust than the original network with random bypass rewiring, while the original network is more robust than the even degree networks without random bypass. We propose a greedy bypass rewiring algorithm which guarantees the maximum size of the largest component at each step, assuming which node will be removed next is unknown. The simulation result shows that the greedy bypass rewiring algorithm improves the robustness of the autonomous system of the Internet under attacks more than random bypass rewiring.

  20. Bypass Rewiring and Robustness of Complex Networks

    CERN Document Server

    Park, Junsang

    2016-01-01

    A concept of bypass rewiring is introduced and random bypass rewiring is analytically and numerically investigated with simulations. Our results show that bypass rewiring makes networks robust against removal of nodes including random failures and attacks. Especially, random bypass rewiring connects all nodes except the removed nodes on an even degree infinite network and makes the percolation threshold $0$ for arbitrary occupation probabilities. In our example, the even degree network is more robust than the original network with random bypass rewiring while the original network is more robust than the even degree networks without random bypass. We propose a greedy bypass rewiring algorithm which guarantees the maximum size of the largest component at each step, assuming which node will be removed next is unknown. The simulation result shows that the greedy bypass rewiring algorithm improves the robustness of the autonomous system of the Internet under attacks more than random bypass rewiring.

  1. A Complex-Network Perspective on Alexander's Wholeness

    CERN Document Server

    Jiang, Bin

    2016-01-01

    The wholeness, conceived and developed by Christopher Alexander, is what exists to some degree or other in space and matter, and can be described by precise mathematical language. However, it remains mysterious and hard to grasp. This paper develops a complex network perspective on the wholeness to better understand the nature of order or beauty, and apply it into sustainable design. I bring together a set of complexity-science subjects such as complex networks, fractal geometry, and in particular underlying scaling hierarchy derived by head/tail breaks, in order to make Alexander's profound thoughts more accessible to design practitioners and complexity-science researchers. Through several case studies (some of which Alexander studied), I demonstrate that the complex-network perspective helps reduce the mystery of wholeness and brings new insights to Alexander's thoughts on the concept of wholeness or objective beauty in fine structures. The complex-network perspective enables us to see things in their whole...

  2. Epidemics and rumours in complex networks

    CERN Document Server

    Draief, Moez

    2009-01-01

    Information propagation through peer-to-peer systems, online social systems, wireless mobile ad hoc networks and other modern structures can be modelled as an epidemic on a network of contacts. Understanding how epidemic processes interact with network topology allows us to predict ultimate course, understand phase transitions and develop strategies to control and optimise dissemination. This book is a concise introduction for applied mathematicians and computer scientists to basic models, analytical tools and mathematical and algorithmic results. Mathematical tools introduced include coupling

  3. Visualization of Complex Networks Based on Dyadic Curvelet Transform

    Directory of Open Access Journals (Sweden)

    Kaoru Hirota

    2006-07-01

    Full Text Available A visualization method is proposed for understanding the structure of complex networks based on an extended Curvelet transform named Dyadic Curvelet Transform (DClet. The proposed visualization method comes to answer specific questions about structures of complex networks by mapping data into orthogonal localized events with a directional component via the Cartesian sampling sets of detail coefficients. It behaves in the same matter as human visual system, seeing in terms of segments and distinguishing them by scale and orientation. Compressing the network is another fact. The performance of the proposed method is evaluated by two different networks with structural properties of small world networks with N = 16 vertices, and a globally coupled network with size N = 1024 and 523 776 edges. As the most large scale real networks are not fully connected, it is tested on the telecommunication network of Iran as a real extremely complex network with 92 intercity switching vertices, 706 350 E1 traffic channels and 315 525 transmission channels. It is shown that the proposed method performs as a simulation tool for successfully design of network and establishing the necessary group sizes. It can clue the network designer in on all structural properties that network has.

