ADAPTIVE GOSSIP BASED PROTOCOL FOR ENERGY EFFICIENT MOBILE ADHOC NETWORK

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S. Rajeswari

2012-03-01

Full Text Available In Gossip Sleep Protocol, network performance is enhanced based on energy resource. But energy conservation is achieved with the reduced throughput. In this paper, it has been proposed a new Protocol for Mobile Ad hoc Network to achieve reliability with energy conservation. Based on the probability (p values, the value of sleep nodes is fixed initially. The probability value can be adaptively adjusted by Remote Activated Switch during the transmission process. The adaptiveness of gossiping probability is determined by the Packet Delivery Ratio. For performance comparison, we have taken Routing overhead, Packet Delivery Ratio, Number of dropped packets and Energy consumption with the increasing number of forwarding nodes. We used UDP based traffic models to analyze the performance of this protocol. We analyzed TCP based traffic models for average end to end delay. We have used the NS-2 simulator.

Promoting sustainable energy systems through networks. A framework for network design developed using the case of BASE (Basel Agency for Sustainable Energy)

Energy Technology Data Exchange (ETDEWEB)

Schlup, M.

2001-09-01

The purpose of this thesis was to generate a framework for establishment of networks to promote sustainable energies and to evaluate the value of networking approaches for Sustainable Energies. Three fields of action had to be analysed and described to provide a full overview of the issues of concern for network design. These were defined as being general factors of success for networks, the definition of appropriate network objectives and the incorporation of demands and needs of the stake holders of a certain field of action. In addition, the framework conditions for the broad topic 'Sustainable Energies' was also analysed and discussed. The framework developed was established using a thorough analysis of the above-mentioned fields of action for BASE, the Basel Agency for Sustainable Energy. Building of trust is a prerequisite for network persistence. It is a slow process that involves different levels of trust. Contributing to successful establishment of trust are 'small wins', benefits that can be felt by participants at an early stage and personal contacts. Communication of the result of the network's activities externally is necessary to harvest PR- and image benefits often part of the motivation to join a network. Balanced inputs and outputs in a network by individual organisations and resource and power dependencies among participating organisations are further factors that influence network persistence. For BASE, a UNEP Collaborating Centre which wants to promote and facilitate investment in sustainable energy, accelerate market development and contribute to global climate protection, networking was recognised as a potential way to increase effectiveness as linking together actors of different levels of the value-chain of sustainable energy projects could help overcoming barriers slowing down investment in the new technologies. Different actors could make use of different specializations of the organisations involved in

The Energy Coding of a Structural Neural Network Based on the Hodgkin-Huxley Model.

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Zhu, Zhenyu; Wang, Rubin; Zhu, Fengyun

2018-01-01

Based on the Hodgkin-Huxley model, the present study established a fully connected structural neural network to simulate the neural activity and energy consumption of the network by neural energy coding theory. The numerical simulation result showed that the periodicity of the network energy distribution was positively correlated to the number of neurons and coupling strength, but negatively correlated to signal transmitting delay. Moreover, a relationship was established between the energy distribution feature and the synchronous oscillation of the neural network, which showed that when the proportion of negative energy in power consumption curve was high, the synchronous oscillation of the neural network was apparent. In addition, comparison with the simulation result of structural neural network based on the Wang-Zhang biophysical model of neurons showed that both models were essentially consistent.

Price-based Energy Control for V2G Networks in the Industrial Smart Grid

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Rong Yu

2015-08-01

Full Text Available The energy crisis and global warming call for a new industrial revolution in production and distribution of renewable energy. Distributed power generation will be well developed in the new smart electricity distribution grid, in which robust power distribution will be the key technology. In this paper, we present a new vehicle-to-grid (V2G network for energy transfer, in which distributed renewable energy helps the power grid balance demand and supply. Plug-in hybrid electric vehicles (PHEVs will act as transporters of electricity for distributed renewable energy dispatching. We formulate and analyze the V2G network within the theoretical framework of complex network. We also employ the generalized synchronization method to study the dynamic behavior of V2G networks. Furthermore, we develop a new price-based energy control method to stimulate the PHEV's behavior of charging and discharging. Simulation results indicate that the V2G network can achieve synchronization and each region is able to balance energy supply and demand through price-based control.

An Energy Centric Cluster-Based Routing Protocol for Wireless Sensor Networks.

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Hosen, A S M Sanwar; Cho, Gi Hwan

2018-05-11

Clustering is an effective way to prolong the lifetime of a wireless sensor network (WSN). The common approach is to elect cluster heads to take routing and controlling duty, and to periodically rotate each cluster head's role to distribute energy consumption among nodes. However, a significant amount of energy dissipates due to control messages overhead, which results in a shorter network lifetime. This paper proposes an energy-centric cluster-based routing mechanism in WSNs. To begin with, cluster heads are elected based on the higher ranks of the nodes. The rank is defined by residual energy and average distance from the member nodes. With the role of data aggregation and data forwarding, a cluster head acts as a caretaker for cluster-head election in the next round, where the ranks' information are piggybacked along with the local data sending during intra-cluster communication. This reduces the number of control messages for the cluster-head election as well as the cluster formation in detail. Simulation results show that our proposed protocol saves the energy consumption among nodes and achieves a significant improvement in the network lifetime.

Analyzing energy consumption of wireless networks. A model-based approach

Energy Technology Data Exchange (ETDEWEB)

Yue, Haidi

2013-03-04

During the last decades, wireless networking has been continuously a hot topic both in academy and in industry. Many different wireless networks have been introduced like wireless local area networks, wireless personal networks, wireless ad hoc networks, and wireless sensor networks. If these networks want to have a long term usability, the power consumed by the wireless devices in each of these networks needs to be managed efficiently. Hence, a lot of effort has been carried out for the analysis and improvement of energy efficiency, either for a specific network layer (protocol), or new cross-layer designs. In this thesis, we apply model-based approach for the analysis of energy consumption of different wireless protocols. The protocols under consideration are: one leader election protocol, one routing protocol, and two medium access control protocols. By model-based approach we mean that all these four protocols are formalized as some formal models, more precisely, as discrete-time Markov chains (DTMCs), Markov decision processes (MDPs), or stochastic timed automata (STA). For the first two models, DTMCs and MDPs, we model them in PRISM, a prominent model checker for probabilistic model checking, and apply model checking technique to analyze them. Model checking belongs to the family of formal methods. It discovers exhaustively all possible (reachable) states of the models, and checks whether these models meet a given specification. Specifications are system properties that we want to study, usually expressed by some logics, for instance, probabilistic computer tree logic (PCTL). However, while model checking relies on rigorous mathematical foundations and automatically explores the entire state space of a model, its applicability is also limited by the so-called state space explosion problem -- even systems of moderate size often yield models with an exponentially larger state space that thwart their analysis. Hence for the STA models in this thesis, since there

Dual-Level Game-Based Energy Efficiency and Fairness for Green Cellular Networks

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Sungwook Kim

2016-01-01

Full Text Available In the recent decades, cellular networks have revolutionized the way of next generation communication networks. However, due to the global climate change, reducing the energy consumption of cellular infrastructures is an important and urgent problem. In this study, we propose a novel two-level cooperative game framework for improving the energy efficiency and fairness in cellular networks. For the energy efficiency, base stations (BSs constantly monitor the current traffic load and cooperate with each other to maximize the energy saving. For the energy fairness, renewable energy can be shared dynamically while ensuring the fairness among BSs. To achieve an excellent cellular network performance, the concepts of the Raiffa Bargaining Solution and Jain’s fairness are extended and practically applied to our dual-level cooperative game model. Through system level simulations, the proposed scheme is evaluated and compared with other existing schemes. The simulation results show that our two-level game approach outperforms the existing schemes in providing a better fair-efficient system performance.

Dynamic Hierarchical Energy-Efficient Method Based on Combinatorial Optimization for Wireless Sensor Networks.

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Chang, Yuchao; Tang, Hongying; Cheng, Yongbo; Zhao, Qin; Yuan, Baoqing Li andXiaobing

2017-07-19

Routing protocols based on topology control are significantly important for improving network longevity in wireless sensor networks (WSNs). Traditionally, some WSN routing protocols distribute uneven network traffic load to sensor nodes, which is not optimal for improving network longevity. Differently to conventional WSN routing protocols, we propose a dynamic hierarchical protocol based on combinatorial optimization (DHCO) to balance energy consumption of sensor nodes and to improve WSN longevity. For each sensor node, the DHCO algorithm obtains the optimal route by establishing a feasible routing set instead of selecting the cluster head or the next hop node. The process of obtaining the optimal route can be formulated as a combinatorial optimization problem. Specifically, the DHCO algorithm is carried out by the following procedures. It employs a hierarchy-based connection mechanism to construct a hierarchical network structure in which each sensor node is assigned to a special hierarchical subset; it utilizes the combinatorial optimization theory to establish the feasible routing set for each sensor node, and takes advantage of the maximum-minimum criterion to obtain their optimal routes to the base station. Various results of simulation experiments show effectiveness and superiority of the DHCO algorithm in comparison with state-of-the-art WSN routing algorithms, including low-energy adaptive clustering hierarchy (LEACH), hybrid energy-efficient distributed clustering (HEED), genetic protocol-based self-organizing network clustering (GASONeC), and double cost function-based routing (DCFR) algorithms.

Energy-efficient Trust-based Aggregation in Wireless Sensor Networks

NARCIS (Netherlands)

Taghikhaki, Zahra; Meratnia, Nirvana; Havinga, Paul J.M.

2011-01-01

Wireless sensor networks (WSNs) are often deployed in unattended and noise-prone environments and suffer from energy constraints that limit the quality and quantity of data transmission. Every decision made based on the low quality and low quantity data may have drastic consequence. Therefore,

Cluster-based Dynamic Energy Management for Collaborative Target Tracking in Wireless Sensor Networks

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Dao-Wei Bi

2007-07-01

Full Text Available A primary criterion of wireless sensor network is energy efficiency. Focused onthe energy problem of target tracking in wireless sensor networks, this paper proposes acluster-based dynamic energy management mechanism. Target tracking problem isformulated by the multi-sensor detection model as well as energy consumption model. Adistributed adaptive clustering approach is investigated to form a reasonable routingframework which has uniform cluster head distribution. Dijkstra’s algorithm is utilized toobtain optimal intra-cluster routing. Target position is predicted by particle filter. Thepredicted target position is adopted to estimate the idle interval of sensor nodes. Hence,dynamic awakening approach is exploited to prolong sleep time of sensor nodes so that theoperation energy consumption of wireless sensor network can be reduced. The sensornodes around the target wake up on time and act as sensing candidates. With the candidatesensor nodes and predicted target position, the optimal sensor node selection is considered.Binary particle swarm optimization is proposed to minimize the total energy consumptionduring collaborative sensing and data reporting. Experimental results verify that theproposed clustering approach establishes a low-energy communication structure while theenergy efficiency of wireless sensor networks is enhanced by cluster-based dynamic energymanagement.

Holding-based network of nations based on listed energy companies: An empirical study on two-mode affiliation network of two sets of actors

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Li, Huajiao; Fang, Wei; An, Haizhong; Gao, Xiangyun; Yan, Lili

2016-05-01

Economic networks in the real world are not homogeneous; therefore, it is important to study economic networks with heterogeneous nodes and edges to simulate a real network more precisely. In this paper, we present an empirical study of the one-mode derivative holding-based network constructed by the two-mode affiliation network of two sets of actors using the data of worldwide listed energy companies and their shareholders. First, we identify the primitive relationship in the two-mode affiliation network of the two sets of actors. Then, we present the method used to construct the derivative network based on the shareholding relationship between two sets of actors and the affiliation relationship between actors and events. After constructing the derivative network, we analyze different topological features on the node level, edge level and entire network level and explain the meanings of the different values of the topological features combining the empirical data. This study is helpful for expanding the usage of complex networks to heterogeneous economic networks. For empirical research on the worldwide listed energy stock market, this study is useful for discovering the inner relationships between the nations and regions from a new perspective.

An Energy-Efficient Game-Theory-Based Spectrum Decision Scheme for Cognitive Radio Sensor Networks.

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Salim, Shelly; Moh, Sangman

2016-06-30

A cognitive radio sensor network (CRSN) is a wireless sensor network in which sensor nodes are equipped with cognitive radio. In this paper, we propose an energy-efficient game-theory-based spectrum decision (EGSD) scheme for CRSNs to prolong the network lifetime. Note that energy efficiency is the most important design consideration in CRSNs because it determines the network lifetime. The central part of the EGSD scheme consists of two spectrum selection algorithms: random selection and game-theory-based selection. The EGSD scheme also includes a clustering algorithm, spectrum characterization with a Markov chain, and cluster member coordination. Our performance study shows that EGSD outperforms the existing popular framework in terms of network lifetime and coordination overhead.

An Energy-Efficient Game-Theory-Based Spectrum Decision Scheme for Cognitive Radio Sensor Networks

Directory of Open Access Journals (Sweden)

Shelly Salim

2016-06-01

Full Text Available A cognitive radio sensor network (CRSN is a wireless sensor network in which sensor nodes are equipped with cognitive radio. In this paper, we propose an energy-efficient game-theory-based spectrum decision (EGSD scheme for CRSNs to prolong the network lifetime. Note that energy efficiency is the most important design consideration in CRSNs because it determines the network lifetime. The central part of the EGSD scheme consists of two spectrum selection algorithms: random selection and game-theory-based selection. The EGSD scheme also includes a clustering algorithm, spectrum characterization with a Markov chain, and cluster member coordination. Our performance study shows that EGSD outperforms the existing popular framework in terms of network lifetime and coordination overhead.

Evaluation and prediction of solar radiation for energy management based on neural networks

Science.gov (United States)

Aldoshina, O. V.; Van Tai, Dinh

2017-08-01

Currently, there is a high rate of distribution of renewable energy sources and distributed power generation based on intelligent networks; therefore, meteorological forecasts are particularly useful for planning and managing the energy system in order to increase its overall efficiency and productivity. The application of artificial neural networks (ANN) in the field of photovoltaic energy is presented in this article. Implemented in this study, two periodically repeating dynamic ANS, that are the concentration of the time delay of a neural network (CTDNN) and the non-linear autoregression of a network with exogenous inputs of the NAEI, are used in the development of a model for estimating and daily forecasting of solar radiation. ANN show good productivity, as reliable and accurate models of daily solar radiation are obtained. This allows to successfully predict the photovoltaic output power for this installation. The potential of the proposed method for controlling the energy of the electrical network is shown using the example of the application of the NAEI network for predicting the electric load.

An Energy Efficient Stable Election-Based Routing Algorithm for Wireless Sensor Networks

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Weiwei Yuan

2013-10-01

Full Text Available Sensor nodes usually have limited energy supply and they are impractical to recharge. How to balance traffic load in sensors in order to increase network lifetime is a very challenging research issue. Many clustering algorithms have been proposed recently for wireless sensor networks (WSNs. However, sensor networks with one fixed sink node often suffer from a hot spots problem since nodes near sinks have more traffic burden to forward during a multi-hop transmission process. The use of mobile sinks has been shown to be an effective technique to enhance network performance features such as latency, energy efficiency, network lifetime, etc. In this paper, a modified Stable Election Protocol (SEP, which employs a mobile sink, has been proposed for WSNs with non-uniform node distribution. The decision of selecting cluster heads by the sink is based on the minimization of the associated additional energy and residual energy at each node. Besides, the cluster head selects the shortest path to reach the sink between the direct approach and the indirect approach with the use of the nearest cluster head. Simulation results demonstrate that our algorithm has better performance than traditional routing algorithms, such as LEACH and SEP.

An Enhanced PSO-Based Clustering Energy Optimization Algorithm for Wireless Sensor Network.

Science.gov (United States)

Vimalarani, C; Subramanian, R; Sivanandam, S N

2016-01-01

Wireless Sensor Network (WSN) is a network which formed with a maximum number of sensor nodes which are positioned in an application environment to monitor the physical entities in a target area, for example, temperature monitoring environment, water level, monitoring pressure, and health care, and various military applications. Mostly sensor nodes are equipped with self-supported battery power through which they can perform adequate operations and communication among neighboring nodes. Maximizing the lifetime of the Wireless Sensor networks, energy conservation measures are essential for improving the performance of WSNs. This paper proposes an Enhanced PSO-Based Clustering Energy Optimization (EPSO-CEO) algorithm for Wireless Sensor Network in which clustering and clustering head selection are done by using Particle Swarm Optimization (PSO) algorithm with respect to minimizing the power consumption in WSN. The performance metrics are evaluated and results are compared with competitive clustering algorithm to validate the reduction in energy consumption.

Deep Belief Network Based Hybrid Model for Building Energy Consumption Prediction

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Chengdong Li

2018-01-01

Full Text Available To enhance the prediction performance for building energy consumption, this paper presents a modified deep belief network (DBN based hybrid model. The proposed hybrid model combines the outputs from the DBN model with the energy-consuming pattern to yield the final prediction results. The energy-consuming pattern in this study represents the periodicity property of building energy consumption and can be extracted from the observed historical energy consumption data. The residual data generated by removing the energy-consuming pattern from the original data are utilized to train the modified DBN model. The training of the modified DBN includes two steps, the first one of which adopts the contrastive divergence (CD algorithm to optimize the hidden parameters in a pre-train way, while the second one determines the output weighting vector by the least squares method. The proposed hybrid model is applied to two kinds of building energy consumption data sets that have different energy-consuming patterns (daily-periodicity and weekly-periodicity. In order to examine the advantages of the proposed model, four popular artificial intelligence methods—the backward propagation neural network (BPNN, the generalized radial basis function neural network (GRBFNN, the extreme learning machine (ELM, and the support vector regressor (SVR are chosen as the comparative approaches. Experimental results demonstrate that the proposed DBN based hybrid model has the best performance compared with the comparative techniques. Another thing to be mentioned is that all the predictors constructed by utilizing the energy-consuming patterns perform better than those designed only by the original data. This verifies the usefulness of the incorporation of the energy-consuming patterns. The proposed approach can also be extended and applied to some other similar prediction problems that have periodicity patterns, e.g., the traffic flow forecasting and the electricity consumption

EDOVE: Energy and Depth Variance-Based Opportunistic Void Avoidance Scheme for Underwater Acoustic Sensor Networks.

Science.gov (United States)

Bouk, Safdar Hussain; Ahmed, Syed Hassan; Park, Kyung-Joon; Eun, Yongsoon

2017-09-26

Underwater Acoustic Sensor Network (UASN) comes with intrinsic constraints because it is deployed in the aquatic environment and uses the acoustic signals to communicate. The examples of those constraints are long propagation delay, very limited bandwidth, high energy cost for transmission, very high signal attenuation, costly deployment and battery replacement, and so forth. Therefore, the routing schemes for UASN must take into account those characteristics to achieve energy fairness, avoid energy holes, and improve the network lifetime. The depth based forwarding schemes in literature use node's depth information to forward data towards the sink. They minimize the data packet duplication by employing the holding time strategy. However, to avoid void holes in the network, they use two hop node proximity information. In this paper, we propose the Energy and Depth variance-based Opportunistic Void avoidance (EDOVE) scheme to gain energy balancing and void avoidance in the network. EDOVE considers not only the depth parameter, but also the normalized residual energy of the one-hop nodes and the normalized depth variance of the second hop neighbors. Hence, it avoids the void regions as well as balances the network energy and increases the network lifetime. The simulation results show that the EDOVE gains more than 15 % packet delivery ratio, propagates 50 % less copies of data packet, consumes less energy, and has more lifetime than the state of the art forwarding schemes.

A decentralized fuzzy C-means-based energy-efficient routing protocol for wireless sensor networks.

Science.gov (United States)

Alia, Osama Moh'd

2014-01-01

Energy conservation in wireless sensor networks (WSNs) is a vital consideration when designing wireless networking protocols. In this paper, we propose a Decentralized Fuzzy Clustering Protocol, named DCFP, which minimizes total network energy dissipation to promote maximum network lifetime. The process of constructing the infrastructure for a given WSN is performed only once at the beginning of the protocol at a base station, which remains unchanged throughout the network's lifetime. In this initial construction step, a fuzzy C-means algorithm is adopted to allocate sensor nodes into their most appropriate clusters. Subsequently, the protocol runs its rounds where each round is divided into a CH-Election phase and a Data Transmission phase. In the CH-Election phase, the election of new cluster heads is done locally in each cluster where a new multicriteria objective function is proposed to enhance the quality of elected cluster heads. In the Data Transmission phase, the sensing and data transmission from each sensor node to their respective cluster head is performed and cluster heads in turn aggregate and send the sensed data to the base station. Simulation results demonstrate that the proposed protocol improves network lifetime, data delivery, and energy consumption compared to other well-known energy-efficient protocols.

A Decentralized Fuzzy C-Means-Based Energy-Efficient Routing Protocol for Wireless Sensor Networks

Science.gov (United States)

2014-01-01

Energy conservation in wireless sensor networks (WSNs) is a vital consideration when designing wireless networking protocols. In this paper, we propose a Decentralized Fuzzy Clustering Protocol, named DCFP, which minimizes total network energy dissipation to promote maximum network lifetime. The process of constructing the infrastructure for a given WSN is performed only once at the beginning of the protocol at a base station, which remains unchanged throughout the network's lifetime. In this initial construction step, a fuzzy C-means algorithm is adopted to allocate sensor nodes into their most appropriate clusters. Subsequently, the protocol runs its rounds where each round is divided into a CH-Election phase and a Data Transmission phase. In the CH-Election phase, the election of new cluster heads is done locally in each cluster where a new multicriteria objective function is proposed to enhance the quality of elected cluster heads. In the Data Transmission phase, the sensing and data transmission from each sensor node to their respective cluster head is performed and cluster heads in turn aggregate and send the sensed data to the base station. Simulation results demonstrate that the proposed protocol improves network lifetime, data delivery, and energy consumption compared to other well-known energy-efficient protocols. PMID:25162060

An Energy-Efficient Spectrum-Aware Reinforcement Learning-Based Clustering Algorithm for Cognitive Radio Sensor Networks.

Science.gov (United States)

Mustapha, Ibrahim; Mohd Ali, Borhanuddin; Rasid, Mohd Fadlee A; Sali, Aduwati; Mohamad, Hafizal

2015-08-13

It is well-known that clustering partitions network into logical groups of nodes in order to achieve energy efficiency and to enhance dynamic channel access in cognitive radio through cooperative sensing. While the topic of energy efficiency has been well investigated in conventional wireless sensor networks, the latter has not been extensively explored. In this paper, we propose a reinforcement learning-based spectrum-aware clustering algorithm that allows a member node to learn the energy and cooperative sensing costs for neighboring clusters to achieve an optimal solution. Each member node selects an optimal cluster that satisfies pairwise constraints, minimizes network energy consumption and enhances channel sensing performance through an exploration technique. We first model the network energy consumption and then determine the optimal number of clusters for the network. The problem of selecting an optimal cluster is formulated as a Markov Decision Process (MDP) in the algorithm and the obtained simulation results show convergence, learning and adaptability of the algorithm to dynamic environment towards achieving an optimal solution. Performance comparisons of our algorithm with the Groupwise Spectrum Aware (GWSA)-based algorithm in terms of Sum of Square Error (SSE), complexity, network energy consumption and probability of detection indicate improved performance from the proposed approach. The results further reveal that an energy savings of 9% and a significant Primary User (PU) detection improvement can be achieved with the proposed approach.

An Enhanced PSO-Based Clustering Energy Optimization Algorithm for Wireless Sensor Network

Directory of Open Access Journals (Sweden)

C. Vimalarani

2016-01-01

Full Text Available Wireless Sensor Network (WSN is a network which formed with a maximum number of sensor nodes which are positioned in an application environment to monitor the physical entities in a target area, for example, temperature monitoring environment, water level, monitoring pressure, and health care, and various military applications. Mostly sensor nodes are equipped with self-supported battery power through which they can perform adequate operations and communication among neighboring nodes. Maximizing the lifetime of the Wireless Sensor networks, energy conservation measures are essential for improving the performance of WSNs. This paper proposes an Enhanced PSO-Based Clustering Energy Optimization (EPSO-CEO algorithm for Wireless Sensor Network in which clustering and clustering head selection are done by using Particle Swarm Optimization (PSO algorithm with respect to minimizing the power consumption in WSN. The performance metrics are evaluated and results are compared with competitive clustering algorithm to validate the reduction in energy consumption.

Spread Spectrum Based Energy Efficient Collaborative Communication in Wireless Sensor Networks.

Science.gov (United States)

Ghani, Anwar; Naqvi, Husnain; Sher, Muhammad; Khan, Muazzam Ali; Khan, Imran; Irshad, Azeem

2016-01-01

Wireless sensor networks consist of resource limited devices. Most crucial of these resources is battery life, as in most applications like battle field or volcanic area monitoring, it is often impossible to replace or recharge the power source. This article presents an energy efficient collaborative communication system based on spread spectrum to achieve energy efficiency as well as immunity against jamming, natural interference, noise suppression and universal frequency reuse. Performance of the proposed system is evaluated using the received signal power, bit error rate (BER) and energy consumption. The results show a direct proportionality between the power gain and the number of collaborative nodes as well as BER and signal-to-noise ratio (Eb/N0). The analytical and simulation results of the proposed system are compared with SISO system. The comparison reveals that SISO perform better than collaborative communication in case of small distances whereas collaborative communication performs better than SISO in case of long distances. On the basis of these results it is safe to conclude that collaborative communication in wireless sensor networks using wideband systems improves the life time of nodes in the networks thereby prolonging the network's life time.

The shareholding similarity of the shareholders of the worldwide listed energy companies based on a two-mode primitive network and a one-mode derivative holding-based network

Science.gov (United States)

Li, Huajiao; Fang, Wei; An, Haizhong; Yan, LiLi

2014-12-01

Two-mode and multi-mode networks represent new directions of simulating a complex network that can simulate the relationships among the entities more precisely. In this paper, we constructed two different levels of networks: one is the two-mode primitive networks of the energy listed companies and their shareholders on the basis of the two-mode method of complex theory, and the other is the derivative one-mode holding-based network based on the equivalence network theory. We calculated two different topological characteristics of the two networks, that is, the out-degree of the actor nodes of the two-mode network (9003 nodes) and the weights of the edges of the one-mode network (619,766 edges), and we analyzed the distribution features of both of the two topological characteristics. In this paper, we define both the weighted and un-weighted Shareholding Similarity Coefficient, and using the data of the worldwide listed energy companies and their shareholders as empirical study subjects, we calculated and compared both the weighted and un-weighted shareholding similarity coefficient of the worldwide listed energy companies. The result of the analysis indicates that (1) both the out-degree of the actor nodes of the two-mode network and the weights of the edges of the one-mode network follow a power-law distribution; (2) there are significant differences between the weighted and un-weighted shareholding similarity coefficient of the worldwide listed energy companies, and the weighted shareholding similarity coefficient is of greater regularity than the un-weighted one; (3) there are a vast majority of shareholders who hold stock in only one or a few of the listed energy companies; and (4) the shareholders hold stock in the same listed energy companies when the value of the un-weighted shareholding similarity coefficient is between 0.4 and 0.8. The study will be a helpful tool to analyze the relationships of the nodes of the one-mode network, which is constructed based

Modelling of synchronisation and energy performance of FBE- and LBE-based standalone LTE-U networks

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Jiamin Li

2017-06-01

Full Text Available Without the aid of licensed channel, deploying long-term evolution (LTE networks over unlicensed spectrum (named standalone LTE-U networks faces the difficulty of establishing and maintaining synchronisation between user equipments and base stations. In this work, considering the two modes of listen-before-talk-based channel access scheme, frame-based equipment (FBE and load-based equipment (LBE, the authors propose analytical frameworks to study the successful probability of synchronisation and the energy consumption of synchronisation in a standalone LTE-U network. Specifically, for the LBE mode, the authors also propose a Lattice-Poisson algorithm-based approach to derive the distribution of the channel non-occupancy period of a standalone LTE-U network. Furthermore, the authors explore the impact of diverse protocol parameters of both FBE and LBE modes on the two studied performance metrics. Simulation results demonstrate the accuracy of the analysis, and shed some light on the selection of FBE and LBE for standalone LTE-U networks, in terms of synchronisation, energy consumption, and throughput of standalone LTE-U and Wi-Fi networks.

Energy Management for Community Energy Network with CHP Based on Cooperative Game

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Xiaofeng Liu

2018-04-01

Full Text Available Integrated energy system (IES has received increasing attention in micro grid due to the high energy efficiency and low emission of carbon dioxide. Based on the technology of combined heat and power (CHP, this paper develops a novel operation mechanism with community micro turbine and shared energy storage system (ESS for energy management of prosumers. In the proposed framework, micro-grid operator (MGO equipped with micro turbine and ESS provides energy selling business and ESS leasing business for prosumers. Prosumers can make energy trading with public grid and MGO, and ESS will be shared among prosumers when they pay for the rent to MGO. Based on such framework, we adopt a cooperative game for prosumers to determine optimal energy trading strategies from MGO and public grid for the next day. Concretely, a cooperative game model is formulated to search the optimal strategies aiming at minimizing the daily cost of coalition, and then a bilateral Shapley value (BSV is proposed to solve the allocation problem of coalition’s cost among prosumers. To verify the effectiveness of proposed energy management framework, a practical example is conducted with a community energy network containing MGO and 10 residential buildings. Simulation results show that the proposed scheme is able to provide financial benefits to all prosumers, while providing peak load leveling for the grid.

Analyzing the factors affecting network lifetime cluster-based wireless sensor network

International Nuclear Information System (INIS)

Malik, A.S.; Qureshi, A.

2010-01-01

Cluster-based wireless sensor networks enable the efficient utilization of the limited energy resources of the deployed sensor nodes and hence prolong the node as well as network lifetime. Low Energy Adaptive Clustering Hierarchy (Leach) is one of the most promising clustering protocol proposed for wireless sensor networks. This paper provides the energy utilization and lifetime analysis for cluster-based wireless sensor networks based upon LEACH protocol. Simulation results identify some important factors that induce unbalanced energy utilization between the sensor nodes and hence affect the network lifetime in these types of networks. These results highlight the need for a standardized, adaptive and distributed clustering technique that can increase the network lifetime by further balancing the energy utilization among sensor nodes. (author)

A method for state of energy estimation of lithium-ion batteries based on neural network model

International Nuclear Information System (INIS)

Dong, Guangzhong; Zhang, Xu; Zhang, Chenbin; Chen, Zonghai

2015-01-01

The state-of-energy is an important evaluation index for energy optimization and management of power battery systems in electric vehicles. Unlike the state-of-charge which represents the residual energy of the battery in traditional applications, state-of-energy is integral result of battery power, which is the product of current and terminal voltage. On the other hand, like state-of-charge, the state-of-energy has an effect on terminal voltage. Therefore, it is hard to solve the nonlinear problems between state-of-energy and terminal voltage, which will complicate the estimation of a battery's state-of-energy. To address this issue, a method based on wavelet-neural-network-based battery model and particle filter estimator is presented for the state-of-energy estimation. The wavelet-neural-network based battery model is used to simulate the entire dynamic electrical characteristics of batteries. The temperature and discharge rate are also taken into account to improve model accuracy. Besides, in order to suppress the measurement noises of current and voltage, a particle filter estimator is applied to estimate cell state-of-energy. Experimental results on LiFePO_4 batteries indicate that the wavelet-neural-network based battery model simulates battery dynamics robustly with high accuracy and the estimation value based on the particle filter estimator converges to the real state-of-energy within an error of ±4%. - Highlights: • State-of-charge is replaced by state-of-energy to determine cells residual energy. • The battery state-space model is established based on a neural network. • Temperature and current influence are considered to improve the model accuracy. • The particle filter is used for state-of-energy estimation to improve accuracy. • The robustness of new method is validated under dynamic experimental conditions.

A Decentralized Fuzzy C-Means-Based Energy-Efficient Routing Protocol for Wireless Sensor Networks

Directory of Open Access Journals (Sweden)

Osama Moh’d Alia

2014-01-01

Full Text Available Energy conservation in wireless sensor networks (WSNs is a vital consideration when designing wireless networking protocols. In this paper, we propose a Decentralized Fuzzy Clustering Protocol, named DCFP, which minimizes total network energy dissipation to promote maximum network lifetime. The process of constructing the infrastructure for a given WSN is performed only once at the beginning of the protocol at a base station, which remains unchanged throughout the network’s lifetime. In this initial construction step, a fuzzy C-means algorithm is adopted to allocate sensor nodes into their most appropriate clusters. Subsequently, the protocol runs its rounds where each round is divided into a CH-Election phase and a Data Transmission phase. In the CH-Election phase, the election of new cluster heads is done locally in each cluster where a new multicriteria objective function is proposed to enhance the quality of elected cluster heads. In the Data Transmission phase, the sensing and data transmission from each sensor node to their respective cluster head is performed and cluster heads in turn aggregate and send the sensed data to the base station. Simulation results demonstrate that the proposed protocol improves network lifetime, data delivery, and energy consumption compared to other well-known energy-efficient protocols.

Adaptive Energy-Efficient Target Detection Based on Mobile Wireless Sensor Networks

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Tengyue Zou

2017-05-01

Full Text Available Target detection is a widely used application for area surveillance, elder care, and fire alarms; its purpose is to find a particular object or event in a region of interest. Usually, fixed observing stations or static sensor nodes are arranged uniformly in the field. However, each part of the field has a different probability of being intruded upon; if an object suddenly enters an area with few guardian devices, a loss of detection will occur, and the stations in the safe areas will waste their energy for a long time without any discovery. Thus, mobile wireless sensor networks may benefit from adaptation and pertinence in detection. Sensor nodes equipped with wheels are able to move towards the risk area via an adaptive learning procedure based on Bayesian networks. Furthermore, a clustering algorithm based on k-means++ and an energy control mechanism is used to reduce the energy consumption of nodes. The extended Kalman filter and a voting data fusion method are employed to raise the localization accuracy of the target. The simulation and experimental results indicate that this new system with adaptive energy-efficient methods is able to achieve better performance than the traditional ones.

Adaptive Energy-Efficient Target Detection Based on Mobile Wireless Sensor Networks.

Science.gov (United States)

Zou, Tengyue; Li, Zhenjia; Li, Shuyuan; Lin, Shouying

2017-05-04

Target detection is a widely used application for area surveillance, elder care, and fire alarms; its purpose is to find a particular object or event in a region of interest. Usually, fixed observing stations or static sensor nodes are arranged uniformly in the field. However, each part of the field has a different probability of being intruded upon; if an object suddenly enters an area with few guardian devices, a loss of detection will occur, and the stations in the safe areas will waste their energy for a long time without any discovery. Thus, mobile wireless sensor networks may benefit from adaptation and pertinence in detection. Sensor nodes equipped with wheels are able to move towards the risk area via an adaptive learning procedure based on Bayesian networks. Furthermore, a clustering algorithm based on k -means++ and an energy control mechanism is used to reduce the energy consumption of nodes. The extended Kalman filter and a voting data fusion method are employed to raise the localization accuracy of the target. The simulation and experimental results indicate that this new system with adaptive energy-efficient methods is able to achieve better performance than the traditional ones.

Prediction of Industrial Electric Energy Consumption in Anhui Province Based on GA-BP Neural Network

Science.gov (United States)

Zhang, Jiajing; Yin, Guodong; Ni, Youcong; Chen, Jinlan

2018-01-01

In order to improve the prediction accuracy of industrial electrical energy consumption, a prediction model of industrial electrical energy consumption was proposed based on genetic algorithm and neural network. The model use genetic algorithm to optimize the weights and thresholds of BP neural network, and the model is used to predict the energy consumption of industrial power in Anhui Province, to improve the prediction accuracy of industrial electric energy consumption in Anhui province. By comparing experiment of GA-BP prediction model and BP neural network model, the GA-BP model is more accurate with smaller number of neurons in the hidden layer.

Accounting for Energy Cost When Designing Energy-Efficient Wireless Access Networks

Directory of Open Access Journals (Sweden)

Greta Vallero

2018-03-01

Full Text Available Because of the increase of the data traffic demand, wireless access networks, through which users access telecommunication services, have expanded, in terms of size and of capability and, consequently, in terms of power consumption. Therefore, costs to buy the necessary power for the supply of base stations of those networks is becoming very high, impacting the communication cost. In this study, strategies to reduce the amount of money spent for the purchase of the energy consumed by the base stations are proposed for a network powered by solar panels, energy batteries and the power grid. First, the variability of the energy prices is exploited. It provides a cost reduction of up to 30%, when energy is bought in advance. If a part of the base stations is deactivated when the energy price is higher than a given threshold, a compromise between the energy cost and the user coverage drop is needed. In the simulated scenario, the necessary energy cost can be reduced by more than 40%, preserving the user coverage by greater than 94%. Second, the network is introduced to the energy market: it buys and sells energy from/to the traditional power grid. Finally, costs are reduced by the reduction of power consumption of the network, achieved by using microcell base stations. In the considered scenario, up to a 31% cost reduction is obtained, without the deterioration of the quality of service, but a huge Capex expenditure is required.

Nation-Wide Mobile Network Energy Evolution Analysis

DEFF Research Database (Denmark)

Perez, Eva; Frank, Philipp; Micallef, Gilbert

2013-01-01

Mobile network operators are facing a challenging dilemma. While on the one hand they are committed to reducing their carbon emissions, and energy consumption, they are also required to continuously upgrade existing networks, ensuring that the relentless growth in data traffic can still be suppor......Mobile network operators are facing a challenging dilemma. While on the one hand they are committed to reducing their carbon emissions, and energy consumption, they are also required to continuously upgrade existing networks, ensuring that the relentless growth in data traffic can still...... be supported. In most cases, these upgrades increase the energy consumption of the network even further. This paper presents a nation-wide case study, based on a commercial network of a leading European operator, intended to provide a clear understanding of how the energy consumption of mobile networks...... is expected to evolve from 2012 until 2020. The study also considers an efficient network capacity evolution path, including base station equipment improvement forecasts....

PERFORMANCE ANALYSIS OF DSR ROUTING PROTOCOL UNDER ENERGY BASED SELFISH ATTACK IN MOBILE AD HOC NETWORKS

Directory of Open Access Journals (Sweden)

T.V.P.Sundararajan

2010-06-01

Full Text Available Mobile Ad hoc Networks (MANETs rely on the cooperation of all participating nodes to provide the fundamental operations such as routing and data forwarding. However, due to the open structure and scarcely available battery-based energy, node misbehaviors may exist.[1]. One such routing misbehavior is that some selfish nodes will participate in the route discovery and maintenance processes but refuse to forward data packets. This paper pointed out Energy based selfish nodes (EBSN where these selfish nodes tend to use the network but do not cooperate, saving battery life for their own communications [2],[3]. We present a simulation study of the effects of Energy based selfish nodes (EBSN on DSR routing protocol and its impact over network performance in terms of throughput and delay of a mobile ad hoc network where a defined percentage of nodes were misbehaving.

Energy-saving scheme based on downstream packet scheduling in ethernet passive optical networks

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Zhang, Lincong; Liu, Yejun; Guo, Lei; Gong, Xiaoxue

2013-03-01

With increasing network sizes, the energy consumption of Passive Optical Networks (PONs) has grown significantly. Therefore, it is important to design effective energy-saving schemes in PONs. Generally, energy-saving schemes have focused on sleeping the low-loaded Optical Network Units (ONUs), which tends to bring large packet delays. Further, the traditional ONU sleep modes are not capable of sleeping the transmitter and receiver independently, though they are not required to transmit or receive packets. Clearly, this approach contributes to wasted energy. Thus, in this paper, we propose an Energy-Saving scheme that is based on downstream Packet Scheduling (ESPS) in Ethernet PON (EPON). First, we design both an algorithm and a rule for downstream packet scheduling at the inter- and intra-ONU levels, respectively, to reduce the downstream packet delay. After that, we propose a hybrid sleep mode that contains not only ONU deep sleep mode but also independent sleep modes for the transmitter and the receiver. This ensures that the energy consumed by the ONUs is minimal. To realize the hybrid sleep mode, a modified GATE control message is designed that involves 10 time points for sleep processes. In ESPS, the 10 time points are calculated according to the allocated bandwidths in both the upstream and the downstream. The simulation results show that ESPS outperforms traditional Upstream Centric Scheduling (UCS) scheme in terms of energy consumption and the average delay for both real-time and non-real-time packets downstream. The simulation results also show that the average energy consumption of each ONU in larger-sized networks is less than that in smaller-sized networks; hence, our ESPS is better suited for larger-sized networks.

A New Wavelength Optimization and Energy-Saving Scheme Based on Network Coding in Software-Defined WDM-PON Networks

Science.gov (United States)

Ren, Danping; Wu, Shanshan; Zhang, Lijing

2016-09-01

In view of the characteristics of the global control and flexible monitor of software-defined networks (SDN), we proposes a new optical access network architecture dedicated to Wavelength Division Multiplexing-Passive Optical Network (WDM-PON) systems based on SDN. The network coding (NC) technology is also applied into this architecture to enhance the utilization of wavelength resource and reduce the costs of light source. Simulation results show that this scheme can optimize the throughput of the WDM-PON network, greatly reduce the system time delay and energy consumption.

Fuzzy-Logic Based Distributed Energy-Efficient Clustering Algorithm for Wireless Sensor Networks.

Science.gov (United States)

Zhang, Ying; Wang, Jun; Han, Dezhi; Wu, Huafeng; Zhou, Rundong

2017-07-03

Due to the high-energy efficiency and scalability, the clustering routing algorithm has been widely used in wireless sensor networks (WSNs). In order to gather information more efficiently, each sensor node transmits data to its Cluster Head (CH) to which it belongs, by multi-hop communication. However, the multi-hop communication in the cluster brings the problem of excessive energy consumption of the relay nodes which are closer to the CH. These nodes' energy will be consumed more quickly than the farther nodes, which brings the negative influence on load balance for the whole networks. Therefore, we propose an energy-efficient distributed clustering algorithm based on fuzzy approach with non-uniform distribution (EEDCF). During CHs' election, we take nodes' energies, nodes' degree and neighbor nodes' residual energies into consideration as the input parameters. In addition, we take advantage of Takagi, Sugeno and Kang (TSK) fuzzy model instead of traditional method as our inference system to guarantee the quantitative analysis more reasonable. In our scheme, each sensor node calculates the probability of being as CH with the help of fuzzy inference system in a distributed way. The experimental results indicate EEDCF algorithm is better than some current representative methods in aspects of data transmission, energy consumption and lifetime of networks.

An Adaption Broadcast Radius-Based Code Dissemination Scheme for Low Energy Wireless Sensor Networks.

Science.gov (United States)

Yu, Shidi; Liu, Xiao; Liu, Anfeng; Xiong, Naixue; Cai, Zhiping; Wang, Tian

2018-05-10

Due to the Software Defined Network (SDN) technology, Wireless Sensor Networks (WSNs) are getting wider application prospects for sensor nodes that can get new functions after updating program codes. The issue of disseminating program codes to every node in the network with minimum delay and energy consumption have been formulated and investigated in the literature. The minimum-transmission broadcast (MTB) problem, which aims to reduce broadcast redundancy, has been well studied in WSNs where the broadcast radius is assumed to be fixed in the whole network. In this paper, an Adaption Broadcast Radius-based Code Dissemination (ABRCD) scheme is proposed to reduce delay and improve energy efficiency in duty cycle-based WSNs. In the ABCRD scheme, a larger broadcast radius is set in areas with more energy left, generating more optimized performance than previous schemes. Thus: (1) with a larger broadcast radius, program codes can reach the edge of network from the source in fewer hops, decreasing the number of broadcasts and at the same time, delay. (2) As the ABRCD scheme adopts a larger broadcast radius for some nodes, program codes can be transmitted to more nodes in one broadcast transmission, diminishing the number of broadcasts. (3) The larger radius in the ABRCD scheme causes more energy consumption of some transmitting nodes, but radius enlarging is only conducted in areas with an energy surplus, and energy consumption in the hot-spots can be reduced instead due to some nodes transmitting data directly to sink without forwarding by nodes in the original hot-spot, thus energy consumption can almost reach a balance and network lifetime can be prolonged. The proposed ABRCD scheme first assigns a broadcast radius, which doesn’t affect the network lifetime, to nodes having different distance to the code source, then provides an algorithm to construct a broadcast backbone. In the end, a comprehensive performance analysis and simulation result shows that the proposed

An Adaption Broadcast Radius-Based Code Dissemination Scheme for Low Energy Wireless Sensor Networks

Directory of Open Access Journals (Sweden)

Shidi Yu

2018-05-01

Full Text Available Due to the Software Defined Network (SDN technology, Wireless Sensor Networks (WSNs are getting wider application prospects for sensor nodes that can get new functions after updating program codes. The issue of disseminating program codes to every node in the network with minimum delay and energy consumption have been formulated and investigated in the literature. The minimum-transmission broadcast (MTB problem, which aims to reduce broadcast redundancy, has been well studied in WSNs where the broadcast radius is assumed to be fixed in the whole network. In this paper, an Adaption Broadcast Radius-based Code Dissemination (ABRCD scheme is proposed to reduce delay and improve energy efficiency in duty cycle-based WSNs. In the ABCRD scheme, a larger broadcast radius is set in areas with more energy left, generating more optimized performance than previous schemes. Thus: (1 with a larger broadcast radius, program codes can reach the edge of network from the source in fewer hops, decreasing the number of broadcasts and at the same time, delay. (2 As the ABRCD scheme adopts a larger broadcast radius for some nodes, program codes can be transmitted to more nodes in one broadcast transmission, diminishing the number of broadcasts. (3 The larger radius in the ABRCD scheme causes more energy consumption of some transmitting nodes, but radius enlarging is only conducted in areas with an energy surplus, and energy consumption in the hot-spots can be reduced instead due to some nodes transmitting data directly to sink without forwarding by nodes in the original hot-spot, thus energy consumption can almost reach a balance and network lifetime can be prolonged. The proposed ABRCD scheme first assigns a broadcast radius, which doesn’t affect the network lifetime, to nodes having different distance to the code source, then provides an algorithm to construct a broadcast backbone. In the end, a comprehensive performance analysis and simulation result shows that

Energy Efficient Evolution of Mobile Networks

DEFF Research Database (Denmark)

Micallef, Gilbert; Mogensen, Preben

2011-01-01

options for how to evolve their networks, allowing them to carry the expected increase in traffic. The best solution is generally selected based on two main criteria, performance and cost. However, pushed by a variety of environmental and energy challenges, MNOs are now also showing interest...... in understanding the impact that different options can have on the energy consumption of their networks. This paper investigates the possible energy gains of evolving a mobile network through a joint pico deployment and macro upgrade solution over a period of 8 years. Besides the network energy consumption, energy...... efficiency in Mbps/kWh is also analyzed. Furthermore, a cost analysis is carried out, to give a more complete picture of the different options being considered. Focusing on the last year of the evolution analysis, results show that deploying more pico sites reduces the energy consumption of the network...

An energy efficient multiple mobile sinks based routing algorithm for wireless sensor networks

Science.gov (United States)

Zhong, Peijun; Ruan, Feng

2018-03-01

With the fast development of wireless sensor networks (WSNs), more and more energy efficient routing algorithms have been proposed. However, one of the research challenges is how to alleviate the hot spot problem since nodes close to static sink (or base station) tend to die earlier than other sensors. The introduction of mobile sink node can effectively alleviate this problem since sink node can move along certain trajectories, causing hot spot nodes more evenly distributed. In this paper, we mainly study the energy efficient routing method with multiple mobile sinks support. We divide the whole network into several clusters and study the influence of mobile sink number on network lifetime. Simulation results show that the best network performance appears when mobile sink number is about 3 under our simulation environment.

Energy-Harvesting Wireless Sensor Networks

DEFF Research Database (Denmark)

Fafoutis, Xenofon; Vuckovic, Dusan; Di Mauro, Alessio

2012-01-01

Energy Harvesting comprises a promising solution to one of the key problems faced by battery-powered Wireless Sensor Networks, namely the limited nature of the energy supply (finite battery capacity). By harvesting energy from the surrounding environment, the sensors can have a continuous lifetime...... Sensor Networks with energy harvesting capability....... without any needs for battery recharge or replacement. However, energy harvesting introduces a change to the fundamental principles based on which WSNs are designed and realized. In this poster we sketch some of the key research challenges as well as our ongoing work in designing and realizing Wireless...

Energy savings through self-backhauling for future heterogeneous networks

International Nuclear Information System (INIS)

Faruk, Nasir; Ruttik, Kalle; Mutafungwa, Edward; Jäntti, Riku

2016-01-01

Mobile operators face continuous challenge of enhancing network capacity and coverage so as to meet demand for ubiquitous high-speed mobile data connectivity. Unfortunately, these enhancements are typically accompanied by increased burden of network energy consumption. Heterogeneous network (HetNet) deployments of a large number of low power small base stations (SBS) to complement existing macro base stations is an approach that increases network capacity but potentially reduces overall network energy consumption. The SBS backhaul links in HetNets present a significant powering burden. In this paper, we show how self backhauling of SBS can reduce overall network power demand. A backhaul-energy consumption model is developed and used to investigate the energy efficiency of different backhauling options. We note that significant energy savings could be achieved through the use of self-backhauling when compared with the conventional microwave backhauling. The results presented would provide guidelines for energy- and cost-efficient backhaul implementation for future HetNets. - Highlights: • A backhaul-energy consumption model is developed. • Self backhauling of small base stations can reduce overall network power demand. • Energy saving strategy presented would relieved the burden on the power networks. • Results provide guidelines for energy and cost effective backhaul implementation.

gTBS: A green Task-Based Sensing for energy efficient Wireless Sensor Networks

KAUST Repository

Al-Halafi, Abdullah

2016-09-08

Wireless sensor networks (WSN) are widely used to sense and measure physical conditions for different purposes and within different regions. However due to the limited lifetime of the sensor\\'s energy source, many efforts are made to design energy efficient WSN. As a result, many techniques were presented in the literature such as power adaptation, sleep and wake-up, and scheduling in order to enhance WSN lifetime. These techniques where presented separately and shown to achieve some gain in terms of energy efficiency. In this paper, we present an energy efficient cross layer design for WSN that we named \\'green Task-Based Sensing\\' (gTBS) scheme. The gTBS design is a task based sensing scheme that not only prevents wasting power in unnecessary signaling, but also utilizes several techniques for achieving reliable and energy efficient WSN. The proposed gTBS combines the power adaptation with a sleep and wake-up technique that allows inactive nodes to sleep. Also, it adopts a gradient-oriented unicast approach to overcome the synchronization problem, minimize network traffic hurdles, and significantly reduce the overall power consumption of the network. We implement the gTBS on a testbed and we show that it reduces the power consumption by a factor of 20%-55% compared to traditional TBS. It also reduces the delay by 54%-145% and improves the delivery ratio by 24%-73%. © 2016 IEEE.

A Multi-Hop Energy Neutral Clustering Algorithm for Maximizing Network Information Gathering in Energy Harvesting Wireless Sensor Networks.

Science.gov (United States)

Yang, Liu; Lu, Yinzhi; Zhong, Yuanchang; Wu, Xuegang; Yang, Simon X

2015-12-26

Energy resource limitation is a severe problem in traditional wireless sensor networks (WSNs) because it restricts the lifetime of network. Recently, the emergence of energy harvesting techniques has brought with them the expectation to overcome this problem. In particular, it is possible for a sensor node with energy harvesting abilities to work perpetually in an Energy Neutral state. In this paper, a Multi-hop Energy Neutral Clustering (MENC) algorithm is proposed to construct the optimal multi-hop clustering architecture in energy harvesting WSNs, with the goal of achieving perpetual network operation. All cluster heads (CHs) in the network act as routers to transmit data to base station (BS) cooperatively by a multi-hop communication method. In addition, by analyzing the energy consumption of intra- and inter-cluster data transmission, we give the energy neutrality constraints. Under these constraints, every sensor node can work in an energy neutral state, which in turn provides perpetual network operation. Furthermore, the minimum network data transmission cycle is mathematically derived using convex optimization techniques while the network information gathering is maximal. Simulation results show that our protocol can achieve perpetual network operation, so that the consistent data delivery is guaranteed. In addition, substantial improvements on the performance of network throughput are also achieved as compared to the famous traditional clustering protocol LEACH and recent energy harvesting aware clustering protocols.

A Multi-Hop Energy Neutral Clustering Algorithm for Maximizing Network Information Gathering in Energy Harvesting Wireless Sensor Networks

Directory of Open Access Journals (Sweden)

Liu Yang

2015-12-01

Full Text Available Energy resource limitation is a severe problem in traditional wireless sensor networks (WSNs because it restricts the lifetime of network. Recently, the emergence of energy harvesting techniques has brought with them the expectation to overcome this problem. In particular, it is possible for a sensor node with energy harvesting abilities to work perpetually in an Energy Neutral state. In this paper, a Multi-hop Energy Neutral Clustering (MENC algorithm is proposed to construct the optimal multi-hop clustering architecture in energy harvesting WSNs, with the goal of achieving perpetual network operation. All cluster heads (CHs in the network act as routers to transmit data to base station (BS cooperatively by a multi-hop communication method. In addition, by analyzing the energy consumption of intra- and inter-cluster data transmission, we give the energy neutrality constraints. Under these constraints, every sensor node can work in an energy neutral state, which in turn provides perpetual network operation. Furthermore, the minimum network data transmission cycle is mathematically derived using convex optimization techniques while the network information gathering is maximal. Simulation results show that our protocol can achieve perpetual network operation, so that the consistent data delivery is guaranteed. In addition, substantial improvements on the performance of network throughput are also achieved as compared to the famous traditional clustering protocol LEACH and recent energy harvesting aware clustering protocols.

Insights into the fold organization of TIM barrel from interaction energy based structure networks.

Science.gov (United States)

Vijayabaskar, M S; Vishveshwara, Saraswathi

2012-01-01

There are many well-known examples of proteins with low sequence similarity, adopting the same structural fold. This aspect of sequence-structure relationship has been extensively studied both experimentally and theoretically, however with limited success. Most of the studies consider remote homology or "sequence conservation" as the basis for their understanding. Recently "interaction energy" based network formalism (Protein Energy Networks (PENs)) was developed to understand the determinants of protein structures. In this paper we have used these PENs to investigate the common non-covalent interactions and their collective features which stabilize the TIM barrel fold. We have also developed a method of aligning PENs in order to understand the spatial conservation of interactions in the fold. We have identified key common interactions responsible for the conservation of the TIM fold, despite high sequence dissimilarity. For instance, the central beta barrel of the TIM fold is stabilized by long-range high energy electrostatic interactions and low-energy contiguous vdW interactions in certain families. The other interfaces like the helix-sheet or the helix-helix seem to be devoid of any high energy conserved interactions. Conserved interactions in the loop regions around the catalytic site of the TIM fold have also been identified, pointing out their significance in both structural and functional evolution. Based on these investigations, we have developed a novel network based phylogenetic analysis for remote homologues, which can perform better than sequence based phylogeny. Such an analysis is more meaningful from both structural and functional evolutionary perspective. We believe that the information obtained through the "interaction conservation" viewpoint and the subsequently developed method of structure network alignment, can shed new light in the fields of fold organization and de novo computational protein design.

Statistical-QoS Guaranteed Energy Efficiency Optimization for Energy Harvesting Wireless Sensor Networks.

Science.gov (United States)

Gao, Ya; Cheng, Wenchi; Zhang, Hailin

2017-08-23

Energy harvesting, which offers a never-ending energy supply, has emerged as a prominent technology to prolong the lifetime and reduce costs for the battery-powered wireless sensor networks. However, how to improve the energy efficiency while guaranteeing the quality of service (QoS) for energy harvesting based wireless sensor networks is still an open problem. In this paper, we develop statistical delay-bounded QoS-driven power control policies to maximize the effective energy efficiency (EEE), which is defined as the spectrum efficiency under given specified QoS constraints per unit harvested energy, for energy harvesting based wireless sensor networks. For the battery-infinite wireless sensor networks, our developed QoS-driven power control policy converges to the Energy harvesting Water Filling (E-WF) scheme and the Energy harvesting Channel Inversion (E-CI) scheme under the very loose and stringent QoS constraints, respectively. For the battery-finite wireless sensor networks, our developed QoS-driven power control policy becomes the Truncated energy harvesting Water Filling (T-WF) scheme and the Truncated energy harvesting Channel Inversion (T-CI) scheme under the very loose and stringent QoS constraints, respectively. Furthermore, we evaluate the outage probabilities to theoretically analyze the performance of our developed QoS-driven power control policies. The obtained numerical results validate our analysis and show that our developed optimal power control policies can optimize the EEE over energy harvesting based wireless sensor networks.

Energy Analysis of Contention Tree-Based Access Protocols in Dense Machine-to-Machine Area Networks

Directory of Open Access Journals (Sweden)

Francisco Vázquez-Gallego

2015-01-01

Full Text Available Machine-to-Machine (M2M area networks aim at connecting an M2M gateway with a large number of energy-constrained devices that must operate autonomously for years. Therefore, attaining high energy efficiency is essential in the deployment of M2M networks. In this paper, we consider a dense M2M area network composed of hundreds or thousands of devices that periodically transmit data upon request from a gateway or coordinator. We theoretically analyse the devices’ energy consumption using two Medium Access Control (MAC protocols which are based on a tree-splitting algorithm to resolve collisions among devices: the Contention Tree Algorithm (CTA and the Distributed Queuing (DQ access. We have carried out computer-based simulations to validate the accuracy of the theoretical models and to compare the energy performance using DQ, CTA, and Frame Slotted-ALOHA (FSA in M2M area networks with devices in compliance with the IEEE 802.15.4 physical layer. Results show that the performance of DQ is totally independent of the number of contending devices, and it can reduce the energy consumed per device in more than 35% with respect to CTA and in more than 80% with respect to FSA.

Spectrum sensing algorithm based on autocorrelation energy in cognitive radio networks

Science.gov (United States)

Ren, Shengwei; Zhang, Li; Zhang, Shibing

2016-10-01

Cognitive radio networks have wide applications in the smart home, personal communications and other wireless communication. Spectrum sensing is the main challenge in cognitive radios. This paper proposes a new spectrum sensing algorithm which is based on the autocorrelation energy of signal received. By taking the autocorrelation energy of the received signal as the statistics of spectrum sensing, the effect of the channel noise on the detection performance is reduced. Simulation results show that the algorithm is effective and performs well in low signal-to-noise ratio. Compared with the maximum generalized eigenvalue detection (MGED) algorithm, function of covariance matrix based detection (FMD) algorithm and autocorrelation-based detection (AD) algorithm, the proposed algorithm has 2 11 dB advantage.

Energy Efficiency Performance Improvements for Ant-Based Routing Algorithm in Wireless Sensor Networks

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Adamu Murtala Zungeru

2013-01-01

Full Text Available The main problem for event gathering in wireless sensor networks (WSNs is the restricted communication range for each node. Due to the restricted communication range and high network density, event forwarding in WSNs is very challenging and requires multihop data forwarding. Currently, the energy-efficient ant based routing (EEABR algorithm, based on the ant colony optimization (ACO metaheuristic, is one of the state-of-the-art energy-aware routing protocols. In this paper, we propose three improvements to the EEABR algorithm to further improve its energy efficiency. The improvements to the original EEABR are based on the following: (1 a new scheme to intelligently initialize the routing tables giving priority to neighboring nodes that simultaneously could be the destination, (2 intelligent update of routing tables in case of a node or link failure, and (3 reducing the flooding ability of ants for congestion control. The energy efficiency improvements are significant particularly for dynamic routing environments. Experimental results using the RMASE simulation environment show that the proposed method increases the energy efficiency by up to 9% and 64% in converge-cast and target-tracking scenarios, respectively, over the original EEABR without incurring a significant increase in complexity. The method is also compared and found to also outperform other swarm-based routing protocols such as sensor-driven and cost-aware ant routing (SC and Beesensor.

Energy optimization in mobile sensor networks

Science.gov (United States)

Yu, Shengwei

Mobile sensor networks are considered to consist of a network of mobile robots, each of which has computation, communication and sensing capabilities. Energy efficiency is a critical issue in mobile sensor networks, especially when mobility (i.e., locomotion control), routing (i.e., communications) and sensing are unique characteristics of mobile robots for energy optimization. This thesis focuses on the problem of energy optimization of mobile robotic sensor networks, and the research results can be extended to energy optimization of a network of mobile robots that monitors the environment, or a team of mobile robots that transports materials from stations to stations in a manufacturing environment. On the energy optimization of mobile robotic sensor networks, our research focuses on the investigation and development of distributed optimization algorithms to exploit the mobility of robotic sensor nodes for network lifetime maximization. In particular, the thesis studies these five problems: 1. Network-lifetime maximization by controlling positions of networked mobile sensor robots based on local information with distributed optimization algorithms; 2. Lifetime maximization of mobile sensor networks with energy harvesting modules; 3. Lifetime maximization using joint design of mobility and routing; 4. Optimal control for network energy minimization; 5. Network lifetime maximization in mobile visual sensor networks. In addressing the first problem, we consider only the mobility strategies of the robotic relay nodes in a mobile sensor network in order to maximize its network lifetime. By using variable substitutions, the original problem is converted into a convex problem, and a variant of the sub-gradient method for saddle-point computation is developed for solving this problem. An optimal solution is obtained by the method. Computer simulations show that mobility of robotic sensors can significantly prolong the lifetime of the whole robotic sensor network while

CoCMA: Energy-Efficient Coverage Control in Cluster-Based Wireless Sensor Networks Using a Memetic Algorithm

Directory of Open Access Journals (Sweden)

Yung-Chung Wang

2009-06-01

Full Text Available Deployment of wireless sensor networks (WSNs has drawn much attention in recent years. Given the limited energy for sensor nodes, it is critical to implement WSNs with energy efficiency designs. Sensing coverage in networks, on the other hand, may degrade gradually over time after WSNs are activated. For mission-critical applications, therefore, energy-efficient coverage control should be taken into consideration to support the quality of service (QoS of WSNs. Usually, coverage-controlling strategies present some challenging problems: (1 resolving the conflicts while determining which nodes should be turned off to conserve energy; (2 designing an optimal wake-up scheme that avoids awakening more nodes than necessary. In this paper, we implement an energy-efficient coverage control in cluster-based WSNs using a Memetic Algorithm (MA-based approach, entitled CoCMA, to resolve the challenging problems. The CoCMA contains two optimization strategies: a MA-based schedule for sensor nodes and a wake-up scheme, which are responsible to prolong the network lifetime while maintaining coverage preservation. The MA-based schedule is applied to a given WSN to avoid unnecessary energy consumption caused by the redundant nodes. During the network operation, the wake-up scheme awakens sleeping sensor nodes to recover coverage hole caused by dead nodes. The performance evaluation of the proposed CoCMA was conducted on a cluster-based WSN (CWSN under either a random or a uniform deployment of sensor nodes. Simulation results show that the performance yielded by the combination of MA and wake-up scheme is better than that in some existing approaches. Furthermore, CoCMA is able to activate fewer sensor nodes to monitor the required sensing area.

Energy efficiency in hybrid mobile and wireless networks

Energy Technology Data Exchange (ETDEWEB)

Abbas, Ziaul Haq

2012-07-01

. Towards this direction, various solutions have been proposed, ranging from deployment strategies for base stations to cooperative techniques etc. However, as base stations have the largest share in a network's energy consumption, methods that allow lightly-loaded base stations sleep or be switched off are possible means as a feasible step towards green communications. In this dissertation, we tackle the above mentioned problems from two perspectives, i.e., mobile station's and operator's perspectives. More specifically, by taking into account the amount of transferred data in uplinks and downlinks individually for various components in a hybrid network, strategies are proposed to reduce mobile station's battery energy consumption. For this purpose, other parameters such as link distance and remaining battery energy can also be considered for handover decision making, in order to maximize energy efficiency of the mobile station. To optimize long-term energy consumption of the mobile stations operated in such scenarios, a Markov decision process-based methodology is proposed as our contribution to this topic. Moreover, from operator's perspective, a network energy conservation scheme which may switch off a base station is proposed for micro- or pico-cells scenarios. Both deterministic and probabilistic schemes are proposed for network energy conservation. The problems considered and the solutions proposed in this dissertation advance the frontiers of the research work within the theme of energy efficiency for mobile devices as well as hybrid mobile and wireless networks.(Author)

Mobile Ad Hoc Network Energy Cost Algorithm Based on Artificial Bee Colony

Directory of Open Access Journals (Sweden)

Mustafa Tareq

2017-01-01

Full Text Available A mobile ad hoc network (MANET is a collection of mobile nodes that dynamically form a temporary network without using any existing network infrastructure. MANET selects a path with minimal number of intermediate nodes to reach the destination node. As the distance between each node increases, the quantity of transmission power increases. The power level of nodes affects the simplicity with which a route is constituted between a couple of nodes. This study utilizes the swarm intelligence technique through the artificial bee colony (ABC algorithm to optimize the energy consumption in a dynamic source routing (DSR protocol in MANET. The proposed algorithm is called bee DSR (BEEDSR. The ABC algorithm is used to identify the optimal path from the source to the destination to overcome energy problems. The performance of the BEEDSR algorithm is compared with DSR and bee-inspired protocols (BeeIP. The comparison was conducted based on average energy consumption, average throughput, average end-to-end delay, routing overhead, and packet delivery ratio performance metrics, varying the node speed and packet size. The BEEDSR algorithm is superior in performance than other protocols in terms of energy conservation and delay degradation relating to node speed and packet size.

On the Design of Energy Efficient Optical Networks with Software Defined Networking Control Across Core and Access Networks

DEFF Research Database (Denmark)

Wang, Jiayuan; Yan, Ying; Dittmann, Lars

2013-01-01

This paper presents a Software Defined Networking (SDN) control plane based on an overlay GMPLS control model. The SDN control platform manages optical core networks (WDM/DWDM networks) and the associated access networks (GPON networks), which makes it possible to gather global information...... and enable wider areas' energy efficiency networking. The energy related information of the networks and the types of the traffic flows are collected and utilized for the end-to-end QoS provision. Dynamic network simulation results show that by applying different routing algorithms according to the type...... of traffic in the core networks, the energy efficiency of the network is improved without compromising the quality of service....

An Energy-Efficient Cluster-Based Vehicle Detection on Road Network Using Intention Numeration Method

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Deepa Devasenapathy

2015-01-01

Full Text Available The traffic in the road network is progressively increasing at a greater extent. Good knowledge of network traffic can minimize congestions using information pertaining to road network obtained with the aid of communal callers, pavement detectors, and so on. Using these methods, low featured information is generated with respect to the user in the road network. Although the existing schemes obtain urban traffic information, they fail to calculate the energy drain rate of nodes and to locate equilibrium between the overhead and quality of the routing protocol that renders a great challenge. Thus, an energy-efficient cluster-based vehicle detection in road network using the intention numeration method (CVDRN-IN is developed. Initially, sensor nodes that detect a vehicle are grouped into separate clusters. Further, we approximate the strength of the node drain rate for a cluster using polynomial regression function. In addition, the total node energy is estimated by taking the integral over the area. Finally, enhanced data aggregation is performed to reduce the amount of data transmission using digital signature tree. The experimental performance is evaluated with Dodgers loop sensor data set from UCI repository and the performance evaluation outperforms existing work on energy consumption, clustering efficiency, and node drain rate.

An energy-efficient cluster-based vehicle detection on road network using intention numeration method.

Science.gov (United States)

Devasenapathy, Deepa; Kannan, Kathiravan

2015-01-01

The traffic in the road network is progressively increasing at a greater extent. Good knowledge of network traffic can minimize congestions using information pertaining to road network obtained with the aid of communal callers, pavement detectors, and so on. Using these methods, low featured information is generated with respect to the user in the road network. Although the existing schemes obtain urban traffic information, they fail to calculate the energy drain rate of nodes and to locate equilibrium between the overhead and quality of the routing protocol that renders a great challenge. Thus, an energy-efficient cluster-based vehicle detection in road network using the intention numeration method (CVDRN-IN) is developed. Initially, sensor nodes that detect a vehicle are grouped into separate clusters. Further, we approximate the strength of the node drain rate for a cluster using polynomial regression function. In addition, the total node energy is estimated by taking the integral over the area. Finally, enhanced data aggregation is performed to reduce the amount of data transmission using digital signature tree. The experimental performance is evaluated with Dodgers loop sensor data set from UCI repository and the performance evaluation outperforms existing work on energy consumption, clustering efficiency, and node drain rate.

Energy network dispatch optimization under emergency of local energy shortage

International Nuclear Information System (INIS)

Cai, Tianxing; Zhao, Chuanyu; Xu, Qiang

2012-01-01

The consequence of short-time energy shortage under extreme conditions, such as earthquake, tsunami, and hurricane, may cause local areas to suffer from delayed rescues, widespread power outages, tremendous economic losses, and even public safety threats. In such urgent events of local energy shortage, agile energy dispatching through an effective energy transportation network, targeting the minimum energy recovery time, should be a top priority. In this paper, a novel methodology is developed for energy network dispatch optimization under emergency of local energy shortage, which includes four stages of work. First, emergency-area-centered energy network needs to be characterized, where the capacity, quantity, and availability of various energy sources are determined. Second, the energy initial situation under emergency conditions needs to be identified. Then, the energy dispatch optimization is conducted based on a developed MILP (mixed-integer linear programming) model in the third stage. Finally, the sensitivity of the minimum dispatch time with respect to uncertainty parameters is characterized by partitioning the entire space of uncertainty parameters into multiple subspaces. The efficacy of the developed methodology is demonstrated via a case study with in-depth discussions. -- Highlights: ► Address the energy network dispatch problem under emergency of local energy shortage. ► Minimize the energy restoration time for the entire energy network under emergency events. ► Develop a new MILP model and a sensitivity analysis method with respect to uncertainties.

Energy Efficient Digital Networks

Energy Technology Data Exchange (ETDEWEB)

Lanzisera, Steven [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Brown, Richard [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)

2013-01-01

Digital networks are the foundation of the information services, and play an expanding and indispensable role in our lives, via the Internet, email, mobile phones, etc. However, these networks consume energy, both through the direct energy use of the network interfaces and equipment that comprise the network, and in the effect they have on the operating patterns of devices connected to the network. The purpose of this research was to investigate a variety of technology and policy issues related to the energy use caused by digital networks, and to further develop several energy-efficiency technologies targeted at networks.

Assessment of energy security in China based on ecological network analysis: A perspective from the security of crude oil supply

International Nuclear Information System (INIS)

Lu, Weiwei; Su, Meirong; Zhang, Yan; Yang, Zhifeng; Chen, Bin; Liu, Gengyuan

2014-01-01

Energy security usually considers both the stability of energy supply and security of energy use and it is receiving increasing attention globally. Considering the strategic importance and sensitivity to international change of the crude oil supply, we decided to examine China’s energy security. An original network model was established based on ecological network analysis to holistically evaluate the security of the crude oil supply in China. Using this model, we found that the security of the crude oil supply in China generally increased from 2001 to 2010. The contribution of different compartments in the network to the overall energy security resembled a pyramid structure, with supply sources at the bottom, the consumption sector at the top, and the refining and transfer sectors in the middle. North and South America made the largest contribution to the security of the crude oil supply in China. We provide suggestions to improve the security of the crude oil supply in China based on our results and further scenario analysis. The original network model provides a new perspective for energy security assessment, which can be used as a baseline to develop other models and policy. - Highlights: • Ecological network analysis (ENA) is introduced into energy security assessment. • A model of crude oil supply network in China is established based on ENA. • A pyramid structure of the contributions of different compartments to energy security was found. • Suggestions for forming a stable network are given to improve energy security

Energy-Saving Mechanism in WDM/TDM-PON Based on Upstream Network Traffic

Directory of Open Access Journals (Sweden)

Paola Garfias

2014-08-01

Full Text Available One of the main challenges of Passive Optical Networks (PONs is the resource (bandwidth and wavelength management. Since it has been shown that access networks consume a significant part of the overall energy of the telecom networks, the resource management schemes should also consider energy minimization strategies. To sustain the increased bandwidth demand of emerging applications in the access section of the network, it is expected that next generation optical access networks will adopt the wavelength division/time division multiplexing (WDM/TDM technique to increase PONs capacity. Compared with traditional PONs, the architecture of a WDM/TDM-PON requires more transceivers/receivers, hence they are expected to consume more energy. In this paper, we focus on the energy minimization in WDM/TDM-PONs and we propose an energy-efficient Dynamic Bandwidth and Wavelength Allocation mechanism whose objective is to turn off, whenever possible, the unnecessary upstream traffic receivers at the Optical Line Terminal (OLT. We evaluate our mechanism in different scenarios and show that the proper use of upstream channels leads to relevant energy savings. Our proposed energy-saving mechanism is able to save energy at the OLT while maintaining the introduced penalties in terms of packet delay and cycle time within an acceptable range. We might highlight the benefits of our proposal as a mechanism that maximizes the channel utilization. Detailed implementation of the proposed algorithm is presented, and simulation results are reported to quantify energy savings and effects on network performance on different network scenarios.

Energy Harvesting Based Body Area Networks for Smart Health.