  4. Pinning synchronization of networked multi-agent systems:spectral analysis

    Institute of Scientific and Technical Information of China (English)

    Linying XIANG; Fei CHEN; Guanrong CHEN

    2015-01-01

    Pinning synchronization of a networked multi-agent system with a directed communication topology is investigated from a spectral analysis approach. Some new types of synchronized regions for networked systems with different nonlinear agent dynamics and inner coupling structures are discovered. The eigenvalue distributions of the coupling and control matrices for different types of directed networks are obtained. The effects of the network topology, pinning density and pinning strength on the network synchronizability are examined through extensive numerical simulations. It is shown that the synchronizability of the pinned network can be effectively improved by increasing pinning density and pinning strength for some types of synchronized regions, whereas too large the pinning density and pinning strength will lead to desynchronization for other types. It is found that directed random networks are not always easier to synchronize than directed small-world networks, and a denser eigenvalue distribution may not always imply better synchronizability.

  5. Synchronization of oscillators in complex networks

    Indian Academy of Sciences (India)

    Louis M Pecora

    2008-06-01

    Theory of identical or complete synchronization of identical oscillators in arbitrary networks is introduced. In addition, several graph theory concepts and results that augment the synchronization theory and a tie in closely to random, semirandom, and regular networks are introduced. Combined theories are used to explore and compare three types of semirandom networks for their efficacy in synchronizing oscillators. It is shown that the simplest -cycle augmented by a few random edges or links are the most efficient network that will guarantee good synchronization.

  6. Distributed coordination of heterogeneous agents using a semantic overlay network and a goal-directed graphplan planner.

    Directory of Open Access Journals (Sweden)

    António Luís Lopes

    Full Text Available In this paper, we describe a distributed coordination system that allows agents to seamlessly cooperate in problem solving by partially contributing to a problem solution and delegating the subproblems for which they do not have the required skills or knowledge to appropriate agents. The coordination mechanism relies on a dynamically built semantic overlay network that allows the agents to efficiently locate, even in very large unstructured networks, the necessary skills for a specific problem. Each agent performs partial contributions to the problem solution using a new distributed goal-directed version of the Graphplan algorithm. This new goal-directed version of the original Graphplan algorithm provides an efficient solution to the problem of "distraction", which most forward-chaining algorithms suffer from. We also discuss a set of heuristics to be used in the backward-search process of the planning algorithm in order to distribute this process amongst idle agents in an attempt to find a solution in less time. The evaluation results show that our approach is effective in building a scalable and efficient agent society capable of solving complex distributable problems.

  7. Secure mobile agent for telemedicine based on P2P networks.

    Science.gov (United States)

    Hsu, Wen-Shin; Pan, Jiann-I

    2013-06-01

    Exploring intelligent mobile agent (MA) technology for assisting medical services or transmitting personal patient-health information in telemedicine applications has been widely investigated. Conversely, peer-to-peer (P2P) networking has become one of the most popular applications used in the Internet because of its benefits for easy-to-manage resources and because it balances workloads. Therefore, constructing an agent-based telemedicine platform based on P2P networking architecture is necessary. The main purpose of this paper is to construct a safe agent-based telemedicine that based on P2P networking architecture. Two themes are addressed in this paper: (a) the P2P network architecture for an agent-based telemedicine service, and (b) the security mechanisms for the proposed telemedicine networking architecture. When an MA contains patient information and migrates from one host to another through the Internet, it can be attacked by other software agents or agent platforms that can illegally access patient information. The proposed P2P network architecture is based on the JXTA protocol and provides two types of telemedicine service models: the predictable service model and unpredictable service model. This architecture employs a two-layer safety mechanism for MAs (i.e., time-limited black boxes and RSA undetachable signature technologies), to provide a secure solution for agent-based telemedicine services.

  8. Decision support systems and methods for complex networks

    Energy Technology Data Exchange (ETDEWEB)

    Huang, Zhenyu [Richland, WA; Wong, Pak Chung [Richland, WA; Ma, Jian [Richland, WA; Mackey, Patrick S [Richland, WA; Chen, Yousu [Richland, WA; Schneider, Kevin P [Seattle, WA

    2012-02-28

    Methods and systems for automated decision support in analyzing operation data from a complex network. Embodiments of the present invention utilize these algorithms and techniques not only to characterize the past and present condition of a complex network, but also to predict future conditions to help operators anticipate deteriorating and/or problem situations. In particular, embodiments of the present invention characterize network conditions from operation data using a state estimator. Contingency scenarios can then be generated based on those network conditions. For at least a portion of all of the contingency scenarios, risk indices are determined that describe the potential impact of each of those scenarios. Contingency scenarios with risk indices are presented visually as graphical representations in the context of a visual representation of the complex network. Analysis of the historical risk indices based on the graphical representations can then provide trends that allow for prediction of future network conditions.