Science.gov (United States)

Hao, Yixue; Peng, Limei; Lu, Huimin; Hassan, Mohammad Mehedi; Alamri, Atif

2017-07-10

Body area networks (BANs) are configured with a great number of ultra-low power consumption wearable devices, which constantly monitor physiological signals of the human body and thus realize intelligent monitoring. However, the collection and transfer of human body signals consume energy, and considering the comfort demand of wearable devices, both the size and the capacity of a wearable device's battery are limited. Thus, minimizing the energy consumption of wearable devices and optimizing the BAN energy efficiency is still a challenging problem. Therefore, in this paper, we propose an energy harvesting-based BAN for smart health and discuss an optimal resource allocation scheme to improve BAN energy efficiency. Specifically, firstly, considering energy harvesting in a BAN and the time limits of human body signal transfer, we formulate the energy efficiency optimization problem of time division for wireless energy transfer and wireless information transfer. Secondly, we convert the optimization problem into a convex optimization problem under a linear constraint and propose a closed-form solution to the problem. Finally, simulation results proved that when the size of data acquired by the wearable devices is small, the proportion of energy consumed by the circuit and signal acquisition of the wearable devices is big, and when the size of data acquired by the wearable devices is big, the energy consumed by the signal transfer of the wearable device is decisive.

An Energy-Efficient Underground Localization System Based on Heterogeneous Wireless Networks

Science.gov (United States)

Yuan, Yazhou; Chen, Cailian; Guan, Xinping; Yang, Qiuling

2015-01-01

A precision positioning system with energy efficiency is of great necessity for guaranteeing personnel safety in underground mines. The location information of the miners' should be transmitted to the control center timely and reliably; therefore, a heterogeneous network with the backbone based on high speed Industrial Ethernet is deployed. Since the mobile wireless nodes are working in an irregular tunnel, a specific wireless propagation model cannot fit all situations. In this paper, an underground localization system is designed to enable the adaptation to kinds of harsh tunnel environments, but also to reduce the energy consumption and thus prolong the lifetime of the network. Three key techniques are developed and implemented to improve the system performance, including a step counting algorithm with accelerometers, a power control algorithm and an adaptive packets scheduling scheme. The simulation study and experimental results show the effectiveness of the proposed algorithms and the implementation. PMID:26016918

Energy neutral protocol based on hierarchical routing techniques for energy harvesting wireless sensor network

Science.gov (United States)

Muhammad, Umar B.; Ezugwu, Absalom E.; Ofem, Paulinus O.; Rajamäki, Jyri; Aderemi, Adewumi O.

2017-06-01

Recently, researchers in the field of wireless sensor networks have resorted to energy harvesting techniques that allows energy to be harvested from the ambient environment to power sensor nodes. Using such Energy harvesting techniques together with proper routing protocols, an Energy Neutral state can be achieved so that sensor nodes can run perpetually. In this paper, we propose an Energy Neutral LEACH routing protocol which is an extension to the traditional LEACH protocol. The goal of the proposed protocol is to use Gateway node in each cluster so as to reduce the data transmission ranges of cluster head nodes. Simulation results show that the proposed routing protocol achieves a higher throughput and ensure the energy neutral status of the entire network.

Advertisement-Based Energy Efficient Medium Access Protocols for Wireless Sensor Networks

Science.gov (United States)

Ray, Surjya Sarathi

One of the main challenges that prevents the large-scale deployment of Wireless Sensor Networks (WSNs) is providing the applications with the required quality of service (QoS) given the sensor nodes' limited energy supplies. WSNs are an important tool in supporting applications ranging from environmental and industrial monitoring, to battlefield surveillance and traffic control, among others. Most of these applications require sensors to function for long periods of time without human intervention and without battery replacement. Therefore, energy conservation is one of the main goals for protocols for WSNs. Energy conservation can be performed in different layers of the protocol stack. In particular, as the medium access control (MAC) layer can access and control the radio directly, large energy savings is possible through intelligent MAC protocol design. To maximize the network lifetime, MAC protocols for WSNs aim to minimize idle listening of the sensor nodes, packet collisions, and overhearing. Several approaches such as duty cycling and low power listening have been proposed at the MAC layer to achieve energy efficiency. In this thesis, I explore the possibility of further energy savings through the advertisement of data packets in the MAC layer. In the first part of my research, I propose Advertisement-MAC or ADV-MAC, a new MAC protocol for WSNs that utilizes the concept of advertising for data contention. This technique lets nodes listen dynamically to any desired transmission and sleep during transmissions not of interest. This minimizes the energy lost in idle listening and overhearing while maintaining an adaptive duty cycle to handle variable loads. Additionally, ADV-MAC enables energy efficient MAC-level multicasting. An analytical model for the packet delivery ratio and the energy consumption of the protocol is also proposed. The analytical model is verified with simulations and is used to choose an optimal value of the advertisement period

Energy Efficient In-network RFID Data Filtering Scheme in Wireless Sensor Networks

Science.gov (United States)

Bashir, Ali Kashif; Lim, Se-Jung; Hussain, Chauhdary Sajjad; Park, Myong-Soon

2011-01-01

RFID (Radio frequency identification) and wireless sensor networks are backbone technologies for pervasive environments. In integration of RFID and WSN, RFID data uses WSN protocols for multi-hop communications. Energy is a critical issue in WSNs; however, RFID data contains a lot of duplication. These duplications can be eliminated at the base station, but unnecessary transmissions of duplicate data within the network still occurs, which consumes nodes’ energy and affects network lifetime. In this paper, we propose an in-network RFID data filtering scheme that efficiently eliminates the duplicate data. For this we use a clustering mechanism where cluster heads eliminate duplicate data and forward filtered data towards the base station. Simulation results prove that our approach saves considerable amounts of energy in terms of communication and computational cost, compared to existing filtering schemes. PMID:22163999

Energy Efficient In-network RFID Data Filtering Scheme in Wireless Sensor Networks

Directory of Open Access Journals (Sweden)

Myong-Soon Park

2011-07-01

Full Text Available RFID (Radio frequency identification and wireless sensor networks are backbone technologies for pervasive environments. In integration of RFID and WSN, RFID data uses WSN protocols for multi-hop communications. Energy is a critical issue in WSNs; however, RFID data contains a lot of duplication. These duplications can be eliminated at the base station, but unnecessary transmissions of duplicate data within the network still occurs, which consumes nodes’ energy and affects network lifetime. In this paper, we propose an in-network RFID data filtering scheme that efficiently eliminates the duplicate data. For this we use a clustering mechanism where cluster heads eliminate duplicate data and forward filtered data towards the base station. Simulation results prove that our approach saves considerable amounts of energy in terms of communication and computational cost, compared to existing filtering schemes.

Energy Balance Routing Algorithm Based on Virtual MIMO Scheme for Wireless Sensor Networks

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Jianpo Li

2014-01-01

Full Text Available Wireless sensor networks are usually energy limited and therefore an energy-efficient routing algorithm is desired for prolonging the network lifetime. In this paper, we propose a new energy balance routing algorithm which has the following three improvements over the conventional LEACH algorithm. Firstly, we propose a new cluster head selection scheme by taking into consideration the remaining energy and the most recent energy consumption of the nodes and the entire network. In this way, the sensor nodes with smaller remaining energy or larger energy consumption will be much less likely to be chosen as cluster heads. Secondly, according to the ratio of remaining energy to distance, cooperative nodes are selected to form virtual MIMO structures. It mitigates the uneven distribution of clusters and the unbalanced energy consumption of the whole network. Thirdly, we construct a comprehensive energy consumption model, which can reflect more realistically the practical energy consumption. Numerical simulations analyze the influences of cooperative node numbers and cluster head node numbers on the network lifetime. It is shown that the energy consumption of the proposed routing algorithm is lower than the conventional LEACH algorithm and for the simulation example the network lifetime is prolonged about 25%.

Bluetooth-based wireless sensor networks

Science.gov (United States)

You, Ke; Liu, Rui Qiang

2007-11-01

In this work a Bluetooth-based wireless sensor network is proposed. In this bluetooth-based wireless sensor networks, information-driven star topology and energy-saved mode are used, through which a blue master node can control more than seven slave node, the energy of each sensor node is reduced and secure management of each sensor node is improved.

Synergies between energy supply networks

DEFF Research Database (Denmark)

Wu, Jianzhnog; Yan, Jinyue; Desideri, Umberto

2017-01-01

Energy system integration uses a whole-system approach to optimize the synergies between energy supply networks to facilitate and coordinate the grid integration of distributed energy resources while enabling the synergies and conflicts between the local distribution networks and the national lev...... and integration of local renewables including solar energy wind geothermal waste heat and biomass is presented.......Energy system integration uses a whole-system approach to optimize the synergies between energy supply networks to facilitate and coordinate the grid integration of distributed energy resources while enabling the synergies and conflicts between the local distribution networks and the national level...... objectives to be understood and optimally coordinated. The latest research on the network coupling technologies analysis of synergies between energy supply networks and optimal use of synergies in network operation is discussed. A diagram on the possible interactions between different energy networks...

Energy landscapes of resting-state brain networks

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Takamitsu eWatanabe

2014-02-01

Full Text Available During rest, the human brain performs essential functions such as memory maintenance, which are associated with resting-state brain networks (RSNs including the default-mode network (DMN and frontoparietal network (FPN. Previous studies based on spiking-neuron network models and their reduced models, as well as those based on imaging data, suggest that resting-state network activity can be captured as attractor dynamics, i.e., dynamics of the brain state toward an attractive state and transitions between different attractors. Here, we analyze the energy landscapes of the RSNs by applying the maximum entropy model, or equivalently the Ising spin model, to human RSN data. We use the previously estimated parameter values to define the energy landscape, and the disconnectivity graph method to estimate the number of local energy minima (equivalent to attractors in attractor dynamics, the basin size, and hierarchical relationships among the different local minima. In both of the DMN and FPN, low-energy local minima tended to have large basins. A majority of the network states belonged to a basin of one of a few local minima. Therefore, a small number of local minima constituted the backbone of each RSN. In the DMN, the energy landscape consisted of two groups of low-energy local minima that are separated by a relatively high energy barrier. Within each group, the activity patterns of the local minima were similar, and different minima were connected by relatively low energy barriers. In the FPN, all dominant energy were separated by relatively low energy barriers such that they formed a single coarse-grained global minimum. Our results indicate that multistable attractor dynamics may underlie the DMN, but not the FPN, and assist memory maintenance with different memory states.

Energy Threshold-based Cluster Head Rotation for Routing Protocol in Wireless Sensor Networks

Directory of Open Access Journals (Sweden)

Hadi Raheem Ali

2018-05-01

Full Text Available Energy efficiency represents a fundamental issue in WSNs, since the network lifetime period entirely depends on the energy of sensor nodes, which are usually battery-operated. In this article, an unequal clustering-based routing protocol has been suggested, where parameters of energy, distance, and density are involved in the cluster head election. Besides, the sizes of clusters are unequal according to distance, energy, and density. Furthermore, the cluster heads are not changed every round unless the residual energy reaches a specific threshold of energy. The outcomes of the conducted simulation confirmed that the performance of the suggested protocol achieves improvement in energy efficiency.

Energy Aware Cluster-Based Routing in Flying Ad-Hoc Networks.

Science.gov (United States)

Aadil, Farhan; Raza, Ali; Khan, Muhammad Fahad; Maqsood, Muazzam; Mehmood, Irfan; Rho, Seungmin

2018-05-03

Flying ad-hoc networks (FANETs) are a very vibrant research area nowadays. They have many military and civil applications. Limited battery energy and the high mobility of micro unmanned aerial vehicles (UAVs) represent their two main problems, i.e., short flight time and inefficient routing. In this paper, we try to address both of these problems by means of efficient clustering. First, we adjust the transmission power of the UAVs by anticipating their operational requirements. Optimal transmission range will have minimum packet loss ratio (PLR) and better link quality, which ultimately save the energy consumed during communication. Second, we use a variant of the K-Means Density clustering algorithm for selection of cluster heads. Optimal cluster heads enhance the cluster lifetime and reduce the routing overhead. The proposed model outperforms the state of the art artificial intelligence techniques such as Ant Colony Optimization-based clustering algorithm and Grey Wolf Optimization-based clustering algorithm. The performance of the proposed algorithm is evaluated in term of number of clusters, cluster building time, cluster lifetime and energy consumption.

Energy Aware Cluster-Based Routing in Flying Ad-Hoc Networks

Directory of Open Access Journals (Sweden)

Farhan Aadil

2018-05-01

Full Text Available Flying ad-hoc networks (FANETs are a very vibrant research area nowadays. They have many military and civil applications. Limited battery energy and the high mobility of micro unmanned aerial vehicles (UAVs represent their two main problems, i.e., short flight time and inefficient routing. In this paper, we try to address both of these problems by means of efficient clustering. First, we adjust the transmission power of the UAVs by anticipating their operational requirements. Optimal transmission range will have minimum packet loss ratio (PLR and better link quality, which ultimately save the energy consumed during communication. Second, we use a variant of the K-Means Density clustering algorithm for selection of cluster heads. Optimal cluster heads enhance the cluster lifetime and reduce the routing overhead. The proposed model outperforms the state of the art artificial intelligence techniques such as Ant Colony Optimization-based clustering algorithm and Grey Wolf Optimization-based clustering algorithm. The performance of the proposed algorithm is evaluated in term of number of clusters, cluster building time, cluster lifetime and energy consumption.

Energy Cost Minimization in Heterogeneous Cellular Networks with Hybrid Energy Supplies

Directory of Open Access Journals (Sweden)

Bang Wang

2016-01-01

Full Text Available The ever increasing data demand has led to the significant increase of energy consumption in cellular mobile networks. Recent advancements in heterogeneous cellular networks and green energy supplied base stations provide promising solutions for cellular communications industry. In this article, we first review the motivations and challenges as well as approaches to address the energy cost minimization problem for such green heterogeneous networks. Owing to the diversities of mobile traffic and renewable energy, the energy cost minimization problem involves both temporal and spatial optimization of resource allocation. We next present a new solution to illustrate how to combine the optimization of the temporal green energy allocation and spatial mobile traffic distribution. The whole optimization problem is decomposed into four subproblems, and correspondingly our proposed solution is divided into four parts: energy consumption estimation, green energy allocation, user association, and green energy reallocation. Simulation results demonstrate that our proposed algorithm can significantly reduce the total energy cost.

Applications of neural networks in high energy physics

International Nuclear Information System (INIS)

Cutts, D.; Hoftun, J.S.; Nesic, D.; Sornborger, A.; Johnson, C.R.; Zeller, R.T.

1990-01-01

Neural network techniques provide promising solutions to pattern recognition problems in high energy physics. We discuss several applications of back propagation networks, and in particular describe the operation of an electron algorithm based on calorimeter energies. 5 refs., 5 figs., 1 tab

Energy Efficiency Perspectives of PMR Networks

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Marco Dolfi

2016-12-01

Full Text Available Recently, the concern about energy efficiency in wireless communications has been growing rapidly. Manufacturers and researchers have developed innovative solutions, highlighting the benefits in reducing operational expenditures (OPEX and carbon footprint. Professional Mobile Radio (PMR systems, like Terrestrial Trunked Radio (TETRA, have been designed to provide voice and data services to professional users. The energy consumption is one of the critical aspects of PMR broadband solutions and a major constraint for PMR services. The future convergence of PMR to the LTE system introduces a new topic in the research discussion about the energy efficiency of wireless systems. This paper focuses on the feasibility of energy efficient solutions for current and potentially future PMR networks, by providing a mathematical formulation of power consumption in TETRA base stations and assessing possible business models and energy saving solutions for enhanced mission-critical operations. The energy efficiency evaluation has been performed by taking into account the traffic load of a deployed TETRA regional network: in the considered network scenario with 150 base stations, significant OPEX savings up to 70 thousand Euros per year of operation are achieved. Moreover, the proposed solutions allow for saving more than 1 ton of CO 2 per year.

Energy Saving Scheme Based On Traffic Forwarding For Optical Fiber Access Networks

DEFF Research Database (Denmark)

Lopez, G. Arturo Rodes; Estaran Tolosa, Jose Manuel; Vegas Olmos, Juan José

2013-01-01

We report on an energy saving block that regroups and powers off OLTs during low traffic periods, resulting in energy savings up to 87,5% in the central office of optical access networks.......We report on an energy saving block that regroups and powers off OLTs during low traffic periods, resulting in energy savings up to 87,5% in the central office of optical access networks....

IMPROVING THE TRANSMISSION PERFORMANCE BASED ON MINIMIZING ENERGY IN MOBILE ADHOC NETWORKS

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Gundala Swathi

2015-06-01

Full Text Available Networking is collectively no of mobile nodes allocate users to correctly detect a distant environment. These wireless mobile networks want strong but simple, scalable, energy efficient and also self organize routing algorithms. In Mobile technology small quantity of power electronics and less power radio frequency have permit the expansion of small, comparatively economical and less power nodes, are associated in a wireless mobile networkIn this study we proposed method are: energy effectiveness, energetic occurrence zone and multiple hop TRANSMIT, taking into concern between the energy of transmit nodes and distance from the transmit node to the trusted neighbor node, link weight energy utilization and distance are measured as most important constraint for decide on greatest possible path from Zone Head (ZH to the neighbor node. In this we use the different constraints and lessen the quantity of distribution messages during the Transmit node choice point to decrease the energy utilization of the complete network.

Performance and energy efficiency in wireless self-organized networks

Energy Technology Data Exchange (ETDEWEB)

Gao, C.

2009-07-01

Self-organized packet radio networks (ad-hoc networks) and wireless sensor networks have got massive attention recently. One of critical problems in such networks is the energy efficiency, because wireless nodes are usually powered by battery. Energy efficiency design can dramatically increase the survivability and stability of wireless ad-hoc/sensor networks. In this thesis the energy efficiency has been considered at different protocol layers for wireless ad-hoc/sensor networks. The energy consumption of wireless nodes is inspected at the physical layer and MAC layer. At the network layer, some current routing protocols are compared and special attention has been paid to reactive routing protocols. A minimum hop analysis is given and according to the analysis result, a modification of AODV routing is proposed. A variation of transmit power can be also applied to clustering algorithm, which is believed to be able to control the scalability of network. Clustering a network can also improve the energy efficiency. We offer a clustering scheme based on the link state measurement and variation of transmit power of intra-cluster and inter-cluster transmission. Simulation shows that it can achieve both targets. In association with the clustering algorithm, a global synchronization scheme is proposed to increase the efficiency of clustering algorithm. The research attention has been also paid to self-organization for multi-hop cellular networks. A 2-hop 2-slot uplink proposal to infrastructure-based cellular networks. The proposed solution can significantly increase the throughput of uplink communication and reduce the energy consumption of wireless terminals. (orig.)

Examining the resilience of national energy systems: Measurements of diversity in production-based and consumption-based electricity in the globalization of trade networks

International Nuclear Information System (INIS)

Kharrazi, Ali; Sato, Masahiro; Yarime, Masaru; Nakayama, Hirofumi; Yu, Yadong; Kraines, Steven

2015-01-01

Energy is a critical component of achieving sustainable development. In addition to the three aspects of promoting access, renewables, and efficiency, the dimension of resilience in energy systems should also considered. The implementation of resilient energy systems requires a quantitative understanding of the socio-economic practices underlying such systems. Specifically, in line with the increasing globalization of trade, there remains a critical knowledge gap on the link between embodied energy in the production and consumption of traded goods. To bridge this knowledge gap, we investigate the resilience of global energy systems through an examination of a diversity measure of global embodied electricity trade based on multi-regional input-output (MRIO) networks. The significance of this research lies in its ability to utilize high resolution MRIO data sets in assessing the resilience of national energy systems. This research indicates that secure and responsible consumption requires the diversification of not only energy generation but also energy imports. This research will lay the ground for further research in the governance of resilience in global energy networks. - Highlights: • We examine the resilience of global embodied energy based on (MRIO) trade networks. • We propose a secure and responsible mode of thinking for national energy consumption. • Secure & responsible consumption requires diversity in energy generation and imports.

Optimizing Cellular Networks Enabled with Renewal Energy via Strategic Learning.

Science.gov (United States)

Sohn, Insoo; Liu, Huaping; Ansari, Nirwan

2015-01-01

An important issue in the cellular industry is the rising energy cost and carbon footprint due to the rapid expansion of the cellular infrastructure. Greening cellular networks has thus attracted attention. Among the promising green cellular network techniques, the renewable energy-powered cellular network has drawn increasing attention as a critical element towards reducing carbon emissions due to massive energy consumption in the base stations deployed in cellular networks. Game theory is a branch of mathematics that is used to evaluate and optimize systems with multiple players with conflicting objectives and has been successfully used to solve various problems in cellular networks. In this paper, we model the green energy utilization and power consumption optimization problem of a green cellular network as a pilot power selection strategic game and propose a novel distributed algorithm based on a strategic learning method. The simulation results indicate that the proposed algorithm achieves correlated equilibrium of the pilot power selection game, resulting in optimum green energy utilization and power consumption reduction.

A General Self-Organized Tree-Based Energy-Balance Routing Protocol for Wireless Sensor Network

Science.gov (United States)

Han, Zhao; Wu, Jie; Zhang, Jie; Liu, Liefeng; Tian, Kaiyun

2014-04-01

Wireless sensor network (WSN) is a system composed of a large number of low-cost micro-sensors. This network is used to collect and send various kinds of messages to a base station (BS). WSN consists of low-cost nodes with limited battery power, and the battery replacement is not easy for WSN with thousands of physically embedded nodes, which means energy efficient routing protocol should be employed to offer a long-life work time. To achieve the aim, we need not only to minimize total energy consumption but also to balance WSN load. Researchers have proposed many protocols such as LEACH, HEED, PEGASIS, TBC and PEDAP. In this paper, we propose a General Self-Organized Tree-Based Energy-Balance routing protocol (GSTEB) which builds a routing tree using a process where, for each round, BS assigns a root node and broadcasts this selection to all sensor nodes. Subsequently, each node selects its parent by considering only itself and its neighbors' information, thus making GSTEB a dynamic protocol. Simulation results show that GSTEB has a better performance than other protocols in balancing energy consumption, thus prolonging the lifetime of WSN.

Energy Cooperation in Ultradense Network Powered by Renewable Energy Based on Cluster and Learning Strategy

Directory of Open Access Journals (Sweden)

Chunhong Duo

2017-01-01

Full Text Available A new method about renewable energy cooperation among small base stations (SBSs is proposed, which is for maximizing the energy efficiency in ultradense network (UDN. In UDN each SBS is equipped with energy harvesting (EH unit, and the energy arrival times are modeled as a Poisson counting process. Firstly, SBSs of large traffic demands are selected as the clustering centers, and then all SBSs are clustered using dynamic k-means algorithm. Secondly, SBSs coordinate their renewable energy within each formed cluster. The process of energy cooperation among SBSs is considered as Markov decision process. Q-learning algorithm is utilized to optimize energy cooperation. In the algorithm there are four different actions and their corresponding reward functions. Q-learning explores the action as much as possible and predicts better action by calculating reward. In addition, ε greedy policy is used to ensure the algorithm convergence. Finally, simulation results show that the new method reduces data dimension and improves calculation speed, which furthermore improves the utilization of renewable energy and promotes the performance of UDN. Through online optimization, the proposed method can significantly improve the energy utilization rate and data transmission rate.

Energy Efficient Clustering Based Network Protocol Stack for 3D Airborne Monitoring System

Directory of Open Access Journals (Sweden)

Abhishek Joshi

2017-01-01

Full Text Available Wireless Sensor Network consists of large number of nodes densely deployed in ad hoc manner. Usually, most of the application areas of WSNs require two-dimensional (2D topology. Various emerging application areas such as airborne networks and underwater wireless sensor networks are usually deployed using three-dimensional (3D network topology. In this paper, a static 3D cluster-based network topology has been proposed for airborne networks. A network protocol stack consisting of various protocols such as TDMA MAC and dynamic routing along with services such as time synchronization, Cluster Head rotation, and power level management has been proposed for this airborne network. The proposed protocol stack has been implemented on the hardware platform consisting of number of TelosB nodes. This 3D airborne network architecture can be used to measure Air Quality Index (AQI in an area. Various parameters of network such as energy consumption, Cluster Head rotation, time synchronization, and Packet Delivery Ratio (PDR have been analyzed. Detailed description of the implementation of the protocol stack along with results of implementation has been provided in this paper.

Energy savings in mobile broadband network based on load predictions

DEFF Research Database (Denmark)

Samulevicius, Saulius; Pedersen, Torben Bach; Sørensen, Troels Bundgaard

2012-01-01

Abstract—The deployment of new network equipment is resulting in increasing energy consumption in mobile broadband networks (MBNs). This contributes to higher CO2 emissions. Over the last 10 years MBNs have grown considerably, and are still growing to meet the evolution in traffic volume carried...

Hybrid energy system evaluation in water supply system energy production: neural network approach

Energy Technology Data Exchange (ETDEWEB)

Goncalves, Fabio V.; Ramos, Helena M. [Civil Engineering Department, Instituto Superior Tecnico, Technical University of Lisbon, Av. Rovisco Pais, 1049-001, Lisbon (Portugal); Reis, Luisa Fernanda R. [Universidade de Sao Paulo, EESC/USP, Departamento de Hidraulica e Saneamento., Avenida do Trabalhador Saocarlense, 400, Sao Carlos-SP (Brazil)

2010-07-01

Water supply systems are large consumers of energy and the use of hybrid systems for green energy production is this new proposal. This work presents a computational model based on neural networks to determine the best configuration of a hybrid system to generate energy in water supply systems. In this study the energy sources to make this hybrid system can be the national power grid, micro-hydro and wind turbines. The artificial neural network is composed of six layers, trained to use data generated by a model of hybrid configuration and an economic simulator - CES. The reason for the development of an advanced model of forecasting based on neural networks is to allow rapid simulation and proper interaction with hydraulic and power model simulator - HPS. The results show that this computational model is useful as advanced decision support system in the design of configurations of hybrid power systems applied to water supply systems, improving the solutions in the development of its global energy efficiency.

A survey of energy conservation mechanisms for dynamic cluster based wireless sensor networks

International Nuclear Information System (INIS)

Enam, R.N.; Tahir, M.; Ahmed, S.; Qureshi, R.

2018-01-01

WSN (Wireless Sensor Network) is an emerging technology that has unlimited potential for numerous application areas including military, crisis management, environmental, transportation, medical, home/ city automations and smart spaces. But energy constrained nature of WSNs necessitates that their architecture and communicating protocols to be designed in an energy aware manner. Sensor data collection through clustering mechanisms has become a common strategy in WSN. This paper presents a survey report on the major perspectives with which energy conservation mechanisms has been proposed in dynamic cluster based WSNs so far. All the solutions discussed in this paper focus on the cluster based protocols only.We have covered a vast scale of existing energy efficient protocols and have categorized them in six categories. In the beginning of this paper the fundamentals of the energy constraint issues of WSNs have been discussed and an overview of the causes of energy consumptions at all layers of WSN has been given. Later in this paper several previously proposed energy efficient protocols of WSNs are presented. (author)

A Survey of Energy Conservation Mechanisms for Dynamic Cluster Based Wireless Sensor Networks

Directory of Open Access Journals (Sweden)

Rabia Noor Enam

2018-04-01

Full Text Available WSN (Wireless Sensor Network is an emerging technology that has unlimited potential for numerous application areas including military, crisis management, environmental, transportation, medical, home/ city automations and smart spaces. But energy constrained nature of WSNs necessitates that their architecture and communicating protocols to be designed in an energy aware manner. Sensor data collection through clustering mechanisms has become a common strategy in WSN. This paper presents a survey report on the major perspectives with which energy conservation mechanisms has been proposed in dynamic cluster based WSNs so far. All the solutions discussed in this paper focus on the cluster based protocols only.We have covered a vast scale of existing energy efficient protocols and have categorized them in six categories. In the beginning of this paper the fundamentals of the energy constraint issues of WSNs have been discussed and an overview of the causes of energy consumptions at all layers of WSN has been given. Later in this paper several previously proposed energy efficient protocols of WSNs are presented.

An Energy-Efficient and High-Quality Video Transmission Architecture in Wireless Video-Based Sensor Networks

Directory of Open Access Journals (Sweden)

Yasaman Samei

2008-08-01

Full Text Available Technological progress in the fields of Micro Electro-Mechanical Systems (MEMS and wireless communications and also the availability of CMOS cameras, microphones and small-scale array sensors, which may ubiquitously capture multimedia content from the field, have fostered the development of low-cost limited resources Wireless Video-based Sensor Networks (WVSN. With regards to the constraints of videobased sensor nodes and wireless sensor networks, a supporting video stream is not easy to implement with the present sensor network protocols. In this paper, a thorough architecture is presented for video transmission over WVSN called Energy-efficient and high-Quality Video transmission Architecture (EQV-Architecture. This architecture influences three layers of communication protocol stack and considers wireless video sensor nodes constraints like limited process and energy resources while video quality is preserved in the receiver side. Application, transport, and network layers are the layers in which the compression protocol, transport protocol, and routing protocol are proposed respectively, also a dropping scheme is presented in network layer. Simulation results over various environments with dissimilar conditions revealed the effectiveness of the architecture in improving the lifetime of the network as well as preserving the video quality.

An Energy-Efficient and High-Quality Video Transmission Architecture in Wireless Video-Based Sensor Networks.

Science.gov (United States)

Aghdasi, Hadi S; Abbaspour, Maghsoud; Moghadam, Mohsen Ebrahimi; Samei, Yasaman

2008-08-04

Technological progress in the fields of Micro Electro-Mechanical Systems (MEMS) and wireless communications and also the availability of CMOS cameras, microphones and small-scale array sensors, which may ubiquitously capture multimedia content from the field, have fostered the development of low-cost limited resources Wireless Video-based Sensor Networks (WVSN). With regards to the constraints of videobased sensor nodes and wireless sensor networks, a supporting video stream is not easy to implement with the present sensor network protocols. In this paper, a thorough architecture is presented for video transmission over WVSN called Energy-efficient and high-Quality Video transmission Architecture (EQV-Architecture). This architecture influences three layers of communication protocol stack and considers wireless video sensor nodes constraints like limited process and energy resources while video quality is preserved in the receiver side. Application, transport, and network layers are the layers in which the compression protocol, transport protocol, and routing protocol are proposed respectively, also a dropping scheme is presented in network layer. Simulation results over various environments with dissimilar conditions revealed the effectiveness of the architecture in improving the lifetime of the network as well as preserving the video quality.

Energy efficiency networks; Energieeffizienz-Netzwerke

Energy Technology Data Exchange (ETDEWEB)

Gruber, Anna [Forschungsgesellschaft fuer Energiewirtschaft mbH (FfE GmbH), Muenchen (Germany)

2011-07-01

Energy efficiency networks are an attractive method to increase the energy efficiency and to reduce the costs and CO{sub 2} emissions of the companies operating in this network. A special feature of the energy efficiency networks is the exchange of experiences and training of the energy managers. Energy efficiency networks consist of about ten to fifteen locally domiciled companies. During the project period of three to four years, there are two main phases. In the first phase, the initial consultation phase, the actual state of a company is captured, and measures to increase the efficiency and energy conservation are identified. Parallel to this, in the second phase every three months a meeting with the participating companies takes place. Experience exchange and implementation of energy efficiency measures are the focus of these meetings. Initial studies show that the increase of the energy efficiency during participating in the energy efficiency network almost can be doubled in comparison to the average of the industry.

Optimized Energy Procurement for Cellular Networks with Uncertain Renewable Energy Generation

KAUST Repository

Rached, Nadhir B.

2017-02-07

Renewable energy (RE) is an emerging solution for reducing carbon dioxide (CO2) emissions from cellular networks. One of the challenges of using RE sources is to handle its inherent uncertainty. In this paper, a RE powered cellular network is investigated. For a one-day operation cycle, the cellular network aims to reduce energy procurement costs from the smart grid by optimizing the amounts of energy procured from their locally deployed RE sources as well as from the smart grid. In addition to that, it aims to determine the extra amount of energy to be sold to the electrical grid at each time period. Chance constrained optimization is first proposed to deal with the randomness in the RE generation. Then, to make the optimization problem tractable, two well- know convex approximation methods, namely; Chernoff and Chebyshev based-approaches, are analyzed in details. Numerical results investigate the optimized energy procurement for various daily scenarios and compare between the performances of the employed convex approximation approaches.

Strategy on energy saving reconstruction of distribution networks based on life cycle cost

Science.gov (United States)

Chen, Xiaofei; Qiu, Zejing; Xu, Zhaoyang; Xiao, Chupeng

2017-08-01

Because the actual distribution network reconstruction project funds are often limited, the cost-benefit model and the decision-making method are crucial for distribution network energy saving reconstruction project. From the perspective of life cycle cost (LCC), firstly the research life cycle is determined for the energy saving reconstruction of distribution networks with multi-devices. Then, a new life cycle cost-benefit model for energy-saving reconstruction of distribution network is developed, in which the modification schemes include distribution transformers replacement, lines replacement and reactive power compensation. In the operation loss cost and maintenance cost area, the operation cost model considering the influence of load season characteristics and the maintenance cost segmental model of transformers are proposed. Finally, aiming at the highest energy saving profit per LCC, a decision-making method is developed while considering financial and technical constraints as well. The model and method are applied to a real distribution network reconstruction, and the results prove that the model and method are effective.

Energy Consumption Model and Measurement Results for Network Coding-enabled IEEE 802.11 Meshed Wireless Networks

DEFF Research Database (Denmark)

Paramanathan, Achuthan; Rasmussen, Ulrik Wilken; Hundebøll, Martin

2012-01-01

This paper presents an energy model and energy measurements for network coding enabled wireless meshed networks based on IEEE 802.11 technology. The energy model and the energy measurement testbed is limited to a simple Alice and Bob scenario. For this toy scenario we compare the energy usages...... for a system with and without network coding support. While network coding reduces the number of radio transmissions, the operational activity on the devices due to coding will be increased. We derive an analytical model for the energy consumption and compare it to real measurements for which we build...... a flexible, low cost tool to be able to measure at any given node in a meshed network. We verify the precision of our tool by comparing it to a sophisticated device. Our main results in this paper are the derivation of an analytical energy model, the implementation of a distributed energy measurement testbed...

Modelling electric trains energy consumption using Neural Networks

Energy Technology Data Exchange (ETDEWEB)

Martinez Fernandez, P.; Garcia Roman, C.; Insa Franco, R.

2016-07-01

Nowadays there is an evident concern regarding the efficiency and sustainability of the transport sector due to both the threat of climate change and the current financial crisis. This concern explains the growth of railways over the last years as they present an inherent efficiency compared to other transport means. However, in order to further expand their role, it is necessary to optimise their energy consumption so as to increase their competitiveness. Improving railways energy efficiency requires both reliable data and modelling tools that will allow the study of different variables and alternatives. With this need in mind, this paper presents the development of consumption models based on neural networks that calculate the energy consumption of electric trains. These networks have been trained based on an extensive set of consumption data measured in line 1 of the Valencia Metro Network. Once trained, the neural networks provide a reliable estimation of the vehicles consumption along a specific route when fed with input data such as train speed, acceleration or track longitudinal slope. These networks represent a useful modelling tool that may allow a deeper study of railway lines in terms of energy expenditure with the objective of reducing the costs and environmental impact associated to railways. (Author)

Improving Energy Efficiency of Cooperative Femtocell Networks via Base Station Switching Off

Directory of Open Access Journals (Sweden)

Woongsup Lee

2016-01-01

Full Text Available Recently, energy efficiency (EE of cellular networks has become an important performance metric, and several techniques have been proposed to increase the EE. Among them, turning off base stations (BSs when not needed is considered as one of the most powerful techniques due to its simple operation and effectiveness. Herein, we propose a novel BS switching-off technique for cooperative femtocell networks where multiple femtocell BSs (FBSs simultaneously send packets to the same mobile station (MS. Unlike conventional schemes, cooperative operation of FBSs, also known as coordinated multipoint (CoMP transmission, is considered to determine which BSs are turned off in the proposed technique. We first formulate the optimization problem to find the optimal set of FBSs to be turned off. Then, we propose a suboptimal scheme operating in a distributed manner in order to reduce the computational complexity of the optimal scheme. The suboptimal scheme is based on throughput ratio (TR which specifies the importance of a particular FBS for the cooperative transmission. Through simulations, we show that the energy consumption can be greatly reduced with the proposed technique, compared with conventional schemes. Moreover, we show that the suboptimal scheme also achieves the near-optimal performance even without the excessive computations.