  9. Evolving Chart Pattern Sensitive Neural Network Based Forex Trading Agents

    CERN Document Server

    Sher, Gene I

    2011-01-01

    Though machine learning has been applied to the foreign exchange market for quiet some time now, and neural networks have been shown to yield good results, in modern approaches neural network systems are optimized through the traditional methods, and their input signals are vectors containing prices and other indicator elements. The aim of this paper is twofold, the presentation and testing of the application of topology and weight evolving artificial neural network (TWEANN) systems to automated currency trading, and the use of chart images as input to a geometrical regularity aware indirectly encoded neural network systems. This paper presents the benchmark results of neural network based automated currency trading systems evolved using TWEANNs, and compares the generalization capabilities of these direct encoded neural networks which use the standard price vector inputs, and the indirect (substrate) encoded neural networks which use chart images as input. The TWEANN algorithm used to evolve these currency t...

  10. Exploring the morphospace of communication efficiency in complex networks.

    Science.gov (United States)

    Goñi, Joaquín; Avena-Koenigsberger, Andrea; Velez de Mendizabal, Nieves; van den Heuvel, Martijn P; Betzel, Richard F; Sporns, Olaf

    2013-01-01

    Graph theoretical analysis has played a key role in characterizing global features of the topology of complex networks, describing diverse systems such as protein interactions, food webs, social relations and brain connectivity. How system elements communicate with each other depends not only on the structure of the network, but also on the nature of the system's dynamics which are constrained by the amount of knowledge and resources available for communication processes. Complementing widely used measures that capture efficiency under the assumption that communication preferentially follows shortest paths across the network ("routing"), we define analytic measures directed at characterizing network communication when signals flow in a random walk process ("diffusion"). The two dimensions of routing and diffusion efficiency define a morphospace for complex networks, with different network topologies characterized by different combinations of efficiency measures and thus occupying different regions of this space. We explore the relation of network topologies and efficiency measures by examining canonical network models, by evolving networks using a multi-objective optimization strategy, and by investigating real-world network data sets. Within the efficiency morphospace, specific aspects of network topology that differentially favor efficient communication for routing and diffusion processes are identified. Charting regions of the morphospace that are occupied by canonical, evolved or real networks allows inferences about the limits of communication efficiency imposed by connectivity and dynamics, as well as the underlying selection pressures that have shaped network topology.

  11. Exploring the morphospace of communication efficiency in complex networks.

    Directory of Open Access Journals (Sweden)

    Joaquín Goñi

    Full Text Available Graph theoretical analysis has played a key role in characterizing global features of the topology of complex networks, describing diverse systems such as protein interactions, food webs, social relations and brain connectivity. How system elements communicate with each other depends not only on the structure of the network, but also on the nature of the system's dynamics which are constrained by the amount of knowledge and resources available for communication processes. Complementing widely used measures that capture efficiency under the assumption that communication preferentially follows shortest paths across the network ("routing", we define analytic measures directed at characterizing network communication when signals flow in a random walk process ("diffusion". The two dimensions of routing and diffusion efficiency define a morphospace for complex networks, with different network topologies characterized by different combinations of efficiency measures and thus occupying different regions of this space. We explore the relation of network topologies and efficiency measures by examining canonical network models, by evolving networks using a multi-objective optimization strategy, and by investigating real-world network data sets. Within the efficiency morphospace, specific aspects of network topology that differentially favor efficient communication for routing and diffusion processes are identified. Charting regions of the morphospace that are occupied by canonical, evolved or real networks allows inferences about the limits of communication efficiency imposed by connectivity and dynamics, as well as the underlying selection pressures that have shaped network topology.