The network-based energy management system for convenience stores

Energy Technology Data Exchange (ETDEWEB)

Wang, An-Ping; Hsu, Pau-Lo [Department of Electrical and Control Engineering, National Chiao-Tung University, 1001 Ta-Hsiue Road, Hsinchu City 310 (China)

2008-07-01

Convenience stores generally consume energy higher than other retailing merchants. As the problem of energy shortage becomes more serious during summer, almost all convenience stores sign a contract with power plants, which provides for fines if demand limiting occurs in Taiwan and many other countries. Therefore, a reliable and effective method to reduce their utility consumption is required for modern business and industry. This research integrates the remote sensors, the control network, and the embedded system technologies to construct a distributed energy management control system for dedicated convenience stores. Energy consumption can thus be reasonably managed with demand limits by measuring and analyzing the power consumption sources in four major subsystems of convenience stores, namely, (1) air-conditioning, (2) lighting, (3) heating, and (4) refrigeration. By applying the proposed demand prediction and control method, the demand limiting condition can be properly predicted, and the possible peak load can thus be eliminated via the network control mechanism. Moreover, by integrating the LonWork fieldbus and the WinCE operating system (OS), the proposed system has been successfully applied to a convenience store. The experimental results indicate that the proposed distributed energy management system suitably predicts the peak loading condition and successfully prevents its occurrence by switching the air-conditioning system without affecting the indoor temperature regulation. (author)

Energy Model of Networks-on-Chip and a Bus

NARCIS (Netherlands)

Wolkotte, P.T.; Smit, Gerardus Johannes Maria; Kavaldjiev, N.K.; Becker, Jens E.; Becker, Jürgen; Nurmi, J.; Takala, J.; Hamalainen, T.D.

2005-01-01

A Network-on-Chip (NoC) is an energy-efficient onchip communication architecture for Multi-Processor Systemon-Chip (MPSoC) architectures. In earlier papers we proposed two Network-on-Chip architectures based on packet-switching and circuit-switching. In this paper we derive an energy model for both

Data-Based Energy Efficient Clustered Routing Protocol for Wireless Sensors Networks – Tabuk Flood Monitoring System Case Study

Directory of Open Access Journals (Sweden)

Ammar Babiker

2017-10-01

Full Text Available Energy efficiency has been considered as the most important issue in wireless sensor networks. As in many applications, wireless sensors are scattered in a wide harsh area, where the battery replacement or charging will be quite difficult and it is the most important challenge. Therefore, the design of energy saving mechanism becomes mandatory in most recent research. In this paper, a new energy efficient clustered routing protocol is proposed: the proposed protocol is based on analyzing the data collected from the sensors in a base-station. Based on this analysis the cluster head will be selected as the one with the most useful data. Then, a variable time slot is specified to each sensor to minimize the transmission of repetitive and un-useful data. The proposed protocol Data-Based Energy Efficient Clustered Routing Protocol for Wireless Sensors Networks (DCRP was compared with the famous energy efficient LEACH protocol and also with one of the recent energy efficient routing protocols named Position Responsive Routing Protocol (PRRP. DCRP has been used in monitoring the floods in Tabuk area –Saudi Arabia. It shows comparatively better results.

Modeling and Analysis of Energy Conservation Scheme Based on Duty Cycling in Wireless Ad Hoc Sensor Network

Science.gov (United States)

Chung, Yun Won; Hwang, Ho Young

2010-01-01

In sensor network, energy conservation is one of the most critical issues since sensor nodes should perform a sensing task for a long time (e.g., lasting a few years) but the battery of them cannot be replaced in most practical situations. For this purpose, numerous energy conservation schemes have been proposed and duty cycling scheme is considered the most suitable power conservation technique, where sensor nodes alternate between states having different levels of power consumption. In order to analyze the energy consumption of energy conservation scheme based on duty cycling, it is essential to obtain the probability of each state. In this paper, we analytically derive steady state probability of sensor node states, i.e., sleep, listen, and active states, based on traffic characteristics and timer values, i.e., sleep timer, listen timer, and active timer. The effect of traffic characteristics and timer values on the steady state probability and energy consumption is analyzed in detail. Our work can provide sensor network operators guideline for selecting appropriate timer values for efficient energy conservation. The analytical methodology developed in this paper can be extended to other energy conservation schemes based on duty cycling with different sensor node states, without much difficulty. PMID:22219676

Modeling and Analysis of Energy Conservation Scheme Based on Duty Cycling in Wireless Ad Hoc Sensor Network

Directory of Open Access Journals (Sweden)

Yun Won Chung

2010-06-01

Full Text Available In sensor network, energy conservation is one of the most critical issues since sensor nodes should perform a sensing task for a long time (e.g., lasting a few years but the battery of them cannot be replaced in most practical situations. For this purpose, numerous energy conservation schemes have been proposed and duty cycling scheme is considered the most suitable power conservation technique, where sensor nodes alternate between states having different levels of power consumption. In order to analyze the energy consumption of energy conservation scheme based on duty cycling, it is essential to obtain the probability of each state. In this paper, we analytically derive steady state probability of sensor node states, i.e., sleep, listen, and active states, based on traffic characteristics and timer values, i.e., sleep timer, listen timer, and active timer. The effect of traffic characteristics and timer values on the steady state probability and energy consumption is analyzed in detail. Our work can provide sensor network operators guideline for selecting appropriate timer values for efficient energy conservation. The analytical methodology developed in this paper can be extended to other energy conservation schemes based on duty cycling with different sensor node states, without much difficulty.

Energy efficient mechanisms for high-performance Wireless Sensor Networks

Science.gov (United States)

Alsaify, Baha'adnan

2009-12-01

Due to recent advances in microelectronics, the development of low cost, small, and energy efficient devices became possible. Those advances led to the birth of the Wireless Sensor Networks (WSNs). WSNs consist of a large set of sensor nodes equipped with communication capabilities, scattered in the area to monitor. Researchers focus on several aspects of WSNs. Such aspects include the quality of service the WSNs provide (data delivery delay, accuracy of data, etc...), the scalability of the network to contain thousands of sensor nodes (the terms node and sensor node are being used interchangeably), the robustness of the network (allowing the network to work even if a certain percentage of nodes fails), and making the energy consumption in the network as low as possible to prolong the network's lifetime. In this thesis, we present an approach that can be applied to the sensing devices that are scattered in an area for Sensor Networks. This work will use the well-known approach of using a awaking scheduling to extend the network's lifespan. We designed a scheduling algorithm that will reduce the delay's upper bound the reported data will experience, while at the same time keeps the advantages that are offered by the use of the awaking scheduling -- the energy consumption reduction which will lead to the increase in the network's lifetime. The wakeup scheduling is based on the location of the node relative to its neighbors and its distance from the Base Station (the terms Base Station and sink are being used interchangeably). We apply the proposed method to a set of simulated nodes using the "ONE Simulator". We test the performance of this approach with three other approaches -- Direct Routing technique, the well known LEACH algorithm, and a multi-parent scheduling algorithm. We demonstrate a good improvement on the network's quality of service and a reduction of the consumed energy.

Energy efficient wireless sensor networks by using a fuzzy-based solution

Science.gov (United States)

Tirrito, Salvatore; Nicolosi, Giuseppina

2016-12-01

Wireless Sensor Networks are characterized by a distributed architecture realized by a set of autonomous electronic devices able to sense data from the surrounding environment and to communicate among them. These devices are battery powered since they may be used even to monitor hazardous events in inaccessible areas. As a consequence, it is preferable to assure the adoption of energy management solutions in order to extend the WSN lifetime, as far as possible. Moreover, it is crucial to guarantee that the nodes receive the transmitted data correctly. It is clear that trading off power optimization and quality of service has become one the most important concerns when dealing with modern systems based on WSNs. This paper introduces a solution based on a Fuzzy Logic Controller (FLC) focusing on the minimization of energy consumption of wireless sensor nodes. This is made possible because the sleeping time of these nodes is dynamically regulated by a FLC.

An energy-efficient data gathering protocol in large wireless sensor network

Science.gov (United States)

Wang, Yamin; Zhang, Ruihua; Tao, Shizhong

2006-11-01

Wireless sensor network consisting of a large number of small sensors with low-power transceiver can be an effective tool for gathering data in a variety of environment. The collected data must be transmitted to the base station for further processing. Since a network consists of sensors with limited battery energy, the method for data gathering and routing must be energy efficient in order to prolong the lifetime of the network. In this paper, we presented an energy-efficient data gathering protocol in wireless sensor network. The new protocol used data fusion technology clusters nodes into groups and builds a chain among the cluster heads according to a hybrid of the residual energy and distance to the base station. Results in stochastic geometry are used to derive the optimum parameter of our algorithm that minimizes the total energy spent in the network. Simulation results show performance superiority of the new protocol.

Energy Efficiency and Network Performance: A Reality Check in SDN-Based 5G Systems

Directory of Open Access Journals (Sweden)

Leonardo Ochoa-Aday

2017-12-01

Full Text Available The increasing power consumption and related environmental implications currently generated by large data networks have become a major concern over the last decade. Given the drastic traffic increase expected in 5G dense environments, the energy consumption problem becomes even more concerning and challenging. In this context, Software-Defined Networks (SDN, a key technology enabler for 5G systems, can be seen as an attractive solution. In these programmable networks, an energy-aware solution could be easily implemented leveraging the capabilities provided by control and data plane separation. This paper investigates the impact of energy-aware routing on network performance. To that end, we propose a novel energy-aware mechanism that reduces the number of active links in SDN with multiple controllers, considering in-band control traffic. The proposed strategy exploits knowledge of the network topology combined with traffic engineering techniques to reduce the overall power consumption. Therefore, two heuristic algorithms are designed: a static network configuration and a dynamic energy-aware routing. Significant values of switched-off links are reached in the simulations where real topologies and demands data are used. Moreover, the obtained results confirm that crucial network parameters such as control traffic delay, data path latency, link utilization and Ternary Content Addressable Memory (TCAM occupation are affected by the performance-agnostic energy-aware model.

Which energy networks for tomorrow?

International Nuclear Information System (INIS)

Lenoir, D.; Couturier, Ch.; Batot, Ph.; Jedliczka, M.; Belon, D.; Goy, E.; Bureau, L.

2010-01-01

A set of brief articles outlines the importance of energy networks of all kinds for the future of energy conservation. Thus, all networks (communication, data, production command and control) will have a role to play to make all energy networks (electricity, gas, heat, cold, water, sewage, telecommunications) communicate with each other, and a new consumption/production model will have to be developed for each territory by taking into account its capacities to improve energy efficiency and valorize renewable energies. The authors also propose a historical perspective of network development and of their trend to become interconnected and complementary, comment the governance issue in terms of concession, evoke the supply of public networks with biogas (legal framework under development), discuss the value of the project of development of smart grids, suggest that a better electricity demand management could be an efficient alternative to grid development, comment the context and implications of the European directive Linky, outline that heat networks will contribute to the reduction of the environmental impact of buildings, evoke the issue of cold water networks and their impact on air conditioning, present the original heat network which is about to be built in Saint-Brieuc, etc.

Evaluating Maximum Wind Energy Exploitation in Active Distribution Networks

DEFF Research Database (Denmark)

Siano, Pierluigi; Chen, Peiyuan; Chen, Zhe

2010-01-01

The increased spreading of distributed and renewable generation requires moving towards active management of distribution networks. In this paper, in order to evaluate maximum wind energy exploitation in active distribution networks, a method based on a multi-period optimal power flow (OPF......) analysis is proposed. Active network management schemes such as coordinated voltage control, energy curtailment and power factor control are integrated in the method in order to investigate their impacts on the maximization of wind energy exploitation. Some case studies, using real data from a Danish...... distribution system, confirmed the effectiveness of the proposed method in evaluating the optimal applications of active management schemes to increase wind energy harvesting without costly network reinforcement for the connection of wind generation....

Secure energy efficient routing protocol for wireless sensor network

Directory of Open Access Journals (Sweden)

Das Ayan Kumar

2016-03-01

Full Text Available The ease of deployment of economic sensor networks has always been a boon to disaster management applications. However, their vulnerability to a number of security threats makes communication a challenging task. This paper proposes a new routing technique to prevent from both external threats and internal threats like hello flooding, eavesdropping and wormhole attack. In this approach one way hash chain is used to reduce the energy drainage. Level based event driven clustering also helps to save energy. The simulation results show that the proposed scheme extends network lifetime even when the cluster based wireless sensor network is under attack.

Energy flow models for the estimation of technical losses in distribution network

International Nuclear Information System (INIS)

Au, Mau Teng; Tan, Chin Hooi

2013-01-01

This paper presents energy flow models developed to estimate technical losses in distribution network. Energy flow models applied in this paper is based on input energy and peak demand of distribution network, feeder length and peak demand, transformer loading capacity, and load factor. Two case studies, an urban distribution network and a rural distribution network are used to illustrate application of the energy flow models. Results on technical losses obtained for the two distribution networks are consistent and comparable to network of similar types and characteristics. Hence, the energy flow models are suitable for practical application.

Solar Energy Innovation Network | Solar Research | NREL

Science.gov (United States)

Energy Innovation Network Solar Energy Innovation Network The Solar Energy Innovation Network grid. Text version The Solar Energy Innovation Network is a collaborative research effort administered (DOE) Solar Energy Technologies Office to develop and demonstrate new ways for solar energy to improve

Forecasting building energy consumption with hybrid genetic algorithm-hierarchical adaptive network-based fuzzy inference system

Energy Technology Data Exchange (ETDEWEB)

Li, Kangji [Institute of Cyber-Systems and Control, Zhejiang University, Hangzhou 310027 (China); School of Electricity Information Engineering, Jiangsu University, Zhenjiang 212013 (China); Su, Hongye [Institute of Cyber-Systems and Control, Zhejiang University, Hangzhou 310027 (China)

2010-11-15

There are several ways to forecast building energy consumption, varying from simple regression to models based on physical principles. In this paper, a new method, namely, the hybrid genetic algorithm-hierarchical adaptive network-based fuzzy inference system (GA-HANFIS) model is developed. In this model, hierarchical structure decreases the rule base dimension. Both clustering and rule base parameters are optimized by GAs and neural networks (NNs). The model is applied to predict a hotel's daily air conditioning consumption for a period over 3 months. The results obtained by the proposed model are presented and compared with regular method of NNs, which indicates that GA-HANFIS model possesses better performance than NNs in terms of their forecasting accuracy. (author)

Energy efficiency in elastic-bandwidth optical networks

DEFF Research Database (Denmark)

Vizcaino, Jorge Lopez; Ye, Yabin; Tafur Monroy, Idelfonso

2011-01-01

of elastic bandwidth allocation, opens new horizons in the operation of optical networks. In this paper, we compare the network planning problem in an elastic bandwidth CO-OFDM-based network and a fixed-grid WDM network. We highlight the benefits that bandwidth elasticity and the selection of different......The forecasted growth in the Internet traffic has made the operators and industry to be concerned about the power consumption of the networks, and to become interested in alternatives to plan and operate the networks in a more energy efficient manner. The introduction of OFDM, and its property...

ENERGY EFFICIENT ROUTING PROTOCOLS FOR WIRELESS AD HOC NETWORKS – A SURVEY

Directory of Open Access Journals (Sweden)

K. Sankar

2012-06-01

Full Text Available Reducing energy consumption, primarily with the goal of extending the lifetime of battery-powered devices, has emerged as a fundamental challenge in wireless communication. The performance of the medium access control (MAC scheme not only has a fairly significant end-result on the behaviour of the routing approach employed, but also on the energy consumption of the wireless network interface card (NIC. We investigate the inadequacies of the MAC schemes designed for ad hoc wireless networks in the context of power awareness herein. The topology changes due to uncontrollable factors such as node mobility, weather, interference, noise, as well as on controllable parameters such as transmission power and antenna direction results in significant amount of energy loss. Controlling rapid topology changes by minimizing the maximum transmission power used in ad hoc wireless networks, while still maintaining networks connectivity can prolong battery life and hence network lifetime considerably. In addition, we systematically explore the potential energy consumption pitfalls of non–power-based and power based routing schemes. We suggest a thorough energy-based performance survey of energy aware routing protocols for wireless mobile ad-hoc networks. We also present the statistical performance metrics measured by our simulations.

Maximizing hosting capacity of renewable energy sources in distribution networks: A multi-objective and scenario-based approach

International Nuclear Information System (INIS)

Rabiee, Abbas; Mohseni-Bonab, Seyed Masoud

2017-01-01

Due to the development of renewable energy sources (RESs), maximization of hosting capacity (HC) of RESs has gained significant interest in the existing and future power systems. HC maximization should be performed considering various technical constraints like power flow equations, limits on the distribution feeders' voltages and currents, as well as economic constraints such as the cost of energy procurement from the upstream network and power generation by RESs. RESs are volatile and uncertain in nature. Thus, it is necessary to handle their inherent uncertainties in the HC maximization problem. Wind power is now the fastest growing RESs around the world. Hence, in this paper a stochastic multi-objective optimization model is proposed to maximize the distribution network's HC for wind power and minimize the energy procurement costs in a wind integrated power system. The following objective functions are considered: 1) Cost of the purchased energy from upstream network (to be minimized) and 2) Operation and maintenance cost of wind farms. The proposed model is examined on a standard radial 69 bus distribution feeder and a practical 152 bus distribution system. The numerical results substantiate that the proposed model is an effective tool for distribution network operators (DNOs) to consider both technical and economic aspects of distribution network's HC for RESs. - Highlights: • Hosting capacity of wind power is improved in distribution feeders. • A stochastic multi-objective optimization model is proposed. • Wind power and load uncertainties are modeled by scenario based approach. • Purchased energy cost from upstream network and O&M cost of wind farms are used.

The Optimization Based Dynamic and Cyclic Working Strategies for Rechargeable Wireless Sensor Networks with Multiple Base Stations and Wireless Energy Transfer Devices

Science.gov (United States)

Ding, Xu; Han, Jianghong; Shi, Lei

2015-01-01

In this paper, the optimal working schemes for wireless sensor networks with multiple base stations and wireless energy transfer devices are proposed. The wireless energy transfer devices also work as data gatherers while charging sensor nodes. The wireless sensor network is firstly divided into sub networks according to the concept of Voronoi diagram. Then, the entire energy replenishing procedure is split into the pre-normal and normal energy replenishing stages. With the objective of maximizing the sojourn time ratio of the wireless energy transfer device, a continuous time optimization problem for the normal energy replenishing cycle is formed according to constraints with which sensor nodes and wireless energy transfer devices should comply. Later on, the continuous time optimization problem is reshaped into a discrete multi-phased optimization problem, which yields the identical optimality. After linearizing it, we obtain a linear programming problem that can be solved efficiently. The working strategies of both sensor nodes and wireless energy transfer devices in the pre-normal replenishing stage are also discussed in this paper. The intensive simulations exhibit the dynamic and cyclic working schemes for the entire energy replenishing procedure. Additionally, a way of eliminating “bottleneck” sensor nodes is also developed in this paper. PMID:25785305

The optimization based dynamic and cyclic working strategies for rechargeable wireless sensor networks with multiple base stations and wireless energy transfer devices.

Science.gov (United States)

Ding, Xu; Han, Jianghong; Shi, Lei

2015-03-16

In this paper, the optimal working schemes for wireless sensor networks with multiple base stations and wireless energy transfer devices are proposed. The wireless energy transfer devices also work as data gatherers while charging sensor nodes. The wireless sensor network is firstly divided into sub networks according to the concept of Voronoi diagram. Then, the entire energy replenishing procedure is split into the pre-normal and normal energy replenishing stages. With the objective of maximizing the sojourn time ratio of the wireless energy transfer device, a continuous time optimization problem for the normal energy replenishing cycle is formed according to constraints with which sensor nodes and wireless energy transfer devices should comply. Later on, the continuous time optimization problem is reshaped into a discrete multi-phased optimization problem, which yields the identical optimality. After linearizing it, we obtain a linear programming problem that can be solved efficiently. The working strategies of both sensor nodes and wireless energy transfer devices in the pre-normal replenishing stage are also discussed in this paper. The intensive simulations exhibit the dynamic and cyclic working schemes for the entire energy replenishing procedure. Additionally, a way of eliminating "bottleneck" sensor nodes is also developed in this paper.

Counter-Based Broadcast Scheme Considering Reachability, Network Density, and Energy Efficiency for Wireless Sensor Networks.

Science.gov (United States)

Jung, Ji-Young; Seo, Dong-Yoon; Lee, Jung-Ryun

2018-01-04

A wireless sensor network (WSN) is emerging as an innovative method for gathering information that will significantly improve the reliability and efficiency of infrastructure systems. Broadcast is a common method to disseminate information in WSNs. A variety of counter-based broadcast schemes have been proposed to mitigate the broadcast-storm problems, using the count threshold value and a random access delay. However, because of the limited propagation of the broadcast-message, there exists a trade-off in a sense that redundant retransmissions of the broadcast-message become low and energy efficiency of a node is enhanced, but reachability become low. Therefore, it is necessary to study an efficient counter-based broadcast scheme that can dynamically adjust the random access delay and count threshold value to ensure high reachability, low redundant of broadcast-messages, and low energy consumption of nodes. Thus, in this paper, we first measure the additional coverage provided by a node that receives the same broadcast-message from two neighbor nodes, in order to achieve high reachability with low redundant retransmissions of broadcast-messages. Second, we propose a new counter-based broadcast scheme considering the size of the additional coverage area, distance between the node and the broadcasting node, remaining battery of the node, and variations of the node density. Finally, we evaluate performance of the proposed scheme compared with the existing counter-based broadcast schemes. Simulation results show that the proposed scheme outperforms the existing schemes in terms of saved rebroadcasts, reachability, and total energy consumption.

Use of artificial neural networks for transport energy demand modeling

International Nuclear Information System (INIS)

Murat, Yetis Sazi; Ceylan, Halim

2006-01-01

The paper illustrates an artificial neural network (ANN) approach based on supervised neural networks for the transport energy demand forecasting using socio-economic and transport related indicators. The ANN transport energy demand model is developed. The actual forecast is obtained using a feed forward neural network, trained with back propagation algorithm. In order to investigate the influence of socio-economic indicators on the transport energy demand, the ANN is analyzed based on gross national product (GNP), population and the total annual average veh-km along with historical energy data available from 1970 to 2001. Comparing model predictions with energy data in testing period performs the model validation. The projections are made with two scenarios. It is obtained that the ANN reflects the fluctuation in historical data for both dependent and independent variables. The results obtained bear out the suitability of the adopted methodology for the transport energy-forecasting problem

Stability-Aware Geographic Routing in Energy Harvesting Wireless Sensor Networks

Directory of Open Access Journals (Sweden)

Tran Dinh Hieu

2016-05-01

Full Text Available A new generation of wireless sensor networks that harvest energy from environmental sources such as solar, vibration, and thermoelectric to power sensor nodes is emerging to solve the problem of energy limitation. Based on the photo-voltaic model, this research proposes a stability-aware geographic routing for reliable data transmissions in energy-harvesting wireless sensor networks (EH-WSNs to provide a reliable routes selection method and potentially achieve an unlimited network lifetime. Specifically, the influences of link quality, represented by the estimated packet reception rate, on network performance is investigated. Simulation results show that the proposed method outperforms an energy-harvesting-aware method in terms of energy consumption, the average number of hops, and the packet delivery ratio.

Scaling up local energy infrastructure; An agent-based model of the emergence of district heating networks

International Nuclear Information System (INIS)

Busch, Jonathan; Roelich, Katy; Bale, Catherine S.E.; Knoeri, Christof

2017-01-01

The potential contribution of local energy infrastructure – such as heat networks – to the transition to a low carbon economy is increasingly recognised in international, national and municipal policy. Creating the policy environment to foster the scaling up of local energy infrastructure is, however, still challenging; despite national policy action and local authority interest the growth of heat networks in UK cities remains slow. Techno-economic energy system models commonly used to inform policy are not designed to address institutional and governance barriers. We present an agent-based model of heat network development in UK cities in which policy interventions aimed at the institutional and governance barriers faced by diverse actors can be explored. Three types of project instigators are included – municipal, commercial and community – which have distinct decision heuristics and capabilities and follow a multi-stage development process. Scenarios of policy interventions developed in a companion modelling approach indicate that the effect of interventions differs between actors depending on their capabilities. Successful interventions account for the specific motivations and capabilities of different actors, provide a portfolio of support along the development process and recognise the important strategic role of local authorities in supporting low carbon energy infrastructure. - Highlights: • Energy policy should account for diverse actor motivations and capabilities. • Project development is a multi-stage process, not a one-off event. • Participatory agent-based modelling can inform policy that accounts for complexity. • Policy should take a portfolio approach to providing support. • Local authorities have an important strategic role in local infrastructure.

Methods for Reducing the Energy Consumption of Mobile Broadband Networks

DEFF Research Database (Denmark)

Micallef, Gilbert

2010-01-01

Up until recently, very little consideration has been given towards reducing the energy consumption of the networks supporting mobile communication. This has now become an important issue since with the predicted boost in traffic, network operators are required to upgrade and extend their networks......, increasing also their overall energy consumption. However, traffic analysis shows that during a 24 hour period, the volume of carried traffic varies continuously, with the network operating anywhere close to its full capacity for very short periods of time. The problem is that during hours of low network...... traffic the energy consumption remains high. This article proposes two major solutions for mitigating this problem. In the first case, an energy saving between 14% and 36% is observed by allowing the network to dynamically optimize its available capacity based on the traffic being carried. In the second...

Radio Frequency Energy Harvesting for Long Lifetime Wireless Sensor Networks

DEFF Research Database (Denmark)

Han, Bo; Nielsen, Rasmus Hjorth; Prasad, Ramjee

2014-01-01

In wireless sensor networks energy scarcity is a major concern on energy consumption, and by properly designing on the node network architecture or selecting efficient protocols of the networks, the maximum energy can be reduced significantly thereby increasing the network lifetime. However......, in most of the cases, the sensor nodes are either powered by non-replaceable batteries, or there will be a considerable replacement cost. Thus a self-rechargeable sensor node design is necessary: the sensor node should be able to harvest energy from the environment. Among the existing techniques......, harvesting energy from the radio frequency (RF) waves gives the lowest system design. Previous research on RF energy harvesting is based on the model that the radio energy is omnidirectional in the air. In this paper, a directional transmission/receiving model is proposed which can further overcome the path...

An Energy-Efficient Adaptive Clustering Protocol for Wireless Sensor Network

Directory of Open Access Journals (Sweden)

Lü Tao

2013-05-01

Full Text Available An energy-efficient adaptive clustering hierarchy EEACH in wireless sensor networks based on LEACH and LEACH-C is proposed in this paper. The main consideration is the LEACH cluster structure, each cluster is not uniform energy consumption; LEACH-C using a centralized algorithm can achieve better clustering, but do not contribute to the implementation of distributed. In EEACH, we analyzed the effects of different numbers of cluster member node on the network energy consumption; and re-planning time slice to balance the energy consumption of each cluster; and avoid the energy hole problem by reasonable cluster head selection algorithm. Its objective is to balance the energy consumption and maximize the network lifetime. Analysis and simulation results show that EEACH provides more uniform energy consumption among nodes and can prolong network lifetime compared to LEACH and LEACH-C.

A Mixed Transmission Strategy to Achieve Energy Balancing in Wireless Sensor Networks

DEFF Research Database (Denmark)

Liu, Tong; Gu, Tao; Jin, Ning

2017-01-01

In this paper, we investigate the problem of energy balanced data collection in wireless sensor networks, aiming to balance energy consumption among all sensor nodes during the data propagation process. Energy balanced data collection can potentially save energy consumption and prolong network...... lifetime, and hence, it has many practical implications for sensor network design and deployment. The traditional hop-by-hop transmission model allows a sensor node to propagate its packets in a hop-by-hop manner toward the sink, resulting in poor energy balancing for the entire network. To address...... the problem, we apply a slice-based energy model, and divide the problem into inter-slice and intra-slice energy balancing problems. We then propose a probability-based strategy named inter-slice mixed transmission protocol and an intra-slice forwarding technique to address each of the problems. We propose...

A Centralized Detection of Sinkhole Attacks Based on Energy Level of the Nodes on Cluster-Based Wireless Sensor Networks

Directory of Open Access Journals (Sweden)

Merve Nilay Aydın

2017-10-01

Full Text Available Wireless Sensor Networks is consist of thousands of small and low-cost devices, which communicate over wireless medium. Due to locating in harsh environment and having limited resources, WSN is prone to various attacks. One of the most dangerous attacks threatening WSN is the sinkhole attack. In this paper, sinkhole attack is modelled on a cluster-based WSN, and a centralized detection algorithm based on the remaining energies of the nodes is proposed. The simulations were run for different values of energy thresholds and various numbers of nodes. The performance of the system was investigated over total energy consumption in the system, the number of packets arrived at base station and true detection rate of the sinkhole node(s. The results showed that the proposed method is energy-efficient and detects the malicious nodes with a 100% accuracy for all number of nodes.

Characterization of Energy Availability in RF Energy Harvesting Networks

Directory of Open Access Journals (Sweden)

Daniela Oliveira

2016-01-01

Full Text Available The multiple nodes forming a Radio Frequency (RF Energy Harvesting Network (RF-EHN have the capability of converting received electromagnetic RF signals in energy that can be used to power a network device (the energy harvester. Traditionally the RF signals are provided by high power transmitters (e.g., base stations operating in the neighborhood of the harvesters. Admitting that the transmitters are spatially distributed according to a spatial Poisson process, we start by characterizing the distribution of the RF power received by an energy harvester node. Considering Gamma shadowing and Rayleigh fading, we show that the received RF power can be approximated by the sum of multiple Gamma distributions with different scale and shape parameters. Using the distribution of the received RF power, we derive the probability of a node having enough energy to transmit a packet after a given amount of charging time. The RF power distribution and the probability of a harvester having enough energy to transmit a packet are validated through simulation. The numerical results obtained with the proposed analysis are close to the ones obtained through simulation, which confirms the accuracy of the proposed analysis.

Energy Efficient Probabilistic Broadcasting for Mobile Ad-Hoc Network

Science.gov (United States)

Kumar, Sumit; Mehfuz, Shabana

2017-06-01

In mobile ad-hoc network (MANETs) flooding method is used for broadcasting route request (RREQ) packet from one node to another node for route discovery. This is the simplest method of broadcasting of RREQ packets but it often results in broadcast storm problem, originating collisions and congestion of packets in the network. A probabilistic broadcasting is one of the widely used broadcasting scheme for route discovery in MANETs and provides solution for broadcasting storm problem. But it does not consider limited energy of the battery of the nodes. In this paper, a new energy efficient probabilistic broadcasting (EEPB) is proposed in which probability of broadcasting RREQs is calculated with respect to remaining energy of nodes. The analysis of simulation results clearly indicate that an EEPB route discovery scheme in ad-hoc on demand distance vector (AODV) can increase the network lifetime with a decrease in the average power consumption and RREQ packet overhead. It also decreases the number of dropped packets in the network, in comparison to other EEPB schemes like energy constraint gossip (ECG), energy aware gossip (EAG), energy based gossip (EBG) and network lifetime through energy efficient broadcast gossip (NEBG).

Energy-Aware Multipath Routing Scheme Based on Particle Swarm Optimization in Mobile Ad Hoc Networks.

Science.gov (United States)

Robinson, Y Harold; Rajaram, M

2015-01-01

Mobile ad hoc network (MANET) is a collection of autonomous mobile nodes forming an ad hoc network without fixed infrastructure. Dynamic topology property of MANET may degrade the performance of the network. However, multipath selection is a great challenging task to improve the network lifetime. We proposed an energy-aware multipath routing scheme based on particle swarm optimization (EMPSO) that uses continuous time recurrent neural network (CTRNN) to solve optimization problems. CTRNN finds the optimal loop-free paths to solve link disjoint paths in a MANET. The CTRNN is used as an optimum path selection technique that produces a set of optimal paths between source and destination. In CTRNN, particle swarm optimization (PSO) method is primly used for training the RNN. The proposed scheme uses the reliability measures such as transmission cost, energy factor, and the optimal traffic ratio between source and destination to increase routing performance. In this scheme, optimal loop-free paths can be found using PSO to seek better link quality nodes in route discovery phase. PSO optimizes a problem by iteratively trying to get a better solution with regard to a measure of quality. The proposed scheme discovers multiple loop-free paths by using PSO technique.

Energy-Aware Routing Protocol for Ad Hoc Wireless Sensor Networks

Directory of Open Access Journals (Sweden)

Mann Raminder P

2005-01-01

Full Text Available Wireless ad hoc sensor networks differ from wireless ad hoc networks from the following perspectives: low energy, lightweight routing protocols, and adaptive communication patterns. This paper proposes an energy-aware routing protocol (EARP suitable for ad hoc wireless sensor networks and presents an analysis for its energy consumption in various phases of route discovery and maintenance. Based on the energy consumption associated with route request processing, EARP advocates the minimization of route requests by allocating dynamic route expiry times. This paper introduces a unique mechanism for estimation of route expiry time based on the probability of route validity, which is a function of time, number of hops, and mobility parameters. In contrast to AODV, EARP reduces the repeated flooding of route requests by maintaining valid routes for longer durations.

Energy prediction using spatiotemporal pattern networks

Energy Technology Data Exchange (ETDEWEB)

Jiang, Zhanhong; Liu, Chao; Akintayo, Adedotun; Henze, Gregor P.; Sarkar, Soumik

2017-11-01

This paper presents a novel data-driven technique based on the spatiotemporal pattern network (STPN) for energy/power prediction for complex dynamical systems. Built on symbolic dynamical filtering, the STPN framework is used to capture not only the individual system characteristics but also the pair-wise causal dependencies among different sub-systems. To quantify causal dependencies, a mutual information based metric is presented and an energy prediction approach is subsequently proposed based on the STPN framework. To validate the proposed scheme, two case studies are presented, one involving wind turbine power prediction (supply side energy) using the Western Wind Integration data set generated by the National Renewable Energy Laboratory (NREL) for identifying spatiotemporal characteristics, and the other, residential electric energy disaggregation (demand side energy) using the Building America 2010 data set from NREL for exploring temporal features. In the energy disaggregation context, convex programming techniques beyond the STPN framework are developed and applied to achieve improved disaggregation performance.

Mixed H2/H∞-Based Fusion Estimation for Energy-Limited Multi-Sensors in Wearable Body Networks

Directory of Open Access Journals (Sweden)

Chao Li

2017-12-01

Full Text Available In wireless sensor networks, sensor nodes collect plenty of data for each time period. If all of data are transmitted to a Fusion Center (FC, the power of sensor node would run out rapidly. On the other hand, the data also needs a filter to remove the noise. Therefore, an efficient fusion estimation model, which can save the energy of the sensor nodes while maintaining higher accuracy, is needed. This paper proposes a novel mixed H2/H∞-based energy-efficient fusion estimation model (MHEEFE for energy-limited Wearable Body Networks. In the proposed model, the communication cost is firstly reduced efficiently while keeping the estimation accuracy. Then, the parameters in quantization method are discussed, and we confirm them by an optimization method with some prior knowledge. Besides, some calculation methods of important parameters are researched which make the final estimates more stable. Finally, an iteration-based weight calculation algorithm is presented, which can improve the fault tolerance of the final estimate. In the simulation, the impacts of some pivotal parameters are discussed. Meanwhile, compared with the other related models, the MHEEFE shows a better performance in accuracy, energy-efficiency and fault tolerance.

Synaptic energy drives the information processing mechanisms in spiking neural networks.

Science.gov (United States)

El Laithy, Karim; Bogdan, Martin

2014-04-01

Flow of energy and free energy minimization underpins almost every aspect of naturally occurring physical mechanisms. Inspired by this fact this work establishes an energy-based framework that spans the multi-scale range of biological neural systems and integrates synaptic dynamic, synchronous spiking activity and neural states into one consistent working paradigm. Following a bottom-up approach, a hypothetical energy function is proposed for dynamic synaptic models based on the theoretical thermodynamic principles and the Hopfield networks. We show that a synapse exposes stable operating points in terms of its excitatory postsynaptic potential as a function of its synaptic strength. We postulate that synapses in a network operating at these stable points can drive this network to an internal state of synchronous firing. The presented analysis is related to the widely investigated temporal coherent activities (cell assemblies) over a certain range of time scales (binding-by-synchrony). This introduces a novel explanation of the observed (poly)synchronous activities within networks regarding the synaptic (coupling) functionality. On a network level the transitions from one firing scheme to the other express discrete sets of neural states. The neural states exist as long as the network sustains the internal synaptic energy.

Optimized smart grid energy procurement for LTE networks using evolutionary algorithms

KAUST Repository

Ghazzai, Hakim

2014-11-01

Energy efficiency aspects in cellular networks can contribute significantly to reducing worldwide greenhouse gas emissions. The base station (BS) sleeping strategy has become a well-known technique to achieve energy savings by switching off redundant BSs mainly for lightly loaded networks. Moreover, introducing renewable energy as an alternative power source has become a real challenge among network operators. In this paper, we formulate an optimization problem that aims to maximize the profit of Long-Term Evolution (LTE) cellular operators and to simultaneously minimize the CO2 emissions in green wireless cellular networks without affecting the desired quality of service (QoS). The BS sleeping strategy lends itself to an interesting implementation using several heuristic approaches, such as the genetic (GA) and particle swarm optimization (PSO) algorithms. In this paper, we propose GA-based and PSO-based methods that reduce the energy consumption of BSs by not only shutting down underutilized BSs but by optimizing the amounts of energy procured from different retailers (renewable energy and electricity retailers), as well. A comparison with another previously proposed algorithm is also carried out to evaluate the performance and the computational complexity of the employed methods.