  12. Optimal structure of complex networks for minimizing traffic congestion.

    Science.gov (United States)

    Zhao, Liang; Cupertino, Thiago Henrique; Park, Kwangho; Lai, Ying-Cheng; Jin, Xiaogang

    2007-12-01

    To design complex networks to minimize traffic congestion, it is necessary to understand how traffic flow depends on network structure. We study data packet flow on complex networks, where the packet delivery capacity of each node is not fixed. The optimal configuration of capacities to minimize traffic congestion is derived and the critical packet generating rate is determined, below which the network is at a free flow state but above which congestion occurs. Our analysis reveals a direct relation between network topology and traffic flow. Optimal network structure, free of traffic congestion, should have two features: uniform distribution of load over all nodes and small network diameter. This finding is confirmed by numerical simulations. Our analysis also makes it possible to theoretically compare the congestion conditions for different types of complex networks. In particular, we find that network with low critical generating rate is more susceptible to congestion. The comparison has been made on the following complex-network topologies: random, scale-free, and regular.

  13. Using complex networks to characterize international business cycles.

    Directory of Open Access Journals (Sweden)

    Petre Caraiani

    Full Text Available BACKGROUND: There is a rapidly expanding literature on the application of complex networks in economics that focused mostly on stock markets. In this paper, we discuss an application of complex networks to study international business cycles. METHODOLOGY/PRINCIPAL FINDINGS: We construct complex networks based on GDP data from two data sets on G7 and OECD economies. Besides the well-known correlation-based networks, we also use a specific tool for presenting causality in economics, the Granger causality. We consider different filtering methods to derive the stationary component of the GDP series for each of the countries in the samples. The networks were found to be sensitive to the detrending method. While the correlation networks provide information on comovement between the national economies, the Granger causality networks can better predict fluctuations in countries' GDP. By using them, we can obtain directed networks allows us to determine the relative influence of different countries on the global economy network. The US appears as the key player for both the G7 and OECD samples. CONCLUSION: The use of complex networks is valuable for understanding the business cycle comovements at an international level.

  14. Macroscopic description of complex adaptive networks co-evolving with dynamic node states

    CERN Document Server

    Wiedermann, Marc; Heitzig, Jobst; Lucht, Wolfgang; Kurths, Jürgen

    2015-01-01

    In many real-world complex systems, the time-evolution of the network's structure and the dynamic state of its nodes are closely entangled. Here, we study opinion formation and imitation on an adaptive complex network which is dependent on the individual dynamic state of each node and vice versa to model the co-evolution of renewable resources with the dynamics of harvesting agents on a social network. The adaptive voter model is coupled to a set of identical logistic growth models and we show that in such systems, the rate of interactions between nodes as well as the adaptive rewiring probability play a crucial role for the sustainability of the system's equilibrium state. We derive a macroscopic description of the system which provides a general framework to model and quantify the influence of single node dynamics on the macroscopic state of the network and is applicable to many fields of study, such as epidemic spreading or social modeling.

  15. Infinite multiple membership relational modeling for complex networks

    DEFF Research Database (Denmark)

    Mørup, Morten; Schmidt, Mikkel Nørgaard; Hansen, Lars Kai

    2011-01-01

    Learning latent structure in complex networks has become an important problem fueled by many types of networked data originating from practically all fields of science. In this paper, we propose a new non-parametric Bayesian multiple-membership latent feature model for networks. Contrary to exist......Learning latent structure in complex networks has become an important problem fueled by many types of networked data originating from practically all fields of science. In this paper, we propose a new non-parametric Bayesian multiple-membership latent feature model for networks. Contrary...... to existing multiplemembership models that scale quadratically in the number of vertices the proposed model scales linearly in the number of links admitting multiple-membership analysis in large scale networks. We demonstrate a connection between the single membership relational model and multiple membership...