Energy-aware virtual network embedding in flexi-grid optical networks

Science.gov (United States)

Lin, Rongping; Luo, Shan; Wang, Haoran; Wang, Sheng; Chen, Bin

2018-01-01

Virtual network embedding (VNE) problem is to map multiple heterogeneous virtual networks (VN) on a shared substrate network, which mitigate the ossification of the substrate network. Meanwhile, energy efficiency has been widely considered in the network design. In this paper, we aim to solve the energy-aware VNE problem in flexi-grid optical networks. We provide an integer linear programming (ILP) formulation to minimize the power increment of each arriving VN request. We also propose a polynomial-time heuristic algorithm where virtual links are embedded sequentially to keep a reasonable acceptance ratio and maintain a low energy consumption. Numerical results show the functionality of the heuristic algorithm in a 24-node network.

Agent-based reactive power management of power distribution networks with distributed energy generation

International Nuclear Information System (INIS)

Rahman, M.S.; Mahmud, M.A.; Oo, A.M.T.; Pota, H.R.; Hossain, M.J.

2016-01-01

Highlights: • A coordinated multi-agent system is proposed for reactive power management. • A linear quadratic regulator with a proportional integral controller is designed. • Proposed multi-agent scheme provides accurate estimation and control of the system. • Voltage stability is improved with proper power management for different scenarios. • Results obtained from the proposed scheme is compared to the traditional approach. - Abstract: In this paper, a new agent-based distributed reactive power management scheme is proposed to improve the voltage stability of energy distribution systems with distributed generation units. Three types of agents – distribution system agent, estimator agent, and control agent are developed within the multi-agent framework. The agents simultaneously coordinated their activities through the online information and energy flow. The overall achievement of the proposed scheme depends on the coordination between two tasks – (i) estimation of reactive power using voltage variation formula and (ii) necessary control actions to provide the estimated reactive power to the distribution networks through the distributed static synchronous compensators. A linear quadratic regulator with a proportional integrator is designed for the control agent in order to control the reactive component of the current and the DC voltage of the compensators. The performance of the proposed scheme is tested on a 10-bus power distribution network under various scenarios. The effectiveness is validated by comparing the proposed approach to the conventional proportional integral control approach. It is found that, the agent-based scheme provides excellent robust performance under various operating conditions of the power distribution network.

Minimum energy control and optimal-satisfactory control of Boolean control network

International Nuclear Information System (INIS)

Li, Fangfei; Lu, Xiwen

2013-01-01

In the literatures, to transfer the Boolean control network from the initial state to the desired state, the expenditure of energy has been rarely considered. Motivated by this, this Letter investigates the minimum energy control and optimal-satisfactory control of Boolean control network. Based on the semi-tensor product of matrices and Floyd's algorithm, minimum energy, constrained minimum energy and optimal-satisfactory control design for Boolean control network are given respectively. A numerical example is presented to illustrate the efficiency of the obtained results.

Forming of the regional core transport network taking into account the allocation of alternative energy sources based on artificial intelligence methods

OpenAIRE

Marina ZHURAVSKAYA; Vladimir TARASYAN

2014-01-01

In the modern world the alternative energy sources, which considerably depend on a region, play more and more significant role. However, the transition of regions to new energy sources lead to the change of transport and logistic network configuration. The formation of optimal core transport network today is a guarantee of the successful economic development of a region tomorrow. The present article studies the issue of advanced core transport network development in a region based on the ...

Energy Aware Simple Ant Routing Algorithm for Wireless Sensor Networks

Directory of Open Access Journals (Sweden)

Sohail Jabbar

2015-01-01

Full Text Available Network lifetime is one of the most prominent barriers in deploying wireless sensor networks for large-scale applications because these networks employ sensors with nonrenewable scarce energy resources. Sensor nodes dissipate most of their energy in complex routing mechanisms. To cope with limited energy problem, we present EASARA, an energy aware simple ant routing algorithm based on ant colony optimization. Unlike most algorithms, EASARA strives to avoid low energy routes and optimizes the routing process through selection of least hop count path with more energy. It consists of three phases, that is, route discovery, forwarding node, and route selection. We have improved the route discovery procedure and mainly concentrate on energy efficient forwarding node and route selection, so that the network lifetime can be prolonged. The four possible cases of forwarding node and route selection are presented. The performance of EASARA is validated through simulation. Simulation results demonstrate the performance supremacy of EASARA over contemporary scheme in terms of various metrics.

A Trust-Based Secure Routing Scheme Using the Traceback Approach for Energy-Harvesting Wireless Sensor Networks

Directory of Open Access Journals (Sweden)

Jiawei Tang

2018-03-01

Full Text Available The Internet of things (IoT is composed of billions of sensing devices that are subject to threats stemming from increasing reliance on communications technologies. A Trust-Based Secure Routing (TBSR scheme using the traceback approach is proposed to improve the security of data routing and maximize the use of available energy in Energy-Harvesting Wireless Sensor Networks (EHWSNs. The main contributions of a TBSR are (a the source nodes send data and notification to sinks through disjoint paths, separately; in such a mechanism, the data and notification can be verified independently to ensure their security. (b Furthermore, the data and notification adopt a dynamic probability of marking and logging approach during the routing. Therefore, when attacked, the network will adopt the traceback approach to locate and clear malicious nodes to ensure security. The probability of marking is determined based on the level of battery remaining; when nodes harvest more energy, the probability of marking is higher, which can improve network security. Because if the probability of marking is higher, the number of marked nodes on the data packet routing path will be more, and the sink will be more likely to trace back the data packet routing path and find malicious nodes according to this notification. When data packets are routed again, they tend to bypass these malicious nodes, which make the success rate of routing higher and lead to improved network security. When the battery level is low, the probability of marking will be decreased, which is able to save energy. For logging, when the battery level is high, the network adopts a larger probability of marking and smaller probability of logging to transmit notification to the sink, which can reserve enough storage space to meet the storage demand for the period of the battery on low level; when the battery level is low, increasing the probability of logging can reduce energy consumption. After the level of

A Trust-Based Secure Routing Scheme Using the Traceback Approach for Energy-Harvesting Wireless Sensor Networks.

Science.gov (United States)

Tang, Jiawei; Liu, Anfeng; Zhang, Jian; Xiong, Neal N; Zeng, Zhiwen; Wang, Tian

2018-03-01

The Internet of things (IoT) is composed of billions of sensing devices that are subject to threats stemming from increasing reliance on communications technologies. A Trust-Based Secure Routing (TBSR) scheme using the traceback approach is proposed to improve the security of data routing and maximize the use of available energy in Energy-Harvesting Wireless Sensor Networks (EHWSNs). The main contributions of a TBSR are (a) the source nodes send data and notification to sinks through disjoint paths, separately; in such a mechanism, the data and notification can be verified independently to ensure their security. (b) Furthermore, the data and notification adopt a dynamic probability of marking and logging approach during the routing. Therefore, when attacked, the network will adopt the traceback approach to locate and clear malicious nodes to ensure security. The probability of marking is determined based on the level of battery remaining; when nodes harvest more energy, the probability of marking is higher, which can improve network security. Because if the probability of marking is higher, the number of marked nodes on the data packet routing path will be more, and the sink will be more likely to trace back the data packet routing path and find malicious nodes according to this notification. When data packets are routed again, they tend to bypass these malicious nodes, which make the success rate of routing higher and lead to improved network security. When the battery level is low, the probability of marking will be decreased, which is able to save energy. For logging, when the battery level is high, the network adopts a larger probability of marking and smaller probability of logging to transmit notification to the sink, which can reserve enough storage space to meet the storage demand for the period of the battery on low level; when the battery level is low, increasing the probability of logging can reduce energy consumption. After the level of battery

Energy efficient evolution of mobile broadband networks

Energy Technology Data Exchange (ETDEWEB)

Micallef, G.

2013-04-15

Over the last decade, the mobile communications industry has broken through some remarkable barriers, pushing further and transforming the way people communicate and access information. As the volume of traffic carried by mobile networks maintains an insatiable growth, mobile network operators are required to ensure that networks can scale accordingly. In addition to upgrading existing networks, a number of operators have already started to rollout a further radio access technology layer, Long Term Evolution, or LTE. In addition to enhancing network capacity, operators are also required to adhere to public commitments for reducing their energy and carbon footprint. In 2008 Vodafone stated that by the year 2020, efforts for reducing emissions are expected to halve emissions registered in the year 2006/7. In addition to presenting a more environmentally conscious brand, this is also hoped to reduce costs, which, based on increasing energy prices and necessary network upgrades are likely to increase. Since base station sites make up for about 75% of the power consumption in mobile networks, studies are focused on this specific network element. A number of factors believed to play a role in the power consumption of mobile networks are separately investigated and later combined, providing a realistic indication of how the consumption is expected to evolve. This is also used as an indication to determine how likely it is for operators to achieve power consumption and emission targets. In order for mobile network operators to upgrade existing infrastructure different options are available. Irrespective of the selected option, capacity upgrades are bound to increase the power consumption of the network. Carried through case studies, a first analysis compares a number of network evolution strategies, determining which provides the necessary performance while limiting the increase in power consumption. Overall, it is noted that a hybrid solution involving the upgrade of

Energy efficient evolution of mobile broadband networks

Energy Technology Data Exchange (ETDEWEB)

Micallef, G.

2013-04-15

Over the last decade, the mobile communications industry has broken through some remarkable barriers, pushing further and transforming the way people communicate and access information. As the volume of traffic carried by mobile networks maintains an insatiable growth, mobile network operators are required to ensure that networks can scale accordingly. In addition to upgrading existing networks, a number of operators have already started to rollout a further radio access technology layer, Long Term Evolution, or LTE. In addition to enhancing network capacity, operators are also required to adhere to public commitments for reducing their energy and carbon footprint. In 2008 Vodafone stated that by the year 2020, efforts for reducing emissions are expected to halve emissions registered in the year 2006/7. In addition to presenting a more environmentally conscious brand, this is also hoped to reduce costs, which, based on increasing energy prices and necessary network upgrades are likely to increase. Since base station sites make up for about 75% of the power consumption in mobile networks, studies are focused on this specific network element. A number of factors believed to play a role in the power consumption of mobile networks are separately investigated and later combined, providing a realistic indication of how the consumption is expected to evolve. This is also used as an indication to determine how likely it is for operators to achieve power consumption and emission targets. In order for mobile network operators to upgrade existing infrastructure different options are available. Irrespective of the selected option, capacity upgrades are bound to increase the power consumption of the network. Carried through case studies, a first analysis compares a number of network evolution strategies, determining which provides the necessary performance while limiting the increase in power consumption. Overall, it is noted that a hybrid solution involving the upgrade of

A Uniform Energy Consumption Algorithm for Wireless Sensor and Actuator Networks Based on Dynamic Polling Point Selection

Science.gov (United States)

Li, Shuo; Peng, Jun; Liu, Weirong; Zhu, Zhengfa; Lin, Kuo-Chi

2014-01-01

Recent research has indicated that using the mobility of the actuator in wireless sensor and actuator networks (WSANs) to achieve mobile data collection can greatly increase the sensor network lifetime. However, mobile data collection may result in unacceptable collection delays in the network if the path of the actuator is too long. Because real-time network applications require meeting data collection delay constraints, planning the path of the actuator is a very important issue to balance the prolongation of the network lifetime and the reduction of the data collection delay. In this paper, a multi-hop routing mobile data collection algorithm is proposed based on dynamic polling point selection with delay constraints to address this issue. The algorithm can actively update the selection of the actuator's polling points according to the sensor nodes' residual energies and their locations while also considering the collection delay constraint. It also dynamically constructs the multi-hop routing trees rooted by these polling points to balance the sensor node energy consumption and the extension of the network lifetime. The effectiveness of the algorithm is validated by simulation. PMID:24451455

Tariffing of energy measured consumers in the distribution network

International Nuclear Information System (INIS)

2006-01-01

Criteria for socio-economic effective tariffing of energy-measured clients in the distribution network are discussed (i.e. households, leisure homes and smaller business clients), this means consumers that do not have hourly measurements or effect measurements. The tariffs should be based on variable segments that reflect short-term marginal costs in the network (in practice loss of transfer) and fixed segments that to the least extent possible influence the consumers' decisions in the choice of energy solutions, both in short term and long term. High-priced energy segments and effect based fixed segments may give unfortunate socio-economic price signals compared to the marginal long-term network costs. A fixed segment per measurement unit is in principle completely neutral, but it is to some extent vulnerable to strategic adjustments if the consumers choose collective measurement. This is not necessarily a big problem in practice (author)

Optimized energy-delay sub-network routing protocol development and implementation for wireless sensor networks

International Nuclear Information System (INIS)

Fonda, James W; Zawodniok, Maciej; Jagannathan, S; Watkins, Steve E

2008-01-01

The development and the implementation issues of a reactive optimized energy-delay sub-network routing (OEDSR) protocol for wireless sensor networks (WSN) are introduced and its performance is contrasted with the popular ad hoc on-demand distance vector (AODV) routing protocol. Analytical results illustrate the performance of the proposed OEDSR protocol, while experimental results utilizing a hardware testbed under various scenarios demonstrate improvements in energy efficiency of the OEDSR protocol. A hardware platform constructed at the University of Missouri-Rolla (UMR), now the Missouri University of Science and Technology (MST), based on the Generation 4 Smart Sensor Node (G4-SSN) prototyping platform is also described. Performance improvements are shown in terms of end-to-end (E2E) delay, throughput, route-set-up time and drop rates and energy usage is given for three topologies, including a mobile topology. Additionally, results from the hardware testbed provide valuable lessons for network deployments. Under testing OEDSR provides a factor of ten improvement in the energy used in the routing session and extends network lifetime compared to AODV. Depletion experiments show that the time until the first node failure is extended by a factor of three with the network depleting and network lifetime is extended by 6.7%

OPEX Savings Based on Energy Efficient Strategies in NREN Core Optical Networks

DEFF Research Database (Denmark)

Turus, Ioan; Fagertun, Anna Manolova; Kleist, Josva

2014-01-01

wavelengths and new circuits are established based on a predefined dimensioning plan. However, because of the continuous increase in the overall traffic demand (estimated to be between 30 % and 60 % per year [1] ) as well as due to the more and more heterogeneous behavior of the incoming requests...... in core optical networks. One proposal is to define differ ent operational states for the optoelectronic components – OFF, IDLE and ON – which correspond to different levels of energy consumption. Another solution is to use advanced transponder architectures (i.e. elastic or flexible transponders...

Energy-aware scheduling of surveillance in wireless multimedia sensor networks.

Science.gov (United States)

Wang, Xue; Wang, Sheng; Ma, Junjie; Sun, Xinyao

2010-01-01

Wireless sensor networks involve a large number of sensor nodes with limited energy supply, which impacts the behavior of their application. In wireless multimedia sensor networks, sensor nodes are equipped with audio and visual information collection modules. Multimedia contents are ubiquitously retrieved in surveillance applications. To solve the energy problems during target surveillance with wireless multimedia sensor networks, an energy-aware sensor scheduling method is proposed in this paper. Sensor nodes which acquire acoustic signals are deployed randomly in the sensing fields. Target localization is based on the signal energy feature provided by multiple sensor nodes, employing particle swarm optimization (PSO). During the target surveillance procedure, sensor nodes are adaptively grouped in a totally distributed manner. Specially, the target motion information is extracted by a forecasting algorithm, which is based on the hidden Markov model (HMM). The forecasting results are utilized to awaken sensor node in the vicinity of future target position. According to the two properties, signal energy feature and residual energy, the sensor nodes decide whether to participate in target detection separately with a fuzzy control approach. Meanwhile, the local routing scheme of data transmission towards the observer is discussed. Experimental results demonstrate the efficiency of energy-aware scheduling of surveillance in wireless multimedia sensor network, where significant energy saving is achieved by the sensor awakening approach and data transmission paths are calculated with low computational complexity.

Energy Efficiency Analysis for Dynamic Routing in Optical Transport Networks

DEFF Research Database (Denmark)

Vizcaíno, Jorge López; Ye, Yabin; Tafur Monroy, Idelfonso

2012-01-01

The energy efficiency in telecommunication networks is gaining more relevance as the Internet traffic is growing. The introduction of OFDM and dynamic operation opens new horizons in the operation of optical networks, improving the network flexibility and its efficiency. In this paper, we compare...... the performance in terms of energy efficiency of a flexible-grid OFDM-based solution with a fixed-grid WDM network in a dynamic scenario with time-varying connections. We highlight the benefits that the bandwidth elasticity and the flexibility of selecting different modulation formats can offer compared...

Energy Harvesting in Heterogeneous Networks with Hybrid Powered Communication Systems

KAUST Repository

Alsharoa, Ahmad; Celik, Abdulkadir; Kamal, Ahmed E.

2018-01-01

In this paper, we investigate an energy efficient and energy harvesting (EH) system model in heterogeneous networks (HetNets) where all base stations (BSS) are equipped to harvest energy from renewable energy sources. We consider a hybrid power

Neural Network Based Maximum Power Point Tracking Control with Quadratic Boost Converter for PMSG—Wind Energy Conversion System

Directory of Open Access Journals (Sweden)

Ramji Tiwari

2018-02-01

Full Text Available This paper proposes an artificial neural network (ANN based maximum power point tracking (MPPT control strategy for wind energy conversion system (WECS implemented with a DC/DC converter. The proposed topology utilizes a radial basis function network (RBFN based neural network control strategy to extract the maximum available power from the wind velocity. The results are compared with a classical Perturb and Observe (P&O method and Back propagation network (BPN method. In order to achieve a high voltage rating, the system is implemented with a quadratic boost converter and the performance of the converter is validated with a boost and single ended primary inductance converter (SEPIC. The performance of the MPPT technique along with a DC/DC converter is demonstrated using MATLAB/Simulink.

Energy Sciences Network (ESnet)

Data.gov (United States)

Federal Laboratory Consortium — The Energy Sciences Network is the Department of Energy’s high-speed network that provides the high-bandwidth, reliable connections that link scientists at national...

Locally Integrated Energy Sectors supported by renewable network management within municipalities

International Nuclear Information System (INIS)

Kostevšek, Anja; Petek, Janez; Čuček, Lidija; Klemeš, Jiří Jaromír; Varbanov, Petar Sabev

2015-01-01

The decarbonisation of energy systems is one of the important issues of the present energy policies. One of the ways of achieving this is to focus on local energy systems, thus ensuring as much as possible their heat and power self-sufficiency by applying local renewable resource integration and transformation of the renewable energy. Increasing the share of renewables within the local energy balance could be accomplished by using a variety of approaches. One possibility is combining the Locally Integrated Energy Sectors' concept with the novel management and organisation of a renewables-based network. As a first priority, the proposed comprehensive approach focuses on increasing the energy efficiency of municipal heat and power systems using the Locally Integrated Energy Sectors' concept, which is followed by the integration of renewable energy sources with the establishment of a renewable-based network. The proposed approach is illustrated by a case study of district heating based on wood biomass for the municipality Ormož, Slovenia by integrating various end-users from different sectors. - Highlights: • The paper presents a new approach for accelerated inception of RES in municipalities. • LIES with RES network increases energy efficiency and accelerates RES integration. • A demonstration case of district heating on wood biomass within Ormož was performed.

Localization of Energy Harvesting Empowered Underwater Optical Wireless Sensor Networks

KAUST Repository

Saeed, Nasir

2017-12-20

In this paper, a received signal strength (RSS) based localization technique is developed for energy harvesting underwater optical wireless sensor networks (EH-UOWSNs), where the optical noise sources and channel impairments of seawater pose significant challenges for range estimation. Energy limitation is another major problem due to the limited battery power and difficulty in replacing or recharging the battery of an underwater sensor node. In the proposed framework, sensor nodes with insufficient battery, harvest the energy and starts communicating once it has sufficient energy storage. Network localization is carried out by measuring the RSSs of active nodes, which are modeled based on the underwater optical communication channel characteristics. Thereafter, block kernel matrices are computed for the RSS based range measurements. Unlike the traditional shortest-path approach, the proposed technique reduces the shortest path estimation for each block kernel matrix. Once the complete block kernel matrices are available, a closed form localization technique is developed to find the location of every optical sensor node in the network. Furthermore, an analytical expression for Cramer Rao lower bound (CRLB) is derived as a benchmark to compare the localization performance of the proposed technique. Finally, extensive simulations show that the proposed technique outperforms the well-known network localization techniques.

Energy-Efficient Cluster-Based Service Discovery in Wireless Sensor Networks

NARCIS (Netherlands)

Marin Perianu, Raluca; Scholten, Johan; Havinga, Paul J.M.; Hartel, Pieter H.

We propose an energy-efficient service discovery protocol for wireless sensor networks. Our solution exploits a cluster overlay, where the clusterhead nodes form a distributed service registry. A service lookup results in visiting only the clusterhead nodes. We aim for minimizing the communication

Energy-Efficient Cluster-Based Service Discovery in Wireless Sensor Networks

NARCIS (Netherlands)

Marin Perianu, Raluca; Scholten, Johan; Havinga, Paul J.M.; Hartel, Pieter H.

2006-01-01

We propose an energy-efficient service discovery protocol for wireless sensor networks. Our solution exploits a cluster overlay, where the clusterhead nodes form a distributed service registry. A service lookup results in visiting only the clusterhead nodes. We aim for minimizing the communication

Efficient Vector-Based Forwarding for Underwater Sensor Networks

Directory of Open Access Journals (Sweden)

Peng Xie

2010-01-01

Full Text Available Underwater Sensor Networks (UWSNs are significantly different from terrestrial sensor networks in the following aspects: low bandwidth, high latency, node mobility, high error probability, and 3-dimensional space. These new features bring many challenges to the network protocol design of UWSNs. In this paper, we tackle one fundamental problem in UWSNs: robust, scalable, and energy efficient routing. We propose vector-based forwarding (VBF, a geographic routing protocol. In VBF, the forwarding path is guided by a vector from the source to the target, no state information is required on the sensor nodes, and only a small fraction of the nodes is involved in routing. To improve the robustness, packets are forwarded in redundant and interleaved paths. Further, a localized and distributed self-adaptation algorithm allows the nodes to reduce energy consumption by discarding redundant packets. VBF performs well in dense networks. For sparse networks, we propose a hop-by-hop vector-based forwarding (HH-VBF protocol, which adapts the vector-based approach at every hop. We evaluate the performance of VBF and HH-VBF through extensive simulations. The simulation results show that VBF achieves high packet delivery ratio and energy efficiency in dense networks and HH-VBF has high packet delivery ratio even in sparse networks.

Energy-efficient algorithm for broadcasting in ad hoc wireless sensor networks.

Science.gov (United States)

Xiong, Naixue; Huang, Xingbo; Cheng, Hongju; Wan, Zheng

2013-04-12

Broadcasting is a common and basic operation used to support various network protocols in wireless networks. To achieve energy-efficient broadcasting is especially important for ad hoc wireless sensor networks because sensors are generally powered by batteries with limited lifetimes. Energy consumption for broadcast operations can be reduced by minimizing the number of relay nodes based on the observation that data transmission processes consume more energy than data reception processes in the sensor nodes, and how to improve the network lifetime is always an interesting issue in sensor network research. The minimum-energy broadcast problem is then equivalent to the problem of finding the minimum Connected Dominating Set (CDS) for a connected graph that is proved NP-complete. In this paper, we introduce an Efficient Minimum CDS algorithm (EMCDS) with help of a proposed ordered sequence list. EMCDS does not concern itself with node energy and broadcast operations might fail if relay nodes are out of energy. Next we have proposed a Minimum Energy-consumption Broadcast Scheme (MEBS) with a modified version of EMCDS, and aimed at providing an efficient scheduling scheme with maximized network lifetime. The simulation results show that the proposed EMCDS algorithm can find smaller CDS compared with related works, and the MEBS can help to increase the network lifetime by efficiently balancing energy among nodes in the networks.

A Novel Scheme for an Energy Efficient Internet of Things Based on Wireless Sensor Networks.

Science.gov (United States)

Rani, Shalli; Talwar, Rajneesh; Malhotra, Jyoteesh; Ahmed, Syed Hassan; Sarkar, Mahasweta; Song, Houbing

2015-11-12

One of the emerging networking standards that gap between the physical world and the cyber one is the Internet of Things. In the Internet of Things, smart objects communicate with each other, data are gathered and certain requests of users are satisfied by different queried data. The development of energy efficient schemes for the IoT is a challenging issue as the IoT becomes more complex due to its large scale the current techniques of wireless sensor networks cannot be applied directly to the IoT. To achieve the green networked IoT, this paper addresses energy efficiency issues by proposing a novel deployment scheme. This scheme, introduces: (1) a hierarchical network design; (2) a model for the energy efficient IoT; (3) a minimum energy consumption transmission algorithm to implement the optimal model. The simulation results show that the new scheme is more energy efficient and flexible than traditional WSN schemes and consequently it can be implemented for efficient communication in the IoT.

Prediction-Based Energy Saving Mechanism in 3GPP NB-IoT Networks.

Science.gov (United States)

Lee, Jinseong; Lee, Jaiyong

2017-09-01

The current expansion of the Internet of things (IoT) demands improved communication platforms that support a wide area with low energy consumption. The 3rd Generation Partnership Project introduced narrowband IoT (NB-IoT) as IoT communication solutions. NB-IoT devices should be available for over 10 years without requiring a battery replacement. Thus, a low energy consumption is essential for the successful deployment of this technology. Given that a high amount of energy is consumed for radio transmission by the power amplifier, reducing the uplink transmission time is key to ensure a long lifespan of an IoT device. In this paper, we propose a prediction-based energy saving mechanism (PBESM) that is focused on enhanced uplink transmission. The mechanism consists of two parts: first, the network architecture that predicts the uplink packet occurrence through a deep packet inspection; second, an algorithm that predicts the processing delay and pre-assigns radio resources to enhance the scheduling request procedure. In this way, our mechanism reduces the number of random accesses and the energy consumed by radio transmission. Simulation results showed that the energy consumption using the proposed PBESM is reduced by up to 34% in comparison with that in the conventional NB-IoT method.

A Novel Energy Efficient Topology Control Scheme Based on a Coverage-Preserving and Sleep Scheduling Model for Sensor Networks.

Science.gov (United States)

Shi, Binbin; Wei, Wei; Wang, Yihuai; Shu, Wanneng

2016-10-14

In high-density sensor networks, scheduling some sensor nodes to be in the sleep mode while other sensor nodes remain active for monitoring or forwarding packets is an effective control scheme to conserve energy. In this paper, a Coverage-Preserving Control Scheduling Scheme (CPCSS) based on a cloud model and redundancy degree in sensor networks is proposed. Firstly, the normal cloud model is adopted for calculating the similarity degree between the sensor nodes in terms of their historical data, and then all nodes in each grid of the target area can be classified into several categories. Secondly, the redundancy degree of a node is calculated according to its sensing area being covered by the neighboring sensors. Finally, a centralized approximation algorithm based on the partition of the target area is designed to obtain the approximate minimum set of nodes, which can retain the sufficient coverage of the target region and ensure the connectivity of the network at the same time. The simulation results show that the proposed CPCSS can balance the energy consumption and optimize the coverage performance of the sensor network.

A Robust Optimization Based Energy-Aware Virtual Network Function Placement Proposal for Small Cell 5G Networks with Mobile Edge Computing Capabilities

Directory of Open Access Journals (Sweden)

Bego Blanco

2017-01-01

Full Text Available In the context of cloud-enabled 5G radio access networks with network function virtualization capabilities, we focus on the virtual network function placement problem for a multitenant cluster of small cells that provide mobile edge computing services. Under an emerging distributed network architecture and hardware infrastructure, we employ cloud-enabled small cells that integrate microservers for virtualization execution, equipped with additional hardware appliances. We develop an energy-aware placement solution using a robust optimization approach based on service demand uncertainty in order to minimize the power consumption in the system constrained by network service latency requirements and infrastructure terms. Then, we discuss the results of the proposed placement mechanism in 5G scenarios that combine several service flavours and robust protection values. Once the impact of the service flavour and robust protection on the global power consumption of the system is analyzed, numerical results indicate that our proposal succeeds in efficiently placing the virtual network functions that compose the network services in the available hardware infrastructure while fulfilling service constraints.

Energy Aware Clustering Algorithms for Wireless Sensor Networks

Science.gov (United States)

Rakhshan, Noushin; Rafsanjani, Marjan Kuchaki; Liu, Chenglian

2011-09-01

The sensor nodes deployed in wireless sensor networks (WSNs) are extremely power constrained, so maximizing the lifetime of the entire networks is mainly considered in the design. In wireless sensor networks, hierarchical network structures have the advantage of providing scalable and energy efficient solutions. In this paper, we investigate different clustering algorithms for WSNs and also compare these clustering algorithms based on metrics such as clustering distribution, cluster's load balancing, Cluster Head's (CH) selection strategy, CH's role rotation, node mobility, clusters overlapping, intra-cluster communications, reliability, security and location awareness.

Data Network Equipment Energy Use and Savings Potential in Buildings

Energy Technology Data Exchange (ETDEWEB)

Lanzisera, Steven; Nordman, Bruce; Brown, Richard E.

2010-06-09

Network connectivity has become nearly ubiquitous, and the energy use of the equipment required for this connectivity is growing. Network equipment consists of devices that primarily switch and route Internet Protocol (IP) packets from a source to a destination, and this category specifically excludes edge devices like PCs, servers and other sources and sinks of IP traffic. This paper presents the results of a study of network equipment energy use and includes case studies of networks in a campus, a medium commercial building, and a typical home. The total energy use of network equipment is the product of the stock of equipment in use, the power of each device, and their usage patterns. This information was gathered from market research reports, broadband market penetration studies, field metering, and interviews with network administrators and service providers. We estimate that network equipment in the USA used 18 TWh, or about 1percent of building electricity, in 2008 and that consumption is expected to grow at roughly 6percent per year to 23 TWh in 2012; world usage in 2008 was 51 TWh. This study shows that office building network switches and residential equipment are the two largest categories of energy use consuming 40percent and 30percent of the total respectively. We estimate potential energy savings for different scenarios using forecasts of equipment stock and energy use, and savings estimates range from 20percent to 50percent based on full market penetration of efficient technologies.

Energy-aware virtual network embedding in flexi-grid networks.

Science.gov (United States)

Lin, Rongping; Luo, Shan; Wang, Haoran; Wang, Sheng

2017-11-27

Network virtualization technology has been proposed to allow multiple heterogeneous virtual networks (VNs) to coexist on a shared substrate network, which increases the utilization of the substrate network. Efficiently mapping VNs on the substrate network is a major challenge on account of the VN embedding (VNE) problem. Meanwhile, energy efficiency has been widely considered in the network design in terms of operation expenses and the ecological awareness. In this paper, we aim to solve the energy-aware VNE problem in flexi-grid optical networks. We provide an integer linear programming (ILP) formulation to minimize the electricity cost of each arriving VN request. We also propose a polynomial-time heuristic algorithm where virtual links are embedded sequentially to keep a reasonable acceptance ratio and maintain a low electricity cost. Numerical results show that the heuristic algorithm performs closely to the ILP for a small size network, and we also demonstrate its applicability to larger networks.

Intelligent Energy Management Control for Extended Range Electric Vehicles Based on Dynamic Programming and Neural Network

Directory of Open Access Journals (Sweden)

Lihe Xi

2017-11-01

Full Text Available The extended range electric vehicle (EREV can store much clean energy from the electric grid when it arrives at the charging station with lower battery energy. Consuming minimum gasoline during the trip is a common goal for most energy management controllers. To achieve these objectives, an intelligent energy management controller for EREV based on dynamic programming and neural networks (IEMC_NN is proposed. The power demand split ratio between the extender and battery are optimized by DP, and the control objectives are presented as a cost function. The online controller is trained by neural networks. Three trained controllers, constructing the controller library in IEMC_NN, are obtained from training three typical lengths of the driving cycle. To determine an appropriate NN controller for different driving distance purposes, the selection module in IEMC_NN is developed based on the remaining battery energy and the driving distance to the charging station. Three simulation conditions are adopted to validate the performance of IEMC_NN. They are target driving distance information, known and unknown, changing the destination during the trip. Simulation results using these simulation conditions show that the IEMC_NN had better fuel economy than the charging deplete/charging sustain (CD/CS algorithm. More significantly, with known driving distance information, the battery SOC controlled by IEMC_NN can just reach the lower bound as the EREV arrives at the charging station, which was also feasible when the driver changed the destination during the trip.

Energy Efficient Routing Algorithms in Dynamic Optical Core Networks with Dual Energy Sources

DEFF Research Database (Denmark)

Wang, Jiayuan; Fagertun, Anna Manolova; Ruepp, Sarah Renée

2013-01-01

This paper proposes new energy efficient routing algorithms in optical core networks, with the application of solar energy sources and bundled links. A comprehensive solar energy model is described in the proposed network scenarios. Network performance in energy savings, connection blocking...... probability, resource utilization and bundled link usage are evaluated with dynamic network simulations. Results show that algorithms proposed aiming for reducing the dynamic part of the energy consumption of the network may raise the fixed part of the energy consumption meanwhile....

Network switching strategy for energy conservation in heterogeneous networks.

Directory of Open Access Journals (Sweden)

Yujae Song

Full Text Available In heterogeneous networks (HetNets, the large-scale deployment of small base stations (BSs together with traditional macro BSs is an economical and efficient solution that is employed to address the exponential growth in mobile data traffic. In dense HetNets, network switching, i.e., handovers, plays a critical role in connecting a mobile terminal (MT to the best of all accessible networks. In the existing literature, a handover decision is made using various handover metrics such as the signal-to-noise ratio, data rate, and movement speed. However, there are few studies on handovers that focus on energy efficiency in HetNets. In this paper, we propose a handover strategy that helps to minimize energy consumption at BSs in HetNets without compromising the quality of service (QoS of each MT. The proposed handover strategy aims to capture the effect of the stochastic behavior of handover parameters and the expected energy consumption due to handover execution when making a handover decision. To identify the validity of the proposed handover strategy, we formulate a handover problem as a constrained Markov decision process (CMDP, by which the effects of the stochastic behaviors of handover parameters and consequential handover energy consumption can be accurately reflected when making a handover decision. In the CMDP, the aim is to minimize the energy consumption to service an MT over the lifetime of its connection, and the constraint is to guarantee the QoS requirements of the MT given in terms of the transmission delay and call-dropping probability. We find an optimal policy for the CMDP using a combination of the Lagrangian method and value iteration. Simulation results verify the validity of the proposed handover strategy.

ENERGY EFFICIENCY AND ROUTING IN SENSOR NETWORKS

DEFF Research Database (Denmark)

Cetin, Bilge Kartal

-hoc networks, recharging or replacing of the sen- sors battery may be inconvenient, or even impossible in some monitoring environments. Therefore, the key challenge in the design of wireless sen- sor network protocols is how to maximize the network lifetime, which is limited by battery energy in sensor nodes......, while providing the application requirement. In sensor networks, there are two important energy consuming pro- cesses, the rst is transmission-reception phase and the second is listening the radio for any possible event. Therefore, there are two strategies for en- ergy saving. The rst is reducing...... for dierent network parameters is de- veloped by considering a duty-cycling mechanism in the network. Upper bound on network lifetime is sought by considering idle and sleep mode energy consumption as well as energy consumption in transmission and reception for sensor networks. The solution of the developed...

Energy-efficient sensing in wireless sensor networks using compressed sensing.

Science.gov (United States)

Razzaque, Mohammad Abdur; Dobson, Simon

2014-02-12

Sensing of the application environment is the main purpose of a wireless sensor network. Most existing energy management strategies and compression techniques assume that the sensing operation consumes significantly less energy than radio transmission and reception. This assumption does not hold in a number of practical applications. Sensing energy consumption in these applications may be comparable to, or even greater than, that of the radio. In this work, we support this claim by a quantitative analysis of the main operational energy costs of popular sensors, radios and sensor motes. In light of the importance of sensing level energy costs, especially for power hungry sensors, we consider compressed sensing and distributed compressed sensing as potential approaches to provide energy efficient sensing in wireless sensor networks. Numerical experiments investigating the effectiveness of compressed sensing and distributed compressed sensing using real datasets show their potential for efficient utilization of sensing and overall energy costs in wireless sensor networks. It is shown that, for some applications, compressed sensing and distributed compressed sensing can provide greater energy efficiency than transform coding and model-based adaptive sensing in wireless sensor networks.

Study of tensions on network- and grid-based energies during the winter consumption peak

International Nuclear Information System (INIS)

Lemaignan, Benoit; Wilmotte, Jean-Yves; Gault, Nicolas

2014-01-01

This document first proposes an analysis of an historical example of a consumption peak (8 February 2012) and of its impacts. It indicates temperatures and consumptions, discusses the level of supply safety on that day (shares of different available energy sources), outlines some peculiarities of a grid-based (electricity) or network-based (gas) energy system and issues related to supply safety, and describes how energy demand varies during the day and with respect to the season. The second part addresses the issue of thermal sensitivity, i.e. an analysis of the relationship between the energy system and the temperature: usages depend on the outdoor temperature; as far as heating is concerned, this sensitivity depends on thermal characteristics of heated buildings; housing heating with fixed equipment represents less than a half of this electrical thermal-sensitivity; electricity demand peak increased of several GW while the share of thermal sensitivity of housing heating decreased; thermal sensitivity of gas increased during the last four years. The third part addresses heating modes, outlines the challenges in terms of CO_2 emissions, notices the benefits of the present energy mix in terms of hydrocarbon use, trade balance and emissions, outlines that households using electric heating do not pay more and are less represented in households suffering of energy poverty

Inventor networks in renewable energies

DEFF Research Database (Denmark)

Cantner, Uwe; Graf, Holger; Herrmann, Johannes

2016-01-01

on patent data. Our results indicate notable differences between the technologies: the network size for wind power is driven by technology push and systemic instruments, while in photovoltaics, demand pull is decisive for network growth. By and large, the instruments complement each other and form...... energies. Our goal is to gain insights into the influence of this policy mix on the intensity and organization of inventive activities for wind power and photovoltaics in Germany since the 1980s. We examine the effect of different instruments on the size and structure of co-inventor networks based......Technological change and gains in efficiency of renewable power generation technologies are to a large extent driven by governmental support. Various policy instruments that can broadly be categorized as technology push, demand pull or systemic constitute part of the policy mix for renewable...

Energy-efficient orthogonal frequency division multiplexing-based passive optical network based on adaptive sleep-mode control and dynamic bandwidth allocation

Science.gov (United States)

Zhang, Chongfu; Xiao, Nengwu; Chen, Chen; Yuan, Weicheng; Qiu, Kun

2016-02-01

We propose an energy-efficient orthogonal frequency division multiplexing-based passive optical network (OFDM-PON) using adaptive sleep-mode control and dynamic bandwidth allocation. In this scheme, a bidirectional-centralized algorithm named the receiver and transmitter accurate sleep control and dynamic bandwidth allocation (RTASC-DBA), which has an overall bandwidth scheduling policy, is employed to enhance the energy efficiency of the OFDM-PON. The RTASC-DBA algorithm is used in an optical line terminal (OLT) to control the sleep mode of an optical network unit (ONU) sleep and guarantee the quality of service of different services of the OFDM-PON. The obtained results show that, by using the proposed scheme, the average power consumption of the ONU is reduced by ˜40% when the normalized ONU load is less than 80%, compared with the average power consumption without using the proposed scheme.

A Novel Scheme for an Energy Efficient Internet of Things Based on Wireless Sensor Networks

Science.gov (United States)

Rani, Shalli; Talwar, Rajneesh; Malhotra, Jyoteesh; Ahmed, Syed Hassan; Sarkar, Mahasweta; Song, Houbing

2015-01-01

One of the emerging networking standards that gap between the physical world and the cyber one is the Internet of Things. In the Internet of Things, smart objects communicate with each other, data are gathered and certain requests of users are satisfied by different queried data. The development of energy efficient schemes for the IoT is a challenging issue as the IoT becomes more complex due to its large scale the current techniques of wireless sensor networks cannot be applied directly to the IoT. To achieve the green networked IoT, this paper addresses energy efficiency issues by proposing a novel deployment scheme. This scheme, introduces: (1) a hierarchical network design; (2) a model for the energy efficient IoT; (3) a minimum energy consumption transmission algorithm to implement the optimal model. The simulation results show that the new scheme is more energy efficient and flexible than traditional WSN schemes and consequently it can be implemented for efficient communication in the IoT. PMID:26569260

A Novel Scheme for an Energy Efficient Internet of Things Based on Wireless Sensor Networks

Directory of Open Access Journals (Sweden)

Shalli Rani

2015-11-01

Full Text Available One of the emerging networking standards that gap between the physical world and the cyber one is the Internet of Things. In the Internet of Things, smart objects communicate with each other, data are gathered and certain requests of users are satisfied by different queried data. The development of energy efficient schemes for the IoT is a challenging issue as the IoT becomes more complex due to its large scale the current techniques of wireless sensor networks cannot be applied directly to the IoT. To achieve the green networked IoT, this paper addresses energy efficiency issues by proposing a novel deployment scheme. This scheme, introduces: (1 a hierarchical network design; (2 a model for the energy efficient IoT; (3 a minimum energy consumption transmission algorithm to implement the optimal model. The simulation results show that the new scheme is more energy efficient and flexible than traditional WSN schemes and consequently it can be implemented for efficient communication in the IoT.

Energy networks - The data serving the energy transition

International Nuclear Information System (INIS)

2017-03-01

The complementary aspects of the electricity and gas transport networks open new perspectives for the construction of a global energy system that is smarter and oriented to the integration of renewable energies. Moving beyond existing cooperative projects on the security of supply, GRTgaz and RTE intend to draw benefit from the digital revolution to build a response to the regional issues of energy, transport and climate. The Open Data platform provides energy production and consumption data on national and local levels. Use of these multi-energy and multi-operator data will facilitate the development of local authority energy policies and contribute strongly to innovation. It will also contribute to the efficiency of stakeholders in the energy system to engage in more pertinent activities with regions. This first data set is part of the ongoing transparency approach adopted by GRTgaz and RTE to provide better information to citizens, regional authorities and economic actors, for use in developing and assessing energy policies. GRTgaz and RTE already operate web sites (Open Data RTE, Open Data GRTgaz) and applications (GRTgaz+ and eCO2mix), which provide open access to key data concerning energy transport networks. The new energy network data platform will be enriched over time with data from other electricity and gas infrastructure operators. RTE joins the Jupiter 1000 project driven by GRTgaz. The Jupiter 1000 project located in Fos-sur-Mer (Bouches-du-Rhone) is designed to test the technical and economic viability of the Power to Gas concept. This consists in transforming surplus electrical energy from renewable sources into methane by combining hydrogen with CO 2 , for injection and storage in gas networks. RTE has joined the Jupiter 1000 project driven by GRTgaz and featuring seven other industrial partners, with several objectives: manage its needs for flexibility, develop the integration of renewable energy sources and make a valuable contribution to the

Fusion Energy Sciences Network Requirements

Energy Technology Data Exchange (ETDEWEB)

Dart, Eli [ESNet, Berkeley, CA (United States); Tierney, Brian [ESNet, Berkeley, CA (United States)

2012-09-26

The Energy Sciences Network (ESnet) is the primary provider of network connectivity for the U.S. Department of Energy Office of Science, the single largest supporter of basic research in the physical sciences in the United States. In support of the Office of Science programs, ESnet regularly updates and refreshes its understanding of the networking requirements of the instruments, facilities, scientists, and science programs that it serves. This focus has helped ESnet to be a highly successful enabler of scientific discovery for over 25 years. In December 2011, ESnet and the Office of Fusion Energy Sciences (FES), of the DOE Office of Science (SC), organized a workshop to characterize the networking requirements of the programs funded by FES. The requirements identified at the workshop are summarized in the Findings section, and are described in more detail in the body of the report.

Energy-Efficiency in Optical Networks

DEFF Research Database (Denmark)

Saldaña Cercos, Silvia

This thesis expands the state-of-the-art on the complex problem of implementing energy efficient optical networks. The main contribution of this Ph.D. thesis is providing a holistic approach in a multi-layered manner where different tools are used to tackle the urgent need of both estimating...... and optimizing power consumption in different network segments. An energy consumption analysis for a novel digital signal processing for signal slicing to reduce bandwidth requirements for passive optical networks is presented in this thesis. This scheme aims at re-using low bandwidth equipment to cope...... with parallel optics and WDM systems is reported. These results show the trade-off between increased capacity and both power consumption and system performance. In conclusion, an energy-efficient set of tools has been provided covering different aspects of the telecommunication network resulting in a cohesive...

Energy Efficient Network Protocols for Wireless and Mobile Networks

National Research Council Canada - National Science Library

Sivalingam, Krishna

2001-01-01

... (also called power aware) network protocols for wireless and mobile networks. Battery power limitations are a very serious concern, and it is essential to study energy efficient protocol design at different layers of the network protocol stack...

Energy and exergy analysis of low temperature district heating network

International Nuclear Information System (INIS)

Li, Hongwei; Svendsen, Svend

2012-01-01

Low temperature district heating with reduced network supply and return temperature provides better match of the low quality building heating demand and the low quality heating supply from waste heat or renewable energy. In this paper, a hypothetical low temperature district heating network is designed to supply heating for 30 low energy detached residential houses. The network operational supply/return temperature is set as 55 °C/25 °C, which is in line with a pilot project carried out in Denmark. Two types of in-house substations are analyzed to supply the consumer domestic hot water demand. The space heating demand is supplied through floor heating in the bathroom and low temperature radiators in the rest of rooms. The network thermal and hydraulic conditions are simulated under steady state. A district heating network design and simulation code is developed to incorporate the network optimization procedure and the network simultaneous factor. Through the simulation, the overall system energy and exergy efficiencies are calculated and the exergy losses for the major district heating system components are identified. Based on the results, suggestions are given to further reduce the system energy/exergy losses and increase the quality match between the consumer heating demand and the district heating supply. -- Highlights: ► Exergy and energy analysis for low and medium temperature district heating systems. ► Different district heating network dimensioning methods are analyzed. ► Major exergy losses are identified in the district heating network and the in-house substations. ► Advantages to apply low temperature district heating are highlighted through exergy analysis. ► The influence of thermal by-pass on system exergy/energy performance is analyzed.

A Game for Energy-Aware Allocation of Virtualized Network Functions

Directory of Open Access Journals (Sweden)

Roberto Bruschi

2016-01-01

Full Text Available Network Functions Virtualization (NFV is a network architecture concept where network functionality is virtualized and separated into multiple building blocks that may connect or be chained together to implement the required services. The main advantages consist of an increase in network flexibility and scalability. Indeed, each part of the service chain can be allocated and reallocated at runtime depending on demand. In this paper, we present and evaluate an energy-aware Game-Theory-based solution for resource allocation of Virtualized Network Functions (VNFs within NFV environments. We consider each VNF as a player of the problem that competes for the physical network node capacity pool, seeking the minimization of individual cost functions. The physical network nodes dynamically adjust their processing capacity according to the incoming workload, by means of an Adaptive Rate (AR strategy that aims at minimizing the product of energy consumption and processing delay. On the basis of the result of the nodes’ AR strategy, the VNFs’ resource sharing costs assume a polynomial form in the workflows, which admits a unique Nash Equilibrium (NE. We examine the effect of different (unconstrained and constrained forms of the nodes’ optimization problem on the equilibrium and compare the power consumption and delay achieved with energy-aware and non-energy-aware strategy profiles.

Energy modelling in sensor networks

Science.gov (United States)

Schmidt, D.; Krämer, M.; Kuhn, T.; Wehn, N.

2007-06-01

Wireless sensor networks are one of the key enabling technologies for the vision of ambient intelligence. Energy resources for sensor nodes are very scarce. A key challenge is the design of energy efficient communication protocols. Models of the energy consumption are needed to accurately simulate the efficiency of a protocol or application design, and can also be used for automatic energy optimizations in a model driven design process. We propose a novel methodology to create models for sensor nodes based on few simple measurements. In a case study the methodology was used to create models for MICAz nodes. The models were integrated in a simulation environment as well as in a SDL runtime framework of a model driven design process. Measurements on a test application that was created automatically from an SDL specification showed an 80% reduction in energy consumption compared to an implementation without power saving strategies.

Problems of organization and development of the Latvian energy efficiency network

International Nuclear Information System (INIS)

Petrov, B.; Puikevica-Puikevska, I.

1999-01-01

The idea to create an Energy Efficiency Network (Network) was put forward in Canada. In 1989 similar activities started in Norway. Taking account the difficult economical situation in the Latvia industry, such a Network would help to develop our enterprises under conditions of competition. In the future, this Network is to ensure a stabile operation of the international level. Therefore Network's purposes are: to promote decision-making process with due account for the energy efficiency measures and environment-friendly energy use in industry; to encourage reducing the specific consumption of energy; to promote the information exchange among industrial enterprises as well as with new technology suppliers, and service and consulting enterprises. The task of Network is to process information on the activities of enterprises, to perform computations and to show the condition of every enterprise in the same branch of industry, by means of diagrams and tables, as well as to reveal weak points of the enterprise. The benefits of the Network participants: Network information data base allows the participants to compare their energy efficiency data with those of other enterprises in the same branch of industry; opportunity to receive information on the newest achievements in the energy efficiency measures; opportunity to familiarise themselves with the necessary project documentation, reports, ets. Network's activities are organised due consideration for particular needs of an enterprise reported directly by the participants of the enterprise. (author)

A Novel Energy Efficient Topology Control Scheme Based on a Coverage-Preserving and Sleep Scheduling Model for Sensor Networks

Science.gov (United States)

Shi, Binbin; Wei, Wei; Wang, Yihuai; Shu, Wanneng

2016-01-01

In high-density sensor networks, scheduling some sensor nodes to be in the sleep mode while other sensor nodes remain active for monitoring or forwarding packets is an effective control scheme to conserve energy. In this paper, a Coverage-Preserving Control Scheduling Scheme (CPCSS) based on a cloud model and redundancy degree in sensor networks is proposed. Firstly, the normal cloud model is adopted for calculating the similarity degree between the sensor nodes in terms of their historical data, and then all nodes in each grid of the target area can be classified into several categories. Secondly, the redundancy degree of a node is calculated according to its sensing area being covered by the neighboring sensors. Finally, a centralized approximation algorithm based on the partition of the target area is designed to obtain the approximate minimum set of nodes, which can retain the sufficient coverage of the target region and ensure the connectivity of the network at the same time. The simulation results show that the proposed CPCSS can balance the energy consumption and optimize the coverage performance of the sensor network. PMID:27754405

A Novel Energy Efficient Topology Control Scheme Based on a Coverage-Preserving and Sleep Scheduling Model for Sensor Networks

Directory of Open Access Journals (Sweden)

Binbin Shi

2016-10-01

Full Text Available In high-density sensor networks, scheduling some sensor nodes to be in the sleep mode while other sensor nodes remain active for monitoring or forwarding packets is an effective control scheme to conserve energy. In this paper, a Coverage-Preserving Control Scheduling Scheme (CPCSS based on a cloud model and redundancy degree in sensor networks is proposed. Firstly, the normal cloud model is adopted for calculating the similarity degree between the sensor nodes in terms of their historical data, and then all nodes in each grid of the target area can be classified into several categories. Secondly, the redundancy degree of a node is calculated according to its sensing area being covered by the neighboring sensors. Finally, a centralized approximation algorithm based on the partition of the target area is designed to obtain the approximate minimum set of nodes, which can retain the sufficient coverage of the target region and ensure the connectivity of the network at the same time. The simulation results show that the proposed CPCSS can balance the energy consumption and optimize the coverage performance of the sensor network.

Integrated topology optimisation of multi-energy networks

NARCIS (Netherlands)

Mazairac, L.A.J.; Salenbien, R.; Vanhoudt, D.; Desmedt, J.; Vries, de B.

2015-01-01

Multi-carrier hybrid energy distribution net- works provide flexibility in case of network malfunctions, energy shortages and price fluctuations through energy conversion and storage. Therefore hybrid networks can cope with large-scale integration of distributed and intermittent renewable energy

Wireless network interface energy consumption implications of popular streaming formats

Science.gov (United States)

Chandra, Surendar

2001-12-01

With the proliferation of mobile streaming multimedia, available battery capacity constrains the end-user experience. Since streaming applications tend to be long running, wireless network interface card's (WNIC) energy consumption is particularly an acute problem. In this work, we explore the WNIC energy consumption implications of popular multimedia streaming formats from Microsoft (Windows media), Real (Real media) and Apple (Quick Time). We investigate the energy consumption under varying stream bandwidth and network loss rates. We also explore history-based client-side strategies to reduce the energy consumed by transitioning the WNICs to a lower power consuming sleep state. We show that Microsoft media tends to transmit packets at regular intervals; streams optimized for 28.8 Kbps can save over 80% in energy consumption with 2% data loss. A high bandwidth stream (768 Kbps) can still save 57% in energy consumption with less than 0.3% data loss. For high bandwidth streams, Microsoft media exploits network-level packet fragmentation, which can lead to excessive packet loss (and wasted energy) in a lossy network. Real stream packets tend to be sent closer to each other, especially at higher bandwidths. Quicktime packets sometimes arrive in quick succession; most likely an application level fragmentation mechanism. Such packets are harder to predict at the network level without understanding the packet semantics.

Decentralized Hypothesis Testing in Energy Harvesting Wireless Sensor Networks

Science.gov (United States)

Tarighati, Alla; Gross, James; Jalden, Joakim

2017-09-01

We consider the problem of decentralized hypothesis testing in a network of energy harvesting sensors, where sensors make noisy observations of a phenomenon and send quantized information about the phenomenon towards a fusion center. The fusion center makes a decision about the present hypothesis using the aggregate received data during a time interval. We explicitly consider a scenario under which the messages are sent through parallel access channels towards the fusion center. To avoid limited lifetime issues, we assume each sensor is capable of harvesting all the energy it needs for the communication from the environment. Each sensor has an energy buffer (battery) to save its harvested energy for use in other time intervals. Our key contribution is to formulate the problem of decentralized detection in a sensor network with energy harvesting devices. Our analysis is based on a queuing-theoretic model for the battery and we propose a sensor decision design method by considering long term energy management at the sensors. We show how the performance of the system changes for different battery capacities. We then numerically show how our findings can be used in the design of sensor networks with energy harvesting sensors.

Energy-Aware Routing Optimization in Dynamic GMPLS Controlled Optical Networks

DEFF Research Database (Denmark)

Wang, Jiayuan; Ricciardi, Sergio; Fagertun, Anna Manolova

2012-01-01

In this paper, routing optimizations based on energy sources are proposed in dynamic GMPLS controlled optical networks. The influences of re-routing and load balancing factors on the algorithm are evaluated, with a focus on different re-routing thresholds. Results from dynamic network simulations...

Localization of Energy Harvesting Empowered Underwater Optical Wireless Sensor Networks

KAUST Repository

Saeed, Nasir; Celik, Abdulkadir; Al-Naffouri, Tareq Y.; Alouini, Mohamed-Slim

2017-01-01

with insufficient battery, harvest the energy and starts communicating once it has sufficient energy storage. Network localization is carried out by measuring the RSSs of active nodes, which are modeled based on the underwater optical communication channel

Energy, Entropy and Exergy in Communication Networks

Directory of Open Access Journals (Sweden)

Slavisa Aleksic

2013-10-01

Full Text Available The information and communication technology (ICT sector is continuously growing, mainly due to the fast penetration of ICT into many areas of business and society. Growth is particularly high in the area of technologies and applications for communication networks, which can be used, among others, to optimize systems and processes. The ubiquitous application of ICT opens new perspectives and emphasizes the importance of understanding the complex interactions between ICT and other sectors. Complex and interacting heterogeneous systems can only properly be addressed by a holistic framework. Thermodynamic theory, and, in particular, the second law of thermodynamics, is a universally applicable tool to analyze flows of energy. Communication systems and their processes can be seen, similar to many other natural processes and systems, as dissipative transformations that level differences in energy density between participating subsystems and their surroundings. This paper shows how to apply thermodynamics to analyze energy flows through communication networks. Application of the second law of thermodynamics in the context of the Carnot heat engine is emphasized. The use of exergy-based lifecycle analysis to assess the sustainability of ICT systems is shown on an example of a radio access network.

Towards understanding the robustness of energy distribution networks based on macroscopic and microscopic evaluations

International Nuclear Information System (INIS)

Liu Jiming; Shi Benyun

2012-01-01

Supply disruptions on one node of a distribution network may spread to other nodes, and potentially bring various social and economic impacts. To understand the performance of a distribution network in the face of supply disruptions, it would be helpful for policy makers to quantitatively evaluate the robustness of the network, i.e., its ability of maintaining a supply–demand balance on individual nodes. In this paper, we first define a notion of network entropy to macroscopically characterize distribution robustness with respect to the dynamics of energy flows. Further, we look into how microscopic evaluation based on a failure spreading model helps us determine the extent to which disruptions on one node may affect the others. We take the natural gas distribution network in the USA as an example to demonstrate the introduced concepts and methods. Specifically, the proposed macroscopic and microscopic evaluations provide us a means of precisely identifying transmission bottlenecks in the U.S. interstate pipeline network, ranking the effects of supply disruptions on individual nodes, and planning geographically advantageous locations for natural gas storage. These findings can offer policy makers, planners, and network managers with further insights into emergency planning as well as possible design improvement. - Highlights: ► This paper evaluates distribution robustness by defining a notion of network entropy. ► The disruption impacts on individual node are evaluated by a failure spreading model. ► The robustness of the U.S. natural gas distribution network is studied. ► Results reveal pipeline bottlenecks, the node rank, and potential storage locations. ► Possible strategies for mitigating the impacts of supply disruptions are discussed.

Mobility based energy efficient and multi-sink algorithms for consumer home networks

OpenAIRE

Wang, Jin; Yin, Yue; Zhang, Jianwei; Lee, Sungyoung; Sherratt, R. Simon

2013-01-01

With the fast development of the Internet, wireless communications and semiconductor devices, home networking has received significant attention. Consumer products can collect and transmit various types of data in the home environment. Typical consumer sensors are often equipped with tiny, irreplaceable batteries and it therefore of the utmost importance to design energy efficient algorithms to prolong the home network lifetime and reduce devices going to landfill. Sink mobility is an importa...

Game-Theory-Based Approach for Energy Routing in a Smart Grid Network

Directory of Open Access Journals (Sweden)

June S. Hong

2016-01-01

Full Text Available Small power plants and buildings with renewable power generation capability have recently been added to traditional central power plants. Through these facilities, prosumers appear to have a concurrent role in both energy production and consumption. Based on bidirectional power transfers by large numbers of prosumers, a smart microgrid has become an important factor in efficiently controlling the microgrids used in power markets and in conducting effective power trades among grids. In this paper, we present an approach utilizing the game theory for effective and efficient energy routing, which is a novel and challenging procedure for a smart microgrid network. First, we propose strategies for choosing the desired transaction price for both electricity surpluses and shortages to maximize profits through energy transactions. An optimization scheme is utilized to search for an energy route with minimum cost using the solving method used in a traditional transportation problem by treating the sale and purchase quantities as transportation supply and demand, respectively. To evaluate the effect of the proposed decision strategies, we simulated our mechanism, and the results proved that our mechanism yields results pursued by each strategy. Our proposed strategies will contribute to spreading a smart microgrid for enhancing the utilization of microgrids.

Energy management in wireless cellular and ad-hoc networks

CERN Document Server

Imran, Muhammad; Qaraqe, Khalid; Alouini, Mohamed-Slim; Vasilakos, Athanasios

2016-01-01

This book investigates energy management approaches for energy efficient or energy-centric system design and architecture and presents end-to-end energy management in the recent heterogeneous-type wireless network medium. It also considers energy management in wireless sensor and mesh networks by exploiting energy efficient transmission techniques and protocols. and explores energy management in emerging applications, services and engineering to be facilitated with 5G networks such as WBANs, VANETS and Cognitive networks. A special focus of the book is on the examination of the energy management practices in emerging wireless cellular and ad hoc networks. Considering the broad scope of energy management in wireless cellular and ad hoc networks, this book is organized into six sections covering range of Energy efficient systems and architectures; Energy efficient transmission and techniques; Energy efficient applications and services. .

Resume: networking in high energy physics

International Nuclear Information System (INIS)

Hutton, J.S.

1985-11-01

Networking in High Energy Physics covers communications inside the experiment and internationally. Inside the experiment the need for agreed 'codes of practice' is now accepted. Within Europe it is accepted that a common infrastructure based on the use of the ISO OSI protocols should be used. In the USA a community initiative has been proposed. The background to these approaches is discussed. (author)

Neural Network based Control of SG based Standalone Generating System with Energy Storage for Power Quality Enhancement

Science.gov (United States)

Nayar, Priya; Singh, Bhim; Mishra, Sukumar

2017-08-01

An artificial intelligence based control algorithm is used in solving power quality problems of a diesel engine driven synchronous generator with automatic voltage regulator and governor based standalone system. A voltage source converter integrated with a battery energy storage system is employed to mitigate the power quality problems. An adaptive neural network based signed regressor control algorithm is used for the estimation of the fundamental component of load currents for control of a standalone system with load leveling as an integral feature. The developed model of the system performs accurately under varying load conditions and provides good dynamic response to the step changes in loads. The real time performance is achieved using MATLAB along with simulink/simpower system toolboxes and results adhere to an IEEE-519 standard for power quality enhancement.

Coupled Triboelectric Nanogenerator Networks for Efficient Water Wave Energy Harvesting.

Science.gov (United States)

Xu, Liang; Jiang, Tao; Lin, Pei; Shao, Jia Jia; He, Chuan; Zhong, Wei; Chen, Xiang Yu; Wang, Zhong Lin

2018-02-27

Water wave energy is a promising clean energy source, which is abundant but hard to scavenge economically. Triboelectric nanogenerator (TENG) networks provide an effective approach toward massive harvesting of water wave energy in oceans. In this work, a coupling design in TENG networks for such purposes is reported. The charge output of the rationally linked units is over 10 times of that without linkage. TENG networks of three different connecting methods are fabricated and show better performance for the ones with flexible connections. The network is based on an optimized ball-shell structured TENG unit with high responsivity to small agitations. The dynamic behavior of single and multiple TENG units is also investigated comprehensively to fully understand their performance in water. The study shows that a rational design on the linkage among the units could be an effective strategy for TENG clusters to operate collaboratively for reaching a higher performance.

Deployment strategy for battery energy storage system in distribution network based on voltage violation regulation

Science.gov (United States)

Wu, H.; Zhou, L.; Xu, T.; Fang, W. L.; He, W. G.; Liu, H. M.

2017-11-01

In order to improve the situation of voltage violation caused by the grid-connection of photovoltaic (PV) system in a distribution network, a bi-level programming model is proposed for battery energy storage system (BESS) deployment. The objective function of inner level programming is to minimize voltage violation, with the power of PV and BESS as the variables. The objective function of outer level programming is to minimize the comprehensive function originated from inner layer programming and all the BESS operating parameters, with the capacity and rated power of BESS as the variables. The differential evolution (DE) algorithm is applied to solve the model. Based on distribution network operation scenarios with photovoltaic generation under multiple alternative output modes, the simulation results of IEEE 33-bus system prove that the deployment strategy of BESS proposed in this paper is well adapted to voltage violation regulation invariable distribution network operation scenarios. It contributes to regulating voltage violation in distribution network, as well as to improve the utilization of PV systems.

Greening radio access networks using distributed base station architectures

DEFF Research Database (Denmark)

Kardaras, Georgios; Soler, José; Dittmann, Lars

2010-01-01

Several actions for developing environmentally friendly technologies have been taken in most industrial fields. Significant resources have also been devoted in mobile communications industry. Moving towards eco-friendly alternatives is primarily a social responsibility for network operators....... However besides this, increasing energy efficiency represents a key factor for reducing operating expenses and deploying cost effective mobile networks. This paper presents how distributed base station architectures can contribute in greening radio access networks. More specifically, the advantages...... energy saving. Different subsystems have to be coordinated real-time and intelligent network nodes supporting complicated functionalities are necessary. Distributed base station architectures are ideal for this purpose mainly because of their high degree of configurability and self...

DCE: A Distributed Energy-Efficient Clustering Protocol for Wireless Sensor Network Based on Double-Phase Cluster-Head Election.

Science.gov (United States)

Han, Ruisong; Yang, Wei; Wang, Yipeng; You, Kaiming

2017-05-01

Clustering is an effective technique used to reduce energy consumption and extend the lifetime of wireless sensor network (WSN). The characteristic of energy heterogeneity of WSNs should be considered when designing clustering protocols. We propose and evaluate a novel distributed energy-efficient clustering protocol called DCE for heterogeneous wireless sensor networks, based on a Double-phase Cluster-head Election scheme. In DCE, the procedure of cluster head election is divided into two phases. In the first phase, tentative cluster heads are elected with the probabilities which are decided by the relative levels of initial and residual energy. Then, in the second phase, the tentative cluster heads are replaced by their cluster members to form the final set of cluster heads if any member in their cluster has more residual energy. Employing two phases for cluster-head election ensures that the nodes with more energy have a higher chance to be cluster heads. Energy consumption is well-distributed in the proposed protocol, and the simulation results show that DCE achieves longer stability periods than other typical clustering protocols in heterogeneous scenarios.

Peak loads and network investments in sustainable energy transitions

Energy Technology Data Exchange (ETDEWEB)

Blokhuis, Erik, E-mail: e.g.j.blokhuis@tue.nl [Eindhoven University of Technology, Department of Architecture, Building and Planning, Vertigo 8.11, P.O. Box 513, 5600MB Eindhoven (Netherlands); Brouwers, Bart [Eindhoven University of Technology, Department of Architecture, Building and Planning, Vertigo 8.11, P.O. Box 513, 5600MB Eindhoven (Netherlands); Putten, Eric van der [Endinet, Gas and Electricity Network Operations, P.O. Box 2005, 5600CA Eindhoven (Netherlands); Schaefer, Wim [Eindhoven University of Technology, Department of Architecture, Building and Planning, Vertigo 8.11, P.O. Box 513, 5600MB Eindhoven (Netherlands)

2011-10-15

Current energy distribution networks are often not equipped for facilitating expected sustainable transitions. Major concerns for future electricity networks are the possibility of peak load increases and the expected growth of decentralized energy generation. In this article, we focus on peak load increases; the effects of possible future developments on peak loads are studied, together with the consequences for the network. The city of Eindhoven (the Netherlands) is used as reference city, for which a scenario is developed in which the assumed future developments adversely influence the maximum peak loads on the network. In this scenario, the total electricity peak load in Eindhoven is expected to increase from 198 MVA in 2009 to 591-633 MVA in 2040. The necessary investments for facilitating the expected increased peak loads are estimated at 305-375 million Euros. Based upon these projections, it is advocated that - contrary to current Dutch policy - choices regarding sustainable transitions should be made from the viewpoint of integral energy systems, evaluating economic implications of changes to generation, grid development, and consumption. Recently applied and finished policies on energy demand reduction showed to be effective; however, additional and connecting policies on energy generation and distribution should be considered on short term. - Highlights: > Sustainable energy transitions can result in major electricity peak load increases. > Introduction of heat pumps and electrical vehicles requires network expansion. > Under worst case assumptions, peak loads in Eindhoven increase with 200% until 2040. > The necessary investment for facilitating this 2040 peak demand is Euro 305-375 million. > Future policy choices should be made from the viewpoint of the integral energy system.

Peak loads and network investments in sustainable energy transitions

International Nuclear Information System (INIS)

Blokhuis, Erik; Brouwers, Bart; Putten, Eric van der; Schaefer, Wim

2011-01-01

Current energy distribution networks are often not equipped for facilitating expected sustainable transitions. Major concerns for future electricity networks are the possibility of peak load increases and the expected growth of decentralized energy generation. In this article, we focus on peak load increases; the effects of possible future developments on peak loads are studied, together with the consequences for the network. The city of Eindhoven (the Netherlands) is used as reference city, for which a scenario is developed in which the assumed future developments adversely influence the maximum peak loads on the network. In this scenario, the total electricity peak load in Eindhoven is expected to increase from 198 MVA in 2009 to 591-633 MVA in 2040. The necessary investments for facilitating the expected increased peak loads are estimated at 305-375 million Euros. Based upon these projections, it is advocated that - contrary to current Dutch policy - choices regarding sustainable transitions should be made from the viewpoint of integral energy systems, evaluating economic implications of changes to generation, grid development, and consumption. Recently applied and finished policies on energy demand reduction showed to be effective; however, additional and connecting policies on energy generation and distribution should be considered on short term. - Highlights: → Sustainable energy transitions can result in major electricity peak load increases. → Introduction of heat pumps and electrical vehicles requires network expansion. → Under worst case assumptions, peak loads in Eindhoven increase with 200% until 2040. → The necessary investment for facilitating this 2040 peak demand is Euro 305-375 million. → Future policy choices should be made from the viewpoint of the integral energy system.

Energy recovery from waste incineration: Assessing the importance of district heating networks

International Nuclear Information System (INIS)

Fruergaard, T.; Christensen, T.H.; Astrup, T.

2010-01-01

Municipal solid waste incineration contributes with 20% of the heat supplied to the more than 400 district heating networks in Denmark. In evaluation of the environmental consequences of this heat production, the typical approach has been to assume that other (fossil) fuels could be saved on a 1:1 basis (e.g. 1 GJ of waste heat delivered substitutes for 1 GJ of coal-based heat). This paper investigates consequences of waste-based heat substitution in two specific Danish district heating networks and the energy-associated interactions between the plants connected to these networks. Despite almost equal electricity and heat efficiencies at the waste incinerators connected to the two district heating networks, the energy and CO 2 accounts showed significantly different results: waste incineration in one network caused a CO 2 saving of 48 kg CO 2 /GJ energy input while in the other network a load of 43 kg CO 2 /GJ. This was caused mainly by differences in operation mode and fuel types of the other heat producing plants attached to the networks. The paper clearly indicates that simple evaluations of waste-to-energy efficiencies at the incinerator are insufficient for assessing the consequences of heat substitution in district heating network systems. The paper also shows that using national averages for heat substitution will not provide a correct answer: local conditions need to be addressed thoroughly otherwise we may fail to assess correctly the heat recovery from waste incineration.

Impact of stand-by energy losses in electronic devices on smart network performance

OpenAIRE

Mandić-Lukić Jasmina S.; Pantović Vladan S.; Vasiljević Željko S.

2012-01-01

Limited energy resources and environmental concerns due to ever increasing energy consumption, more and more emphasis is being put on energy savings. Smart networks are promoted worldwide as a powerful tool used to improve the energy efficiency through consumption management, as well as to enable the distributed power generation, primarily based on renewable energy sources, to be optimally explored. To make it possible for the smart networks to function, a large number of electronic dev...

Balancing energy consumption with hybrid clustering and routing strategy in wireless sensor networks.

Science.gov (United States)

Xu, Zhezhuang; Chen, Liquan; Liu, Ting; Cao, Lianyang; Chen, Cailian

2015-10-20

Multi-hop data collection in wireless sensor networks (WSNs) is a challenge issue due to the limited energy resource and transmission range of wireless sensors. The hybrid clustering and routing (HCR) strategy has provided an effective solution, which can generate a connected and efficient cluster-based topology for multi-hop data collection in WSNs. However, it suffers from imbalanced energy consumption, which results in the poor performance of the network lifetime. In this paper, we evaluate the energy consumption of HCR and discover an important result: the imbalanced energy consumption generally appears in gradient k = 1, i.e., the nodes that can communicate with the sink directly. Based on this observation, we propose a new protocol called HCR-1, which includes the adaptive relay selection and tunable cost functions to balance the energy consumption. The guideline of setting the parameters in HCR-1 is provided based on simulations. The analytical and numerical results prove that, with minor modification of the topology in Sensors 2015, 15 26584 gradient k = 1, the HCR-1 protocol effectively balances the energy consumption and prolongs the network lifetime.