  16. Coevolutionary networks: a novel approach to understanding the relationships of humans with the infectious agents

    Directory of Open Access Journals (Sweden)

    Carlos Eduardo Tosta

    2001-04-01

    Full Text Available Human organism is interpenetrated by the world of microorganisms, from the conception until the death. This interpenetration involves different levels of interactions between the partners including trophic exchanges, bi-directional cell signaling and gene activation, besides genetic and epigenetic phenomena, and tends towards mutual adaptation and coevolution. Since these processes are critical for the survival of individuals and species, they rely on the existence of a complex organization of adaptive systems aiming at two apparently conflicting purposes: the maintenance of the internal coherence of each partner, and a mutually advantageous coexistence and progressive adaptation between them. Humans possess three adaptive systems: the nervous, the endocrine and the immune system, each internally organized into subsystems functionally connected by intraconnections, to maintain the internal coherence of the system. The three adaptive systems aim at the maintenance of the internal coherence of the organism and are functionally linked by interconnections, in such way that what happens to one is immediately sensed by the others. The different communities of infectious agents that live within the organism are also organized into functional networks. The members of each community are linked by intraconnections, represented by the mutual trophic, metabolic and other influences, while the different infectious communities affect each other through interconnections. Furthermore, by means of its adaptive systems, the organism influences and is influenced by the microbial communities through the existence of transconnections. It is proposed that these highly complex and dynamic networks, involving gene exchange and epigenetic phenomena, represent major coevolutionary forces for humans and microorganisms.

  17. Quantum complexity: Quantum mutual information, complex networks, and emergent phenomena in quantum cellular automata

    Science.gov (United States)

    Vargas, David L.

    Emerging quantum simulator technologies provide a new challenge to quantum many body theory. Quantifying the emergent order in and predicting the dynamics of such complex quantum systems requires a new approach. We develop such an approach based on complex network analysis of quantum mutual information. First, we establish the usefulness of quantum mutual information complex networks by reproducing the phase diagrams of transverse Ising and Bose-Hubbard models. By quantifying the complexity of quantum cellular automata we then demonstrate the applicability of complex network theory to non-equilibrium quantum dynamics. We conclude with a study of student collaboration networks, correlating a student's role in a collaboration network with their grades. This work thus initiates a quantitative theory of quantum complexity and provides a new tool for physics education research. (Abstract shortened by ProQuest.).

  18. Stochastic synchronization for time-varying complex dynamical networks

    Institute of Scientific and Technical Information of China (English)

    Guo Xiao-Yong; Li Jun-Min

    2012-01-01

    This paper studies the stochastic synchronization problem for time-varying complex dynamical networks. This model is totally different from some existing network models. Based on the Lyapunov stability theory, inequality techniques, and the properties of the Weiner process, some controllers and adaptive laws are designed to ensure achieving stochastic synchronization of a complex dynamical network model. A sufficient synchronization condition is given to ensure that the proposed network model is mean-square stable. Theoretical analysis and numerical simulation fully verify the main results.

  19. Supervised Learning with Complex-valued Neural Networks

    CERN Document Server

    Suresh, Sundaram; Savitha, Ramasamy

    2013-01-01

    Recent advancements in the field of telecommunications, medical imaging and signal processing deal with signals that are inherently time varying, nonlinear and complex-valued. The time varying, nonlinear characteristics of these signals can be effectively analyzed using artificial neural networks.  Furthermore, to efficiently preserve the physical characteristics of these complex-valued signals, it is important to develop complex-valued neural networks and derive their learning algorithms to represent these signals at every step of the learning process. This monograph comprises a collection of new supervised learning algorithms along with novel architectures for complex-valued neural networks. The concepts of meta-cognition equipped with a self-regulated learning have been known to be the best human learning strategy. In this monograph, the principles of meta-cognition have been introduced for complex-valued neural networks in both the batch and sequential learning modes. For applications where the computati...

  20. 5th Workshop on Complex Networks

    CERN Document Server

    Menezes, Ronaldo; Omicini, Andrea; Poncela-Casasnovas, Julia

    2014-01-01

    A network is a mathematical object consisting of a set of points that are connected to each other in some fashion by lines. It turns out this simple description corresponds to a bewildering array of systems in the real world, ranging from technological ones such as the Internet and World Wide Web, biological networks such as that of connections of the nervous systems, food webs, or  protein interactions, infrastructural systems such as networks of roads, airports or the power-grid, to patterns of social and professional relationships such as friendship, sex partners, network of Hollywood actors, co-authorship networks and many more. Recent years have witnessed a substantial amount of interest within the scientific community in the properties of these networks. The emergence of the internet in particular, coupled with the widespread availability of inexpensive computing resources has facilitated studies ranging from large scale empirical analysis of networks in the real world, to the development...