Renewable energy export network

International Nuclear Information System (INIS)

Anon

2000-01-01

A Renewable Energy Exporters Network (REEN) has recently been established, following a meeting of renewable energy exporters and government agencies on 30 October 2000. REEN will assist the Australian renewable energy industry to take advantage of the opportunities offered by the burgeoning global market for renewable energy goods and services. Recent estimates of the significant potential global growth is renewable energy demand have reinforced the industry and Government's view that, in the medium to long-term, growth in the Australian renewable energy industry will largely depend on capturing export market share. Expanding the export market was identified as a crucial component in the Renewable Energy Action Agenda, developed jointly by industry and Government and released in June 2000. It was estimated that, for the industry to achieve its vision of sales of $4 billion per year by 2010, exports would need to comprise approximately 50% of the forecast growth in sales. As such, the need for a specific export strategy for the Australian renewable energy industry was recognised in the Action Agenda, and the establishment of the REEN is one of the first initiatives undertaken as part of the Renewable Energy Export Strategy. The REEN comprises approximately 50 export-ready renewable energy companies, the Department of Industry, Science and Resources, Austrade, and Stage Government agencies such as NSW's Sustainable Energy Development Authority. The Export Network will operate electronically, with face-to-face meetings held as appropriate. The Department of Industry, Science and Resources will facilitate the Export Network and has published a website at www.isr.gov.au/industry/reen. The site includes: a members directory; a discussion forum; information on opportunities to showcase Australian renewable; energy products and services; and Iinks to sites containing information that may be useful to renewable energy exporters. Other actions that are being undertaken as

Optimal satisfaction degree in energy harvesting cognitive radio networks

International Nuclear Information System (INIS)

Li Zan; Liu Bo-Yang; Si Jiang-Bo; Zhou Fu-Hui

2015-01-01

A cognitive radio (CR) network with energy harvesting (EH) is considered to improve both spectrum efficiency and energy efficiency. A hidden Markov model (HMM) is used to characterize the imperfect spectrum sensing process. In order to maximize the whole satisfaction degree (WSD) of the cognitive radio network, a tradeoff between the average throughput of the secondary user (SU) and the interference to the primary user (PU) is analyzed. We formulate the satisfaction degree optimization problem as a mixed integer nonlinear programming (MINLP) problem. The satisfaction degree optimization problem is solved by using differential evolution (DE) algorithm. The proposed optimization problem allows the network to adaptively achieve the optimal solution based on its required quality of service (Qos). Numerical results are given to verify our analysis. (paper)

Energy Efficient Routing in Nomadic Networks

DEFF Research Database (Denmark)

Kristensen, Mads Darø; Bouvin, Niels Olof

2007-01-01

We present an evaluation of a novel energy-efficient routing protocol for mobile ad-hoc networks. We combine two techniques for optimizing energy levels with a well-known routing protocol. We examine the behavior of this combination in a nomadic network setting, where some nodes are stationary...

Energy-saving framework for passive optical networks with ONU sleep/doze mode.

Science.gov (United States)

Van, Dung Pham; Valcarenghi, Luca; Dias, Maluge Pubuduni Imali; Kondepu, Koteswararao; Castoldi, Piero; Wong, Elaine

2015-02-09

This paper proposes an energy-saving passive optical network framework (ESPON) that aims to incorporate optical network unit (ONU) sleep/doze mode into dynamic bandwidth allocation (DBA) algorithms to reduce ONU energy consumption. In the ESPON, the optical line terminal (OLT) schedules both downstream (DS) and upstream (US) transmissions in the same slot in an online and dynamic fashion whereas the ONU enters sleep mode outside the slot. The ONU sleep time is maximized based on both DS and US traffic. Moreover, during the slot, the ONU might enter doze mode when only its transmitter is idle to further improve energy efficiency. The scheduling order of data transmission, control message exchange, sleep period, and doze period defines an energy-efficient scheme under the ESPON. Three schemes are designed and evaluated in an extensive FPGA-based evaluation. Results show that whilst all the schemes significantly save ONU energy for different evaluation scenarios, the scheduling order has great impact on their performance. In addition, the ESPON allows for a scheduling order that saves ONU energy independently of the network reach.

Energy efficient routing protocols for wireless sensor networks: comparison and future directions

Directory of Open Access Journals (Sweden)

Loganathan Murukesan

2017-01-01

Full Text Available Wireless sensor network consists of nodes with limited resources. Hence, it is important to design protocols or algorithms which increases energy efficiency in order to improve the network lifetime. In this paper, techniques used in the network layer (routing of the internet protocol stack to achieve energy efficiency are reviewed. Usually, the routing protocols are classified into four main schemes: (1 Network Structure, (2 Communication Model, (3 Topology Based, and (4 Reliable Routing. In this work, only network structure based routing protocols are reviewed due to the page constraint. Besides, this type of protocols are much popular among the researchers since they are fairly simple to implement and produce good results as presented in this paper. Also, the pros and cons of each protocols are presented. Finally, the paper concludes with possible further research directions.

An Energy-Efficient Sleep Strategy for Target Tracking Sensor Networks

Directory of Open Access Journals (Sweden)

Juan FENG

2014-02-01

Full Text Available Energy efficiency is very important for sensor networks since sensor nodes have limited energy supply from battery. So far, many researches have been focused on this issue, while less emphasis was placed on the optimal sleep time of each node. This paper proposed an adaptive energy conservation strategy for target tracking based on a grid network structure, where each node autonomously determines when and if to sleep. It allows sensor nodes far away from targets to sleep to save energy and guarantee the tracking accuracy. The proposed approach extend network lifetime by adopting an adaptive sleep scheduling scheme that combines the local power management (PM and the adaptive coordinate PM strategies to schedule the activities of sensor nodes. And each node can choose an optimal sleep time so as to make system adaptive and energy-efficient. We show the performance of our approach in terms of energy drop, comparing it to a naive approach, dynamic PM with fixed sleep time and the coordinate PM strategies. From the experimental results, it is readily seen that the efficiency of the proposed approach.

A genetic algorithm solution for the operation of green LTE networks with energy and environment considerations

KAUST Repository

Ghazzai, Hakim

2012-01-01

The Base Station (BS) sleeping strategy has become a well-known technique to achieve energy savings in cellular networks by switching off redundant BSs mainly for lightly loaded networks. Besides, the exploitation of renewable energies, as additional power sources in smart grids, becomes a real challenge to network operators to reduce power costs. In this paper, we propose a method based on genetic algorithms that decreases the energy consumption of a Long-Term Evolution (LTE) cellular network by not only shutting down underutilized BSs but also by optimizing the amounts of energy procured from the smart grid without affecting the desired Quality of Service. © 2012 Springer-Verlag.

Design of atomic energy information network system

International Nuclear Information System (INIS)

Kim, Y. T.; Lee, E. J.; Han, K. W.; Lee, H. C.; Chang, J. H.

2004-01-01

As the 21 st century is expected to induce a Knowledge based society, responding to this kind of change on our own initiative could be achieved by establishing networks among atomic energy agencies with the Atomic Energy Portal Site in a pivotal role. Thus, enabling the knowledge information from each agency to be easily shared and utilized. Furthermore, it can contribute to further researches by providing accumulated knowledge in the atomic energy, such as research output and past achievements, and by avoiding the repetition of researches on the same subjects. It could also provide remote educational data to researchers and industrial experts in atomic energy, as well as atomic energy information for general public consistently, so that we can promote our confidence in atomic energy

Energy-Aware Topology Evolution Model with Link and Node Deletion in Wireless Sensor Networks

Directory of Open Access Journals (Sweden)

Xiaojuan Luo

2012-01-01

Full Text Available Based on the complex network theory, a new topological evolving model is proposed. In the evolution of the topology of sensor networks, the energy-aware mechanism is taken into account, and the phenomenon of change of the link and node in the network is discussed. Theoretical analysis and numerical simulation are conducted to explore the topology characteristics and network performance with different node energy distribution. We find that node energy distribution has the weak effect on the degree distribution P(k that evolves into the scale-free state, nodes with more energy carry more connections, and degree correlation is nontrivial disassortative. Moreover, the results show that, when nodes energy is more heterogeneous, the network is better clustered and enjoys higher performance in terms of the network efficiency and the average path length for transmitting data.

Optimized smart grid energy procurement for LTE networks using evolutionary algorithms

KAUST Repository

Ghazzai, Hakim; Yaacoub, Elias E.; Alouini, Mohamed-Slim; Abu-Dayya, Adnan A.

2014-01-01

Energy efficiency aspects in cellular networks can contribute significantly to reducing worldwide greenhouse gas emissions. The base station (BS) sleeping strategy has become a well-known technique to achieve energy savings by switching off

Development of Energy Efficient Clustering Protocol in Wireless Sensor Network Using Neuro-Fuzzy Approach.

Science.gov (United States)

Julie, E Golden; Selvi, S Tamil

2016-01-01

Wireless sensor networks (WSNs) consist of sensor nodes with limited processing capability and limited nonrechargeable battery power. Energy consumption in WSN is a significant issue in networks for improving network lifetime. It is essential to develop an energy aware clustering protocol in WSN to reduce energy consumption for increasing network lifetime. In this paper, a neuro-fuzzy energy aware clustering scheme (NFEACS) is proposed to form optimum and energy aware clusters. NFEACS consists of two parts: fuzzy subsystem and neural network system that achieved energy efficiency in forming clusters and cluster heads in WSN. NFEACS used neural network that provides effective training set related to energy and received signal strength of all nodes to estimate the expected energy for tentative cluster heads. Sensor nodes with higher energy are trained with center location of base station to select energy aware cluster heads. Fuzzy rule is used in fuzzy logic part that inputs to form clusters. NFEACS is designed for WSN handling mobility of node. The proposed scheme NFEACS is compared with related clustering schemes, cluster-head election mechanism using fuzzy logic, and energy aware fuzzy unequal clustering. The experiment results show that NFEACS performs better than the other related schemes.

A Fair Resource Allocation Algorithm for Data and Energy Integrated Communication Networks

Directory of Open Access Journals (Sweden)

Qin Yu

2016-01-01

Full Text Available With the rapid advancement of wireless network technologies and the rapid increase in the number of mobile devices, mobile users (MUs have an increasing high demand to access the Internet with guaranteed quality-of-service (QoS. Data and energy integrated communication networks (DEINs are emerging as a new type of wireless networks that have the potential to simultaneously transfer wireless energy and information via the same base station (BS. This means that a physical BS is virtualized into two parts: one is transferring energy and the other is transferring information. The former is called virtual energy base station (eBS and the latter is named as data base station (dBS. One important issue in such setting is dynamic resource allocation. Here the resource concerned includes both power and time. In this paper, we propose a fair data-and-energy resource allocation algorithm for DEINs by jointly designing the downlink energy beamforming and a power-and-time allocation scheme, with the consideration of finite capacity batteries at MUs and power sensitivity of radio frequency (RF to direct current (DC conversion circuits. Simulation results demonstrate that our proposed algorithm outperforms the existing algorithms in terms of fairness, beamforming design, sensitivity, and average throughput.

Exploring the challenges of energy and resources network governance

International Nuclear Information System (INIS)

Poocharoen, Ora-orn; Sovacool, Benjamin K.

2012-01-01

While a growing amount of literature has recently emerged describing network governance, less attention has been paid to evaluating the actual performance of networks. Our paper looks at the challenges facing network governance for natural resources (primarily logging and forestry) and energy (primarily renewable energy and energy efficiency) in Asia. The paper investigates what network governance is, and what types of challenges networks have to tackle. It then develops a qualitative analytical framework to evaluate the effectiveness of networks consisting of five criteria: (1) clarity of roles and objectives among members, (2) having strong, independent, continual sources of funding, (3) institutional formality (having a permanent secretariat, budget, full time staff, etc.), (4) efficacy (ability to accomplish its mission and goals at the least possible cost); and (5) level of interdependency among members. Finally, we apply this framework to four case studies: the Association of Southeast Asian Nations (ASEAN) Centre for Energy, Renewable Energy and Energy Efficiency Partnership (REEEP), ASEAN Regional Knowledge Network on Forests and Climate Change (FCC), and ASEAN Regional Knowledge Network on Forest Law Enforcement and Governance (FLEG). These cases illustrate effective (or ineffective) environmental and energy networks and the factors that are associated with network governance. - Highlights: ► This article evaluates four cases of energy and resources network governance. ► We assess these cases according to five criteria. ► We illustrate the effectiveness (and ineffectiveness) of these networks.

Dynamic sink assignment for efficient energy consumption in wireless sensor networks

KAUST Repository

Oikonomou, Konstantinos N.

2012-04-01

Efficient energy consumption is a challenging problem in wireless sensor networks (WSNs) and closely related to extending network lifetime. The usual way of tackling this issue for topologies with fixed link weight and fixed sink location, has been shown to be severely affected by the energy hole problem. In this paper, the energy consumption problem is initially studied for WSNs with fixed sink assignment and it is analytically shown that energy consumption is minimized when the sink is assigned to the node that is the solution of a suitably formulated 1-median problem. This motivates the introduction of a dynamic environment where link weights change based on the energy level and the aggregate traffic load of the adjacent nodes. Then, the sink is adaptively allowed to move among neighbor nodes, according to a scalable sink migration strategy. Simulation results support the analytical claims demonstrating energy consumption reduction and an additional network lifetime increment when migration is employed in the dynamic environment. © 2012 IEEE.

Energy Efficient Evolution of Mobile Broadband Networks

DEFF Research Database (Denmark)

Micallef, Gilbert

to public commitments for reducing their energy and carbon footprint. In 2008 Vodafone stated that by the year 2020, efforts for reducing emissions are expected to halve emissions registered in the year 2006/7. In addition to presenting a more environmentally conscious brand, this is also hoped to reduce...... for mobile network operators to upgrade existing infrastructure different options are available. Irrespective of the selected option, capacity upgrades are bound to increase the power consumption of the network. Carried through case studies, a first analysis compares a number of network evolution strategies......, determining which provides the necessary performance while limiting the increase in power consumption. Overall, it is noted that a hybrid solution involving the upgrade of existing macro base station sites together with the deployment of outdoor or indoor small cells (heterogeneous network) provide the best...

On Applicability of Network Coding Technique for 6LoWPAN-based Sensor Networks.

Science.gov (United States)

Amanowicz, Marek; Krygier, Jaroslaw

2018-05-26

In this paper, the applicability of the network coding technique in 6LoWPAN-based sensor multihop networks is examined. The 6LoWPAN is one of the standards proposed for the Internet of Things architecture. Thus, we can expect the significant growth of traffic in such networks, which can lead to overload and decrease in the sensor network lifetime. The authors propose the inter-session network coding mechanism that can be implemented in resource-limited sensor motes. The solution reduces the overall traffic in the network, and in consequence, the energy consumption is decreased. Used procedures take into account deep header compressions of the native 6LoWPAN packets and the hop-by-hop changes of the header structure. Applied simplifications reduce signaling traffic that is typically occurring in network coding deployments, keeping the solution usefulness for the wireless sensor networks with limited resources. The authors validate the proposed procedures in terms of end-to-end packet delay, packet loss ratio, traffic in the air, total energy consumption, and network lifetime. The solution has been tested in a real wireless sensor network. The results confirm the efficiency of the proposed technique, mostly in delay-tolerant sensor networks.

Equalized Energy Consumption in Wireless Body Area Networks for a Prolonged Network Lifetime

Directory of Open Access Journals (Sweden)

Maryam El Azhari

2017-01-01

Full Text Available The phenomenal advances in electronics contributed to a widespread use of distributed sensors in wireless communications. A set of biosensors can be deployed or implanted in the human body to form a Wireless Body Area Network (WBAN, where various WBAN PHY layers are utilized. The WBAN allows the measurement of physiological data, which is forwarded by the gateway to the base station for analysis purposes. The main issue in conceiving a WBAN communication mechanism is to manage the residual energy of sensors. The mobile agent system has been widely applied for surveillance applications in Wireless Sensor Networks (WSNs. It consists in dispatching one or more mobile agents simultaneously to collect data, while following a predetermined optimum itinerary. The continuous use of the optimal itinerary leads to a rapid depletion of sensor nodes batteries, which minimizes the network lifetime. This paper presents a new algorithm to equalize the energy consumption among sensor motes. The algorithm exploits all the available paths towards the destination and classifies them with respect to the end-to-end delay and the overall energy consumption. The proposed algorithm performs better compared to the optimal routing path. It increases the network lifetime to the maximum by postponing routing of data via the most-recently used path, and it also maintains data delivery within the delay interval threshold.

A comprehensive probabilistic analysis model of oil pipelines network based on Bayesian network

Science.gov (United States)

Zhang, C.; Qin, T. X.; Jiang, B.; Huang, C.

2018-02-01

Oil pipelines network is one of the most important facilities of energy transportation. But oil pipelines network accident may result in serious disasters. Some analysis models for these accidents have been established mainly based on three methods, including event-tree, accident simulation and Bayesian network. Among these methods, Bayesian network is suitable for probabilistic analysis. But not all the important influencing factors are considered and the deployment rule of the factors has not been established. This paper proposed a probabilistic analysis model of oil pipelines network based on Bayesian network. Most of the important influencing factors, including the key environment condition and emergency response are considered in this model. Moreover, the paper also introduces a deployment rule for these factors. The model can be used in probabilistic analysis and sensitive analysis of oil pipelines network accident.

A Novel Energy Efficient Topology Control Scheme Based on a Coverage-Preserving and Sleep Scheduling Model for Sensor Networks

OpenAIRE

Shi, Binbin; Wei, Wei; Wang, Yihuai; Shu, Wanneng

2016-01-01

In high-density sensor networks, scheduling some sensor nodes to be in the sleep mode while other sensor nodes remain active for monitoring or forwarding packets is an effective control scheme to conserve energy. In this paper, a Coverage-Preserving Control Scheduling Scheme (CPCSS) based on a cloud model and redundancy degree in sensor networks is proposed. Firstly, the normal cloud model is adopted for calculating the similarity degree between the sensor nodes in terms of their historical d...

What is the energy policy-planning network and who dominates it?: A network and QCA analysis of leading energy firms and organizations

International Nuclear Information System (INIS)

Crawford, Seth

2012-01-01

This study examines the structure of the energy industry and the energy policy-planning network (EPPN). I use cross-sectional director interlocks from 2002 to examine the social networks amongst a sample of the largest energy firms, between these firms and the EPPN, and to calculate relative network centrality measures for the firms. I then use qualitative comparative analysis (QCA) to isolate specific combinations of energy firm attributes that are associated with network position. I find that the energy industry has several key intra-firm interlocks that link dominant companies to each other and that the industry is well represented on the boards of EPPN organizations. Additionally, several dominant energy firms provide links between ultra-conservative and moderate policy development organizations. Finally, QCA models suggest that firms with many employees, high revenue, and who produce oil are most likely to hold prominent positions in the EPPN—though above average political campaign contributions offer an alternative path into the network. - Highlights: ► Identifies organizations in the Energy Policy-Planning Network (EPPN). ► Examines measures of network association between EPPN organizations and energy firms. ► Isolates key attributes of energy firms who are highly embedded within the EPPN. ► Large, oil producing firms hold key positions in the network. ► EPPN organizations act as a bridge between many firms, linking them indirectly.

Silicon-embedded copper nanostructure network for high energy storage

Science.gov (United States)

Yu, Tianyue

2016-03-15

Provided herein are nanostructure networks having high energy storage, electrochemically active electrode materials including nanostructure networks having high energy storage, as well as electrodes and batteries including the nanostructure networks having high energy storage. According to various implementations, the nanostructure networks have high energy density as well as long cycle life. In some implementations, the nanostructure networks include a conductive network embedded with electrochemically active material. In some implementations, silicon is used as the electrochemically active material. The conductive network may be a metal network such as a copper nanostructure network. Methods of manufacturing the nanostructure networks and electrodes are provided. In some implementations, metal nanostructures can be synthesized in a solution that contains silicon powder to make a composite network structure that contains both. The metal nanostructure growth can nucleate in solution and on silicon nanostructure surfaces.

Silicon-embedded copper nanostructure network for high energy storage

Energy Technology Data Exchange (ETDEWEB)

Yu, Tianyue

2018-01-23

Provided herein are nanostructure networks having high energy storage, electrochemically active electrode materials including nanostructure networks having high energy storage, as well as electrodes and batteries including the nanostructure networks having high energy storage. According to various implementations, the nanostructure networks have high energy density as well as long cycle life. In some implementations, the nanostructure networks include a conductive network embedded with electrochemically active material. In some implementations, silicon is used as the electrochemically active material. The conductive network may be a metal network such as a copper nanostructure network. Methods of manufacturing the nanostructure networks and electrodes are provided. In some implementations, metal nanostructures can be synthesized in a solution that contains silicon powder to make a composite network structure that contains both. The metal nanostructure growth can nucleate in solution and on silicon nanostructure surfaces.

Energy Savings through Site Renewal in an HSPA/LTE Network Evolution Scenario

DEFF Research Database (Denmark)

Micallef, Gilbert; Mogensen, Preben

Mobile network operators are committing themselves to reduce the energy consumption of their networks. However, the expected growth in traffic and the upgrades required to sustain this growth pose a serious question on whether these targets are achievable. Through a case study, this paper looks a...... to just 12%. In some cases, when a less aggressive traffic growth is assumed, the energy savings are enough to balance any increase in energy. In a best case scenario, where all sites are replaced when new equipment is available, energy savings close to 40% are achievable....... at how the energy consumption of a mobile network is likely to develop over a period of nine years, considering the evolution of an existing HSPA layer into a multi-layered (HSPA+LTE) network. Besides, this study also considers four different equipment versions released throughout the years, which...... are introduced in the network based on a replacement strategy. In addition, the two most modern sites are assumed to be configured with remote radio head. In comparison to the reference case which leads to an increase in energy consumption of almost 200%, considering these site upgrades can limit the increase...

Bayes Node Energy Polynomial Distribution to Improve Routing in Wireless Sensor Network

Science.gov (United States)

Palanisamy, Thirumoorthy; Krishnasamy, Karthikeyan N.

2015-01-01

Wireless Sensor Network monitor and control the physical world via large number of small, low-priced sensor nodes. Existing method on Wireless Sensor Network (WSN) presented sensed data communication through continuous data collection resulting in higher delay and energy consumption. To conquer the routing issue and reduce energy drain rate, Bayes Node Energy and Polynomial Distribution (BNEPD) technique is introduced with energy aware routing in the wireless sensor network. The Bayes Node Energy Distribution initially distributes the sensor nodes that detect an object of similar event (i.e., temperature, pressure, flow) into specific regions with the application of Bayes rule. The object detection of similar events is accomplished based on the bayes probabilities and is sent to the sink node resulting in minimizing the energy consumption. Next, the Polynomial Regression Function is applied to the target object of similar events considered for different sensors are combined. They are based on the minimum and maximum value of object events and are transferred to the sink node. Finally, the Poly Distribute algorithm effectively distributes the sensor nodes. The energy efficient routing path for each sensor nodes are created by data aggregation at the sink based on polynomial regression function which reduces the energy drain rate with minimum communication overhead. Experimental performance is evaluated using Dodgers Loop Sensor Data Set from UCI repository. Simulation results show that the proposed distribution algorithm significantly reduce the node energy drain rate and ensure fairness among different users reducing the communication overhead. PMID:26426701

Bayes Node Energy Polynomial Distribution to Improve Routing in Wireless Sensor Network.

Science.gov (United States)

Palanisamy, Thirumoorthy; Krishnasamy, Karthikeyan N

2015-01-01

Wireless Sensor Network monitor and control the physical world via large number of small, low-priced sensor nodes. Existing method on Wireless Sensor Network (WSN) presented sensed data communication through continuous data collection resulting in higher delay and energy consumption. To conquer the routing issue and reduce energy drain rate, Bayes Node Energy and Polynomial Distribution (BNEPD) technique is introduced with energy aware routing in the wireless sensor network. The Bayes Node Energy Distribution initially distributes the sensor nodes that detect an object of similar event (i.e., temperature, pressure, flow) into specific regions with the application of Bayes rule. The object detection of similar events is accomplished based on the bayes probabilities and is sent to the sink node resulting in minimizing the energy consumption. Next, the Polynomial Regression Function is applied to the target object of similar events considered for different sensors are combined. They are based on the minimum and maximum value of object events and are transferred to the sink node. Finally, the Poly Distribute algorithm effectively distributes the sensor nodes. The energy efficient routing path for each sensor nodes are created by data aggregation at the sink based on polynomial regression function which reduces the energy drain rate with minimum communication overhead. Experimental performance is evaluated using Dodgers Loop Sensor Data Set from UCI repository. Simulation results show that the proposed distribution algorithm significantly reduce the node energy drain rate and ensure fairness among different users reducing the communication overhead.

Security of supply and regulation of energy networks

International Nuclear Information System (INIS)

Jamasb, Tooraj; Pollitt, Michael

2008-01-01

In recent years, the security of energy supplies has re-emerged as a central issue in the energy policy arena in the UK and elsewhere. This re-emergence takes place against a backdrop of increased liberalisation of the energy markets, so that security of supply needs to be revisited within this context. Security of supply is multifaceted, but is often discussed in terms of physical availability of energy sources and their commodity price risk. This paper discusses the relationship between security of supply and network regulation - that is, how the energy networks, and appropriate regulation of them, can contribute to security of supply in liberalised energy sectors. Energy networks are predominantly natural monopolies and as a result are generally subject to regulatory oversight. We discuss a range of issues and trends that pose challenges and opportunities to network regulation and which call for new and innovative measures. The paper identifies a number of areas where network regulation can play a significant role in increasing the security of supply of future energy systems. (author)

Energy Efficient Medium Access Control Protocol for Clustered Wireless Sensor Networks with Adaptive Cross-Layer Scheduling.

Science.gov (United States)

Sefuba, Maria; Walingo, Tom; Takawira, Fambirai

2015-09-18

This paper presents an Energy Efficient Medium Access Control (MAC) protocol for clustered wireless sensor networks that aims to improve energy efficiency and delay performance. The proposed protocol employs an adaptive cross-layer intra-cluster scheduling and an inter-cluster relay selection diversity. The scheduling is based on available data packets and remaining energy level of the source node (SN). This helps to minimize idle listening on nodes without data to transmit as well as reducing control packet overhead. The relay selection diversity is carried out between clusters, by the cluster head (CH), and the base station (BS). The diversity helps to improve network reliability and prolong the network lifetime. Relay selection is determined based on the communication distance, the remaining energy and the channel quality indicator (CQI) for the relay cluster head (RCH). An analytical framework for energy consumption and transmission delay for the proposed MAC protocol is presented in this work. The performance of the proposed MAC protocol is evaluated based on transmission delay, energy consumption, and network lifetime. The results obtained indicate that the proposed MAC protocol provides improved performance than traditional cluster based MAC protocols.

Analytical network process based optimum cluster head selection in wireless sensor network.

Science.gov (United States)

Farman, Haleem; Javed, Huma; Jan, Bilal; Ahmad, Jamil; Ali, Shaukat; Khalil, Falak Naz; Khan, Murad

2017-01-01

Wireless Sensor Networks (WSNs) are becoming ubiquitous in everyday life due to their applications in weather forecasting, surveillance, implantable sensors for health monitoring and other plethora of applications. WSN is equipped with hundreds and thousands of small sensor nodes. As the size of a sensor node decreases, critical issues such as limited energy, computation time and limited memory become even more highlighted. In such a case, network lifetime mainly depends on efficient use of available resources. Organizing nearby nodes into clusters make it convenient to efficiently manage each cluster as well as the overall network. In this paper, we extend our previous work of grid-based hybrid network deployment approach, in which merge and split technique has been proposed to construct network topology. Constructing topology through our proposed technique, in this paper we have used analytical network process (ANP) model for cluster head selection in WSN. Five distinct parameters: distance from nodes (DistNode), residual energy level (REL), distance from centroid (DistCent), number of times the node has been selected as cluster head (TCH) and merged node (MN) are considered for CH selection. The problem of CH selection based on these parameters is tackled as a multi criteria decision system, for which ANP method is used for optimum cluster head selection. Main contribution of this work is to check the applicability of ANP model for cluster head selection in WSN. In addition, sensitivity analysis is carried out to check the stability of alternatives (available candidate nodes) and their ranking for different scenarios. The simulation results show that the proposed method outperforms existing energy efficient clustering protocols in terms of optimum CH selection and minimizing CH reselection process that results in extending overall network lifetime. This paper analyzes that ANP method used for CH selection with better understanding of the dependencies of

A Comparison of Energy Consumption Prediction Models Based on Neural Networks of a Bioclimatic Building

Directory of Open Access Journals (Sweden)

Hamid R. Khosravani

2016-01-01

Full Text Available Energy consumption has been increasing steadily due to globalization and industrialization. Studies have shown that buildings are responsible for the biggest proportion of energy consumption; for example in European Union countries, energy consumption in buildings represents around 40% of the total energy consumption. In order to control energy consumption in buildings, different policies have been proposed, from utilizing bioclimatic architectures to the use of predictive models within control approaches. There are mainly three groups of predictive models including engineering, statistical and artificial intelligence models. Nowadays, artificial intelligence models such as neural networks and support vector machines have also been proposed because of their high potential capabilities of performing accurate nonlinear mappings between inputs and outputs in real environments which are not free of noise. The main objective of this paper is to compare a neural network model which was designed utilizing statistical and analytical methods, with a group of neural network models designed benefiting from a multi objective genetic algorithm. Moreover, the neural network models were compared to a naïve autoregressive baseline model. The models are intended to predict electric power demand at the Solar Energy Research Center (Centro de Investigación en Energía SOLar or CIESOL in Spanish bioclimatic building located at the University of Almeria, Spain. Experimental results show that the models obtained from the multi objective genetic algorithm (MOGA perform comparably to the model obtained through a statistical and analytical approach, but they use only 0.8% of data samples and have lower model complexity.

Cell Identification based on Received Signal Strength Fingerprints: Concept and Application towards Energy Saving in Cellular Networks

Directory of Open Access Journals (Sweden)

Elke Roth-Mandutz

2014-09-01

Full Text Available The increasing deployment of small cells aimed at off-loading data traffic from macrocells in heterogeneous networks has resulted in a drastic increase in energy consumption in cellular networks. Energy consumption can be optimized in a selforganized way by adapting the number of active cells in response to the current traffic demand. In this paper we concentrate on the complex problem of how to identify small cells to be reactivated in situations where multiple cells are concurrently inactive. Solely based on the received signal strength, we present cell-specific patterns for the generation of unique cell fingerprints. The cell fingerprints of the deactivated cells are matched with measurements from a high data rate demanding mobile device to identify the most appropriate candidate. Our scheme results in a matching success rate of up to 100% to identify the best cell depending on the number of cells to be activated.

Convolutional networks for fast, energy-efficient neuromorphic computing.

Science.gov (United States)

Esser, Steven K; Merolla, Paul A; Arthur, John V; Cassidy, Andrew S; Appuswamy, Rathinakumar; Andreopoulos, Alexander; Berg, David J; McKinstry, Jeffrey L; Melano, Timothy; Barch, Davis R; di Nolfo, Carmelo; Datta, Pallab; Amir, Arnon; Taba, Brian; Flickner, Myron D; Modha, Dharmendra S

2016-10-11

Deep networks are now able to achieve human-level performance on a broad spectrum of recognition tasks. Independently, neuromorphic computing has now demonstrated unprecedented energy-efficiency through a new chip architecture based on spiking neurons, low precision synapses, and a scalable communication network. Here, we demonstrate that neuromorphic computing, despite its novel architectural primitives, can implement deep convolution networks that (i) approach state-of-the-art classification accuracy across eight standard datasets encompassing vision and speech, (ii) perform inference while preserving the hardware's underlying energy-efficiency and high throughput, running on the aforementioned datasets at between 1,200 and 2,600 frames/s and using between 25 and 275 mW (effectively >6,000 frames/s per Watt), and (iii) can be specified and trained using backpropagation with the same ease-of-use as contemporary deep learning. This approach allows the algorithmic power of deep learning to be merged with the efficiency of neuromorphic processors, bringing the promise of embedded, intelligent, brain-inspired computing one step closer.

Price-based optimal control of power flow in electrical energy transmission networks

NARCIS (Netherlands)

Jokic, A.; Lazar, M.; Bosch, van den P.P.J.; Bemporad, A.; Bicchi, A.; Buttazzo, G.

2007-01-01

This article presents a novel control scheme for achieving optimal power balancing and congestion control in electrical energy transmission networks via nodal prices. We develop an explicit controller that guarantees economically optimal steady-state operation while respecting all line flow

Opportunities and Challenges of AC/DC Transmission Network Planning Considering High Proportion Renewable Energy

Directory of Open Access Journals (Sweden)

Arslan Habib

2018-03-01

Full Text Available The time and space distribution characteristics of future high proportion of renewable energy sources will bring unprecedented challenges to the electric power system’s processing and planning, the basic form of electric power system and operating characteristics will have fundamental changes. Based on the research status quo at home and abroad, this paper expounds the four scientific problems of the transmission network planning with high proportion of renewable energy. Respectively, from the network source collaborative planning, transmission network flexible planning. With the distribution network in conjunction with the transmission network planning, transmission planning program comprehensive evaluation and decision-making methods. This paper puts forward the research ideas and framework of transmission network planning considering the high proportion of renewable energy. At the end, the future high proportion of (renewable energy grid-connected transmission network’s opportunities and challenges are presented.

Dynamic energy management employing renewable energy sources in IP over DWDM networks

DEFF Research Database (Denmark)

Chen, Xin; Phillips, Chris; Wang, Jiayuan

2013-01-01

management framework employing renewable energy sources in IP over DWDM core networks. The main concept is to combine infrastructure sleeping and virtual router migration to improve the network energy efficiency. By using the energy source information provided by the smart grid, the nodes that are powered...

A Hierarchical Energy Efficient Reliable Transport Protocol for Wireless Sensor Networks

Directory of Open Access Journals (Sweden)

Prabhudutta Mohanty

2014-12-01

Full Text Available The two important requirements for many Wireless Senor Networks (WSNs are prolonged network lifetime and end-to-end reliability. The sensor nodes consume more energy during data transmission than the data sensing. In WSN, the redundant data increase the energy consumption, latency and reduce reliability during data transmission. Therefore, it is important to support energy efficient reliable data transport in WSNs. In this paper, we present a Hierarchical Energy Efficient Reliable Transport Protocol (HEERTP for the data transmission within the WSN. This protocol maximises the network lifetime by controlling the redundant data transmission with the co-ordination of Base Station (BS. The proposed protocol also achieves end-to-end reliability using a hop-by-hop acknowledgement scheme. We evaluate the performance of the proposed protocol through simulation. The simulation results reveal that our proposed protocol achieves better performance in terms of energy efficiency, latency and reliability than the existing protocols.

Development of Energy Efficient Clustering Protocol in Wireless Sensor Network Using Neuro-Fuzzy Approach

Directory of Open Access Journals (Sweden)

E. Golden Julie

2016-01-01

Full Text Available Wireless sensor networks (WSNs consist of sensor nodes with limited processing capability and limited nonrechargeable battery power. Energy consumption in WSN is a significant issue in networks for improving network lifetime. It is essential to develop an energy aware clustering protocol in WSN to reduce energy consumption for increasing network lifetime. In this paper, a neuro-fuzzy energy aware clustering scheme (NFEACS is proposed to form optimum and energy aware clusters. NFEACS consists of two parts: fuzzy subsystem and neural network system that achieved energy efficiency in forming clusters and cluster heads in WSN. NFEACS used neural network that provides effective training set related to energy and received signal strength of all nodes to estimate the expected energy for tentative cluster heads. Sensor nodes with higher energy are trained with center location of base station to select energy aware cluster heads. Fuzzy rule is used in fuzzy logic part that inputs to form clusters. NFEACS is designed for WSN handling mobility of node. The proposed scheme NFEACS is compared with related clustering schemes, cluster-head election mechanism using fuzzy logic, and energy aware fuzzy unequal clustering. The experiment results show that NFEACS performs better than the other related schemes.

Discovery of intramolecular signal transduction network based on a new protein dynamics model of energy dissipation.

Directory of Open Access Journals (Sweden)

Cheng-Wei Ma

Full Text Available A novel approach to reveal intramolecular signal transduction network is proposed in this work. To this end, a new algorithm of network construction is developed, which is based on a new protein dynamics model of energy dissipation. A key feature of this approach is that direction information is specified after inferring protein residue-residue interaction network involved in the process of signal transduction. This enables fundamental analysis of the regulation hierarchy and identification of regulation hubs of the signaling network. A well-studied allosteric enzyme, E. coli aspartokinase III, is used as a model system to demonstrate the new method. Comparison with experimental results shows that the new approach is able to predict all the sites that have been experimentally proved to desensitize allosteric regulation of the enzyme. In addition, the signal transduction network shows a clear preference for specific structural regions, secondary structural types and residue conservation. Occurrence of super-hubs in the network indicates that allosteric regulation tends to gather residues with high connection ability to collectively facilitate the signaling process. Furthermore, a new parameter of propagation coefficient is defined to determine the propagation capability of residues within a signal transduction network. In conclusion, the new approach is useful for fundamental understanding of the process of intramolecular signal transduction and thus has significant impact on rational design of novel allosteric proteins.

INORE: The International Network on Offshore Renewable Energy

International Nuclear Information System (INIS)

Martini, Michele; De Andrén, Andrés

2015-01-01

The International Network on Offshore Renewable Energy (INORE) is a non-profit organization run by volunteers. INORE was born to support early stage researchers in the offshore renewable energy field. Today, INORE has more than 1200 members from more than 70 different countries. The aim of this organization is to facilitate networking and information exchange between young researchers and professionals. This is achieved by arranging symposia, workshops, networking events and issuing scholarships. Three main knowledge areas are currently within INORE’s dedication: sea wave energy, tidal current energy and offshore wind energy.

Traffic-aware Elastic Optical Networks to leverage Energy Savings

DEFF Research Database (Denmark)

Turus, Ioan; Fagertun, Anna Manolova; Dittmann, Lars

2014-01-01

Because of the static nature of the deployed optical networks, large energy wastage is experienced today in production networks such as Telecom networks . With power-adaptive optical interfaces and suitable grooming procedures, we propose the design of more energy efficient transport networks....... Optical network reconfigurations are performed by GMPLS node controllers according to monitored traffic information. The investigated energy reduction strategies are simulated on two large scale transport networks (DT17 and COST37). The results show that the energy savings obtained by these strategies......-Europea n COST37 network, for both symbol-rate and modulation format adaptations significant savings are obtained . Mixed adaptation (jointly performing symbol-rate and modulation format adaptations) used together with optical grooming allows up to 4 4 % and 4 7 % power savings in DT17 and COST37 networks...

Topology control algorithm for wireless sensor networks based on Link forwarding

Science.gov (United States)

Pucuo, Cairen; Qi, Ai-qin

2018-03-01

The research of topology control could effectively save energy and increase the service life of network based on wireless sensor. In this paper, a arithmetic called LTHC (link transmit hybrid clustering) based on link transmit is proposed. It decreases expenditure of energy by changing the way of cluster-node’s communication. The idea is to establish a link between cluster and SINK node when the cluster is formed, and link-node must be non-cluster. Through the link, cluster sends information to SINK nodes. For the sake of achieving the uniform distribution of energy on the network, prolongate the network survival time, and improve the purpose of communication, the communication will cut down much more expenditure of energy for cluster which away from SINK node. In the two aspects of improving the traffic and network survival time, we find that the LTCH is far superior to the traditional LEACH by experiments.

Telecommunications energy and greenhouse gas emissions management for future network growth

International Nuclear Information System (INIS)

Chan, Chien Aun; Gygax, André F.; Leckie, Christopher; Wong, Elaine; Nirmalathas, Ampalavanapillai; Hinton, Kerry

2016-01-01

Highlights: • Model to evaluate key interdependencies of a fast growing telecommunications network. • Network growth analysis using real data and Monte Carlo simulation. • Importance of both operational and embodied energy efficiency improvements. • Embodied energy expected to dominate in the future under current energy efficiency trends. • Carbon footprint and energy management through optimum network replacement cycle. - Abstract: A key aspect of greener network deployment is how to achieve sustainable growth of a telecommunications network, both in terms of operational and embodied energy. Hence, in this paper we investigate how the overall energy consumption and greenhouse gas emissions of a fast growing telecommunications network can be minimized. Due to the complexities in modeling the embodied energy of networks, this aspect of energy consumption has received limited attention by network operators. Here, we present the first model to evaluate the interdependencies of the four main contributing factors in managing the sustainable growth of a telecommunications network: (i) the network’s operational energy consumption; (ii) the embodied energy of network equipment; (iii) network traffic growth; and (iv) the expected energy efficiency improvements in both the operational and embodied phases. Using Monte Carlo techniques with real network data, our results demonstrate that under the current trends in overall energy efficiency improvements the network embodied energy will account for over 40% of the total network energy in 2025 compared to 20% in 2015. Further, we find that the optimum equipment replacement cycle, which will result in the lowest total network life cycle energy, is directly dependent on the technological progress in energy efficiency improvements of both operational and embodied phases. Our model and analysis highlight the need for a comprehensive approach to better understand the interactions between network growth, technological

Optimal dimensioning of low-energy district heating networks with operational planning

DEFF Research Database (Denmark)

Tol, Hakan; Svendsen, Svend

2012-01-01

in design stage resulted in satisfaction of heat demand of the house in low temperature operation. In this paper the operational planning of the low-energy DH systems was investigated to reduce the dimensions of the distribution network with consideration given both to current high-heat and future low......-heat demand situations. The operational planning was based on boosting (increasing) the supply temperature at peak-demand situations which occur rarely over a year period. Hence optimal pipe dimensions of low-energy DH systems were investigated based on the dynamic response of in-house heating systems...... of operational planning in comparison to DH network dimensioned according to high heat demand situation....

A simulated-based neural network algorithm for forecasting electrical energy consumption in Iran

International Nuclear Information System (INIS)

Azadeh, A.; Ghaderi, S.F.; Sohrabkhani, S.

2008-01-01

This study presents an integrated algorithm for forecasting monthly electrical energy consumption based on artificial neural network (ANN), computer simulation and design of experiments using stochastic procedures. First, an ANN approach is illustrated based on supervised multi-layer perceptron (MLP) network for the electrical consumption forecasting. The chosen model, therefore, can be compared to that of estimated by time series model. Computer simulation is developed to generate random variables for monthly electricity consumption. This is achieved to foresee the effects of probabilistic distribution on monthly electricity consumption. The simulated-based ANN model is then developed. Therefore, there are four treatments to be considered in analysis of variance (ANOVA), which are actual data, time series, ANN and simulated-based ANN. Furthermore, ANOVA is used to test the null hypothesis of the above four alternatives being statistically equal. If the null hypothesis is accepted, then the lowest mean absolute percentage error (MAPE) value is used to select the best model, otherwise the Duncan method (DMRT) of paired comparison is used to select the optimum model which could be time series, ANN or simulated-based ANN. In case of ties the lowest MAPE value is considered as the benchmark. The integrated algorithm has several unique features. First, it is flexible and identifies the best model based on the results of ANOVA and MAPE, whereas previous studies consider the best fitted ANN model based on MAPE or relative error results. Second, the proposed algorithm may identify conventional time series as the best model for future electricity consumption forecasting because of its dynamic structure, whereas previous studies assume that ANN always provide the best solutions and estimation. To show the applicability and superiority of the proposed algorithm, the monthly electricity consumption in Iran from March 1994 to February 2005 (131 months) is used and applied to

Modeling Irrigation Networks for the Quantification of Potential Energy Recovering: A Case Study

Directory of Open Access Journals (Sweden)

Modesto Pérez-Sánchez

2016-06-01

Full Text Available Water irrigation systems are required to provide adequate pressure levels in any sort of network. Quite frequently, this requirement is achieved by using pressure reducing valves (PRVs. Nevertheless, the possibility of using hydraulic machines to recover energy instead of PRVs could reduce the energy footprint of the whole system. In this research, a new methodology is proposed to help water managers quantify the potential energy recovering of an irrigation water network with adequate conditions of topographies distribution. EPANET has been used to create a model based on probabilities of irrigation and flow distribution in real networks. Knowledge of the flows and pressures in the network is necessary to perform an analysis of economic viability. Using the proposed methodology, a case study has been analyzed in a typical Mediterranean region and the potential available energy has been estimated. The study quantifies the theoretical energy recoverable if hydraulic machines were installed in the network. Particularly, the maximum energy potentially recovered in the system has been estimated up to 188.23 MWh/year with a potential saving of non-renewable energy resources (coal and gas of CO2 137.4 t/year.

Modelling the impact of social network on energy savings

International Nuclear Information System (INIS)

Du, Feng; Zhang, Jiangfeng; Li, Hailong; Yan, Jinyue; Galloway, Stuart; Lo, Kwok L.

2016-01-01

Highlights: • Energy saving propagation along a social network is modelled. • This model consists of a time evolving weighted directed network. • Network weights and information decay are applied in savings calculation. - Abstract: It is noted that human behaviour changes can have a significant impact on energy consumption, however, qualitative study on such an impact is still very limited, and it is necessary to develop the corresponding mathematical models to describe how much energy savings can be achieved through human engagement. In this paper a mathematical model of human behavioural dynamic interactions on a social network is derived to calculate energy savings. This model consists of a weighted directed network with time evolving information on each node. Energy savings from the whole network is expressed as mathematical expectation from probability theory. This expected energy savings model includes both direct and indirect energy savings of individuals in the network. The savings model is obtained by network weights and modified by the decay of information. Expected energy savings are calculated for cases where individuals in the social network are treated as a single information source or multiple sources. This model is tested on a social network consisting of 40 people. The results show that the strength of relations between individuals is more important to information diffusion than the number of connections individuals have. The expected energy savings of optimally chosen node can be 25.32% more than randomly chosen nodes at the end of the second month for the case of single information source in the network, and 16.96% more than random nodes for the case of multiple information sources. This illustrates that the model presented in this paper can be used to determine which individuals will have the most influence on the social network, which in turn provides a useful guide to identify targeted customers in energy efficiency technology rollout

IPv6 (Internet Protocol version 6) heterogeneous networking infrastructure for energy efficient building

International Nuclear Information System (INIS)

Ben Saad, Leila; Chauvenet, Cedric; Tourancheau, Bernard

2012-01-01

In the context of increasing developments of home, building and city automation, Power Line Communication (PLC) networking is called for unprecedented usage, especially for energy efficiency improvement. Our view of the future building networking infrastructure places PLC as the central point. We point that while Wireless Sensor Network (WSN) is necessary in the sensor and actuator networking infrastructure, PLC is mandatory for the smart-grid metering and command infrastructure. PLC will also serve the sensor/actuator infrastructure when the energy requirement of the probing system itself cannot be fulfilled by autonomous battery and harvesting based nodes. PLC may also provide the numerous bridges necessary to sustain a long lifetime (years) with the battery based WSN part of the infrastructure. This new role of PLC networking will be possible only if the interoperability between all media and technology is made possible. Thanks to the converging design of Internet Protocol version 6 (IPv6) networking layers, we show that such a full inter-interoperability is already possible even in very tiny constrained networking devices. Moreover, the low power PLC technology used in our experiments will be able to provide this smart grid monitoring without impacting noticeably the overall energy balance of the monitored system.

Bayes Node Energy Polynomial Distribution to Improve Routing in Wireless Sensor Network.

Directory of Open Access Journals (Sweden)

Thirumoorthy Palanisamy

Full Text Available Wireless Sensor Network monitor and control the physical world via large number of small, low-priced sensor nodes. Existing method on Wireless Sensor Network (WSN presented sensed data communication through continuous data collection resulting in higher delay and energy consumption. To conquer the routing issue and reduce energy drain rate, Bayes Node Energy and Polynomial Distribution (BNEPD technique is introduced with energy aware routing in the wireless sensor network. The Bayes Node Energy Distribution initially distributes the sensor nodes that detect an object of similar event (i.e., temperature, pressure, flow into specific regions with the application of Bayes rule. The object detection of similar events is accomplished based on the bayes probabilities and is sent to the sink node resulting in minimizing the energy consumption. Next, the Polynomial Regression Function is applied to the target object of similar events considered for different sensors are combined. They are based on the minimum and maximum value of object events and are transferred to the sink node. Finally, the Poly Distribute algorithm effectively distributes the sensor nodes. The energy efficient routing path for each sensor nodes are created by data aggregation at the sink based on polynomial regression function which reduces the energy drain rate with minimum communication overhead. Experimental performance is evaluated using Dodgers Loop Sensor Data Set from UCI repository. Simulation results show that the proposed distribution algorithm significantly reduce the node energy drain rate and ensure fairness among different users reducing the communication overhead.

Statistical Delay QoS Provisioning for Energy-Efficient Spectrum-Sharing Based Wireless Ad Hoc Sensor Networks

Directory of Open Access Journals (Sweden)

Yichen Wang

2016-01-01

Full Text Available In this paper, we develop the statistical delay quality-of-service (QoS provisioning framework for the energy-efficient spectrum-sharing based wireless ad hoc sensor network (WAHSN, which is characterized by the delay-bound violation probability. Based on the established delay QoS provisioning framework, we formulate the nonconvex optimization problem which aims at maximizing the average energy efficiency of the sensor node in the WAHSN while meeting PU’s statistical delay QoS requirement as well as satisfying sensor node’s average transmission rate, average transmitting power, and peak transmitting power constraints. By employing the theories of fractional programming, convex hull, and probabilistic transmission, we convert the original fractional-structured nonconvex problem to the additively structured parametric convex problem and obtain the optimal power allocation strategy under the given parameter via Lagrangian method. Finally, we derive the optimal average energy efficiency and corresponding optimal power allocation scheme by employing the Dinkelbach method. Simulation results show that our derived optimal power allocation strategy can be dynamically adjusted based on PU’s delay QoS requirement as well as the channel conditions. The impact of PU’s delay QoS requirement on sensor node’s energy efficiency is also illustrated.

Energy management and multi-layer control of networked microgrids

Science.gov (United States)

Zamora, Ramon

Networked microgrids is a group of neighboring microgrids that has ability to interchange power when required in order to increase reliability and resiliency. Networked microgrid can operate in different possible configurations including: islanded microgrid, a grid-connected microgrid without a tie-line converter, a grid-connected microgrid with a tie-line converter, and networked microgrids. These possible configurations and specific characteristics of renewable energy offer challenges in designing control and management algorithms for voltage, frequency and power in all possible operating scenarios. In this work, control algorithm is designed based on large-signal model that enables microgrid to operate in wide range of operating points. A combination between PI controller and feed-forward measured system responses will compensate for the changes in operating points. The control architecture developed in this work has multi-layers and the outer layer is slower than the inner layer in time response. The main responsibility of the designed controls are to regulate voltage magnitude and frequency, as well as output power of the DG(s). These local controls also integrate with a microgrid level energy management system or microgrid central controller (MGCC) for power and energy balance for. the entire microgrid in islanded, grid-connected, or networked microgid mode. The MGCC is responsible to coordinate the lower level controls to have reliable and resilient operation. In case of communication network failure, the decentralized energy management will operate locally and will activate droop control. Simulation results indicate the superiority of designed control algorithms compared to existing ones.

Analysis of recurrent neural networks for short-term energy load forecasting

Science.gov (United States)

Di Persio, Luca; Honchar, Oleksandr

2017-11-01

Short-term forecasts have recently gained an increasing attention because of the rise of competitive electricity markets. In fact, short-terms forecast of possible future loads turn out to be fundamental to build efficient energy management strategies as well as to avoid energy wastage. Such type of challenges are difficult to tackle both from a theoretical and applied point of view. Latter tasks require sophisticated methods to manage multidimensional time series related to stochastic phenomena which are often highly interconnected. In the present work we first review novel approaches to energy load forecasting based on recurrent neural network, focusing our attention on long/short term memory architectures (LSTMs). Such type of artificial neural networks have been widely applied to problems dealing with sequential data such it happens, e.g., in socio-economics settings, for text recognition purposes, concerning video signals, etc., always showing their effectiveness to model complex temporal data. Moreover, we consider different novel variations of basic LSTMs, such as sequence-to-sequence approach and bidirectional LSTMs, aiming at providing effective models for energy load data. Last but not least, we test all the described algorithms on real energy load data showing not only that deep recurrent networks can be successfully applied to energy load forecasting, but also that this approach can be extended to other problems based on time series prediction.

Analysis of Energy Efficiency in Dynamic Optical Networks Employing Solar Energy Sources

DEFF Research Database (Denmark)

Wang, Jiayuan; Fagertun, Anna Manolova; Ruepp, Sarah Renée

2013-01-01

The paper presents energy efficient routing in dynamic optical networks, where solar energy sources are employed for the network nodes. Different parameters are evaluated, including the number of nodes that have access to solar energy sources, the different maximum solar output power, traffic type...... and the locations of solar powered nodes. Results show a maximum 39% savings in energy consumption with different increases in connection blocking probability....

Energy generation for an ad hoc wireless sensor network-based monitoring system using animal head movement

DEFF Research Database (Denmark)

S. Nadimi, Esmaeil; Blanes-Vidal, Victoria; Jørgensen, Rasmus Nyholm

2011-01-01

are not easily accessible. Therefore, exploring novel sources of energy generation rather than operating electronics only on limited power supplies such as batteries is a major challenge. Monitoring free-ranging animal behavior is an application in which the entities (animals) within the MANET are not readily...... that the amount of energy generated by the vertical neck–head movement of sheep during grazing can be converted to useful electrical power adequate to provide power for operation of wireless sensor nodes on a continuous basis within a MANET-based animal behavior monitoring system.......The supply of energy to electronics is an imperative constraining factor to be considered during the design process of mobile ad hoc wireless sensor networks (MANETs). This influence is especially important when the MANET is deployed unattended or the wireless modules within the MANET...

Comprehensive Forecast of Urban Water-Energy Demand Based on a Neural Network Model

Directory of Open Access Journals (Sweden)

Ziyi Yin

2018-03-01

Full Text Available Water-energy nexus has been a popular topic of rese arch in recent years. The relationships between the demand for water resources and energy are intense and closely connected in urban areas. The primary, secondary, and tertiary industry gross domestic product (GDP, the total population, the urban population, annual precipitation, agricultural and industrial water consumption, tap water supply, the total discharge of industrial wastewater, the daily sewage treatment capacity, total and domestic electricity consumption, and the consumption of coal in industrial enterprises above the designed size were chosen as input indicators. A feedforward artificial neural network model (ANN based on a back-propagation algorithm with two hidden layers was constructed to combine urban water resources with energy demand. This model used historical data from 1991 to 2016 from Wuxi City, eastern China. Furthermore, a multiple linear regression model (MLR was introduced for comparison with the ANN. The results show the following: (a The mean relative error values of the forecast and historical urban water-energy demands are 1.58 % and 2.71%, respectively; (b The predicted water-energy demand value for 2020 is 4.843 billion cubic meters and 47.561 million tons of standard coal equivalent; (c The predicted water-energy demand value in the year 2030 is 5.887 billion cubic meters and 60.355 million tons of standard coal equivalent; (d Compared with the MLR, the ANN performed better in fitting training data, which achieved a more satisfactory accuracy and may provide a reference for urban water-energy supply planning decisions.

Impact of stand-by energy losses in electronic devices on smart network performance

Directory of Open Access Journals (Sweden)

Mandić-Lukić Jasmina S.

2012-01-01

Full Text Available Limited energy resources and environmental concerns due to ever increasing energy consumption, more and more emphasis is being put on energy savings. Smart networks are promoted worldwide as a powerful tool used to improve the energy efficiency through consumption management, as well as to enable the distributed power generation, primarily based on renewable energy sources, to be optimally explored. To make it possible for the smart networks to function, a large number of electronic devices is needed to operate or to be in their stand-by mode. The consumption of these devices is added to the consumption of many other electronic devices already in use in households and offices, thus giving rise to the overall power consumption and threatening to counteract the primary function of smart networks. This paper addresses the consumption of particular electronic devices, with an emphasis placed on their thermal losses when in stand-by mode and their total share in the overall power consumption in certain countries. The thermal losses of electronic devices in their stand-by mode are usually neglected, but it seems theoretically possible that a massive increase in their number can impact net performance of the future smart networks considerably so that above an optimum level of energy savings achieved by their penetration, total consumption begins to increase. Based on the current stand-by energy losses from the existing electronic devices, we propose that the future penetration of smart networks be optimized taking also into account losses from their own electronic devices, required to operate in stand-by mode.

SDN-Enabled Communication Network Framework for Energy Internet

Directory of Open Access Journals (Sweden)

Zhaoming Lu

2017-01-01

Full Text Available To support distributed energy generators and improve energy utilization, energy Internet has attracted global research focus. In China, energy Internet has been proposed as an important issue of government and institutes. However, managing a large amount of distributed generators requires smart, low-latency, reliable, and safe networking infrastructure, which cannot be supported by traditional networks in power grids. In order to design and construct smart and flexible energy Internet, we proposed a software defined network framework with both microgrid cluster level and global grid level designed by a hierarchical manner, which will bring flexibility, efficiency, and reliability for power grid networks. Finally, we evaluate and verify the performance of this framework in terms of latency, reliability, and security by both theoretical analysis and real-world experiments.

Research on energy stock market associated network structure based on financial indicators

Science.gov (United States)

Xi, Xian; An, Haizhong

2018-01-01

A financial market is a complex system consisting of many interacting units. In general, due to the various types of information exchange within the industry, there is a relationship between the stocks that can reveal their clear structural characteristics. Complex network methods are powerful tools for studying the internal structure and function of the stock market, which allows us to better understand the stock market. Applying complex network methodology, a stock associated network model based on financial indicators is created. Accordingly, we set threshold value and use modularity to detect the community network, and we analyze the network structure and community cluster characteristics of different threshold situations. The study finds that the threshold value of 0.7 is the abrupt change point of the network. At the same time, as the threshold value increases, the independence of the community strengthens. This study provides a method of researching stock market based on the financial indicators, exploring the structural similarity of financial indicators of stocks. Also, it provides guidance for investment and corporate financial management.

Management of Energy Consumption on Cluster Based Routing Protocol for MANET

Science.gov (United States)

Hosseini-Seno, Seyed-Amin; Wan, Tat-Chee; Budiarto, Rahmat; Yamada, Masashi

The usage of light-weight mobile devices is increasing rapidly, leading to demand for more telecommunication services. Consequently, mobile ad hoc networks and their applications have become feasible with the proliferation of light-weight mobile devices. Many protocols have been developed to handle service discovery and routing in ad hoc networks. However, the majority of them did not consider one critical aspect of this type of network, which is the limited of available energy in each node. Cluster Based Routing Protocol (CBRP) is a robust/scalable routing protocol for Mobile Ad hoc Networks (MANETs) and superior to existing protocols such as Ad hoc On-demand Distance Vector (AODV) in terms of throughput and overhead. Therefore, based on this strength, methods to increase the efficiency of energy usage are incorporated into CBRP in this work. In order to increase the stability (in term of life-time) of the network and to decrease the energy consumption of inter-cluster gateway nodes, an Enhanced Gateway Cluster Based Routing Protocol (EGCBRP) is proposed. Three methods have been introduced by EGCBRP as enhancements to the CBRP: improving the election of cluster Heads (CHs) in CBRP which is based on the maximum available energy level, implementing load balancing for inter-cluster traffic using multiple gateways, and implementing sleep state for gateway nodes to further save the energy. Furthermore, we propose an Energy Efficient Cluster Based Routing Protocol (EECBRP) which extends the EGCBRP sleep state concept into all idle member nodes, excluding the active nodes in all clusters. The experiment results show that the EGCBRP decreases the overall energy consumption of the gateway nodes up to 10% and the EECBRP reduces the energy consumption of the member nodes up to 60%, both of which in turn contribute to stabilizing the network.

A Solution Based on Bluetooth Low Energy for Smart Home Energy Management

Directory of Open Access Journals (Sweden)

Mario Collotta

2015-10-01

Full Text Available The research and the implementation of home automation are getting more popular because the Internet of Things holds promise for making homes smarter through wireless technologies. The installation of systems based on wireless networks can play a key role also in the extension of the smart grid towards smart homes, that can be deemed as one of the most important components of smart grids. This paper proposes a fuzzy-based solution for smart energy management in a home automation wireless network. The approach, by using Bluetooth Low Energy (BLE, introduces a Fuzzy Logic Controller (FLC in order to improve a Home Energy Management (HEM scheme, addressing the power load of standby appliances and their loads in different hours of the day. Since the consumer is involved in the choice of switching on/off of home appliances, the approach introduced in this work proposes a fuzzy-based solution in order to manage the consumer feedbacks. Simulation results show that the proposed solution is efficient in terms of reducing peak load demand, electricity consumption charges with an increase comfort level of consumers. The performance of the proposed BLE-based wireless network scenario are validated in terms of packet delivery ratio, delay, and jitter and are compared to IEEE 802.15.4 technology.

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

International Nuclear Information System (INIS)

Beck, Jessica; Kempener, Ruud; Cohen, Brett; Petrie, Jim

2008-01-01

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

A Robust Optimization Based Energy-Aware Virtual Network Function Placement Proposal for Small Cell 5G Networks with Mobile Edge Computing Capabilities

OpenAIRE

Blanco, Bego; Taboada, Ianire; Fajardo, Jose Oscar; Liberal, Fidel

2017-01-01

In the context of cloud-enabled 5G radio access networks with network function virtualization capabilities, we focus on the virtual network function placement problem for a multitenant cluster of small cells that provide mobile edge computing services. Under an emerging distributed network architecture and hardware infrastructure, we employ cloud-enabled small cells that integrate microservers for virtualization execution, equipped with additional hardware appliances. We develop an energy-awa...

QoS and energy aware cooperative routing protocol for wildfire monitoring wireless sensor networks.

Science.gov (United States)

Maalej, Mohamed; Cherif, Sofiane; Besbes, Hichem

2013-01-01

Wireless sensor networks (WSN) are presented as proper solution for wildfire monitoring. However, this application requires a design of WSN taking into account the network lifetime and the shadowing effect generated by the trees in the forest environment. Cooperative communication is a promising solution for WSN which uses, at each hop, the resources of multiple nodes to transmit its data. Thus, by sharing resources between nodes, the transmission quality is enhanced. In this paper, we use the technique of reinforcement learning by opponent modeling, optimizing a cooperative communication protocol based on RSSI and node energy consumption in a competitive context (RSSI/energy-CC), that is, an energy and quality-of-service aware-based cooperative communication routing protocol. Simulation results show that the proposed algorithm performs well in terms of network lifetime, packet delay, and energy consumption.

Secure Broadcast in Energy-Aware Wireless Sensor Networks

National Research Council Canada - National Science Library

Lazos, Loukas; Poovendran, Radha

2002-01-01

.... The authors show that existing efficient key distribution techniques for wired networks that rely on logical hierarchies are extremely energy inefficient for energy-constrained wireless ad-hoc networks...

Spatial structure, inequality and trading community of renewable energy networks: A comparative study of solar and hydro energy product trades

International Nuclear Information System (INIS)

Fu, Xin; Yang, Yu; Dong, Wen; Wang, Changjian; Liu, Yi

2017-01-01

Renewable energy trade is booming and has formed complicated networks worldwide. However, our knowledge of the spatial structures and evolution of these networks is limited. In this paper, network analyses are used to examine the geographic characteristics of selected renewable energy trades and their evolution based on the United Nations COMTRADE Database from 1988 to 2013. The results show that the networks are expanding to include more and more countries and relationships, and scale of the networks is larger than ever. A tripartite confrontational renewable energy trading system has been forming and is strengthening. Europe, the USA, China and other Asian countries are the main players, and China has overtaken the USA and Europe as the leading player. Inequality and ‘small-world’ characteristics appear in renewable energy trade. Solar energy trade presents a triadic community structure with Europe, the USA and China as the dominant players, while hydro energy trade presents a smaller and more dispersed structure. The core–periphery structure strongly suggests a trade dependency between hubs and peripheral elements in renewable energy trade. Developing countries should design appropriate incentives and contribute to particular segments in renewable energy value chain to accelerate and benefit from the South–South renewable energy trade. - Highlights: • Renewable energy trade networks are identified and analyzed. • Tripartite confrontational renewable energy trade systems have been formed and are strengthening. • Unequal and ‘small world’ characteristics have appeared in the renewable energy trade. • China has overtaken the USA and Europe as the leading player in the renewable energy trade. • Developing countries should make efforts to benefit from the South–South energy trade.

Energy Harvesting for Structural Health Monitoring Sensor Networks

Energy Technology Data Exchange (ETDEWEB)

Park, G.; Farrar, C. R.; Todd, M. D.; Hodgkiss, T.; Rosing, T.

2007-02-26

This report has been developed based on information exchanges at a 2.5-day workshop on energy harvesting for embedded structural health monitoring (SHM) sensing systems that was held June 28-30, 2005, at Los Alamos National Laboratory. The workshop was hosted by the LANL/UCSD Engineering Institute (EI). This Institute is an education- and research-focused collaboration between Los Alamos National Laboratory (LANL) and the University of California, San Diego (UCSD), Jacobs School of Engineering. A Statistical Pattern Recognition paradigm for SHM is first presented and the concept of energy harvesting for embedded sensing systems is addressed with respect to the data acquisition portion of this paradigm. Next, various existing and emerging sensing modalities used for SHM and their respective power requirements are summarized, followed by a discussion of SHM sensor network paradigms, power requirements for these networks and power optimization strategies. Various approaches to energy harvesting and energy storage are discussed and limitations associated with the current technology are addressed. This discussion also addresses current energy harvesting applications and system integration issues. The report concludes by defining some future research directions and possible technology demonstrations that are aimed at transitioning the concept of energy harvesting for embedded SHM sensing systems from laboratory research to field-deployed engineering prototypes.

Map of decentralised energy potential based on renewable energy sources in Croatia

International Nuclear Information System (INIS)

Schneider, D. R.; Ban, M.; Duic, N.; Bogdan, Z.

2005-01-01

Although the Republic of Croatia is almost completely electrified there are still regions where electricity network is not in place or network capacity is insufficient. These regions usually include areas of special state care (underdeveloped, war-affected or depopulated areas), islands, and mountainous areas. However, they often have good renewable energy potential. Decentralised energy generation based on renewable energy sources (wind power, hydropower, solar energy, biomass) has potential to ensure energy supply to users in remote and often isolated rural areas (off-grid applications). Such applications will primarily be related to tourism business in mountainous, rural and island/coastal regions. Also, agriculture, wood-processing and food-processing industries will potentially be interested in application of decentralised energy generation systems, most likely those using biomass as fuel (for example cogeneration facilities, connected on-grid).(author)

Green IGP Link Weights for Energy-efficiency and Load-balancing in IP Backbone Networks

OpenAIRE

Francois, Frederic; Wang, Ning; Moessner, Klaus; Georgoulas, Stylianos; Xu, Ke

2013-01-01

The energy consumption of backbone networks has become a primary concern for network operators and regulators due to the pervasive deployment of wired backbone networks to meet the requirements of bandwidth-hungry applications. While traditional optimization of IGP link weights has been used in IP based load-balancing operations, in this paper we introduce a novel link weight setting algorithm, the Green Load-balancing Algorithm (GLA), which is able to jointly optimize both energy efficiency ...

An Energy-Efficient Scheme for Multirelay Cooperative Networks with Energy Harvesting

Directory of Open Access Journals (Sweden)

Dingcheng Yang

2016-01-01

Full Text Available This study investigates an energy-efficient scheme in multirelay cooperative networks with energy harvesting where multiple sessions need to communicate with each other via the relay node. A two-step optimal method is proposed which maximizes the system energy efficiency, while taking into account the receiver circuit energy consumption. Firstly, the optimal power allocation for relay nodes is determined to maximize the system throughput; this is based on directional water-filling algorithm. Secondly, using quantum particle swarm optimization (QPSO, a joint relay node selection and session grouping optimization is proposed. With this algorithm, sessions can be classified into multiple groups that are assisted by the specific relay node with the maximum energy efficiency. This approach leads to a better global optimization in searching ability and efficiency. Simulation results show that the proposed scheme can improve the energy efficiency effectively compared with direct transmission and opportunistic relay-selected cooperative transmission.

A Hybrid Energy Efficient Protocol for Mobile Ad Hoc Networks

Directory of Open Access Journals (Sweden)

Niranjan Kumar Ray

2016-01-01

Full Text Available We proposed an energy conservation technique called Location Based Topology Control with Sleep Scheduling for ad hoc networks. It uses the feature of both topology control approach and power management approach. Like the topology control approach, it attempts to reduce the transmission power of a node, which is determined from its neighborhood location information. A node goes to sleep state based on the traffic condition as that of power management approach. In the proposed scheme, a node goes to sleep state only when its absence does not create local partition in its neighborhood. We preformed extensive simulation to compare the proposed scheme with existing ones. Simulation results show that the energy consumption is lower with increase in the network lifetime and higher throughput in the proposed scheme.

Convolutional networks for fast, energy-efficient neuromorphic computing

Science.gov (United States)

Esser, Steven K.; Merolla, Paul A.; Arthur, John V.; Cassidy, Andrew S.; Appuswamy, Rathinakumar; Andreopoulos, Alexander; Berg, David J.; McKinstry, Jeffrey L.; Melano, Timothy; Barch, Davis R.; di Nolfo, Carmelo; Datta, Pallab; Amir, Arnon; Taba, Brian; Flickner, Myron D.; Modha, Dharmendra S.

2016-01-01

Deep networks are now able to achieve human-level performance on a broad spectrum of recognition tasks. Independently, neuromorphic computing has now demonstrated unprecedented energy-efficiency through a new chip architecture based on spiking neurons, low precision synapses, and a scalable communication network. Here, we demonstrate that neuromorphic computing, despite its novel architectural primitives, can implement deep convolution networks that (i) approach state-of-the-art classification accuracy across eight standard datasets encompassing vision and speech, (ii) perform inference while preserving the hardware’s underlying energy-efficiency and high throughput, running on the aforementioned datasets at between 1,200 and 2,600 frames/s and using between 25 and 275 mW (effectively >6,000 frames/s per Watt), and (iii) can be specified and trained using backpropagation with the same ease-of-use as contemporary deep learning. This approach allows the algorithmic power of deep learning to be merged with the efficiency of neuromorphic processors, bringing the promise of embedded, intelligent, brain-inspired computing one step closer. PMID:27651489

Knowledge network model of the energy consumption in discrete manufacturing system

Science.gov (United States)

Xu, Binzi; Wang, Yan; Ji, Zhicheng

2017-07-01

Discrete manufacturing system generates a large amount of data and information because of the development of information technology. Hence, a management mechanism is urgently required. In order to incorporate knowledge generated from manufacturing data and production experience, a knowledge network model of the energy consumption in the discrete manufacturing system was put forward based on knowledge network theory and multi-granularity modular ontology technology. This model could provide a standard representation for concepts, terms and their relationships, which could be understood by both human and computer. Besides, the formal description of energy consumption knowledge elements (ECKEs) in the knowledge network was also given. Finally, an application example was used to verify the feasibility of the proposed method.

Markov Chain Model-Based Optimal Cluster Heads Selection for Wireless Sensor Networks

Directory of Open Access Journals (Sweden)

Gulnaz Ahmed

2017-02-01

Full Text Available The longer network lifetime of Wireless Sensor Networks (WSNs is a goal which is directly related to energy consumption. This energy consumption issue becomes more challenging when the energy load is not properly distributed in the sensing area. The hierarchal clustering architecture is the best choice for these kind of issues. In this paper, we introduce a novel clustering protocol called Markov chain model-based optimal cluster heads (MOCHs selection for WSNs. In our proposed model, we introduce a simple strategy for the optimal number of cluster heads selection to overcome the problem of uneven energy distribution in the network. The attractiveness of our model is that the BS controls the number of cluster heads while the cluster heads control the cluster members in each cluster in such a restricted manner that a uniform and even load is ensured in each cluster. We perform an extensive range of simulation using five quality measures, namely: the lifetime of the network, stable and unstable region in the lifetime of the network, throughput of the network, the number of cluster heads in the network, and the transmission time of the network to analyze the proposed model. We compare MOCHs against Sleep-awake Energy Efficient Distributed (SEED clustering, Artificial Bee Colony (ABC, Zone Based Routing (ZBR, and Centralized Energy Efficient Clustering (CEEC using the above-discussed quality metrics and found that the lifetime of the proposed model is almost 1095, 2630, 3599, and 2045 rounds (time steps greater than SEED, ABC, ZBR, and CEEC, respectively. The obtained results demonstrate that the MOCHs is better than SEED, ABC, ZBR, and CEEC in terms of energy efficiency and the network throughput.

Topology control of tactical wireless sensor networks using energy efficient zone routing

Directory of Open Access Journals (Sweden)

Preetha Thulasiraman

2016-02-01

Full Text Available The US Department of Defense (DoD routinely uses wireless sensor networks (WSNs for military tactical communications. Sensor node die-out has a significant impact on the topology of a tactical WSN. This is problematic for military applications where situational data is critical to tactical decision making. To increase the amount of time all sensor nodes remain active within the network and to control the network topology tactically, energy efficient routing mechanisms must be employed. In this paper, we aim to provide realistic insights on the practical advantages and disadvantages of using established routing techniques for tactical WSNs. We investigate the following established routing algorithms: direct routing, minimum transmission energy (MTE, Low Energy Adaptive Cluster Head routing (LEACH, and zone clustering. Based on the node die out statistics observed with these algorithms and the topological impact the node die outs have on the network, we develop a novel, energy efficient zone clustering algorithm called EZone. Via extensive simulations using MATLAB, we analyze the effectiveness of these algorithms on network performance for single and multiple gateway scenarios and show that the EZone algorithm tactically controls the topology of the network, thereby maintaining significant service area coverage when compared to the other routing algorithms.

Transport energy demand modeling of South Korea using artificial neural network

International Nuclear Information System (INIS)

Geem, Zong Woo

2011-01-01

Artificial neural network models were developed to forecast South Korea's transport energy demand. Various independent variables, such as GDP, population, oil price, number of vehicle registrations, and passenger transport amount, were considered and several good models (Model 1 with GDP, population, and passenger transport amount; Model 2 with GDP, number of vehicle registrations, and passenger transport amount; and Model 3 with oil price, number of vehicle registrations, and passenger transport amount) were selected by comparing with multiple linear regression models. Although certain regression models obtained better R-squared values than neural network models, this does not guarantee the fact that the former is better than the latter because root mean squared errors of the former were much inferior to those of the latter. Also, certain regression model had structural weakness based on P-value. Instead, neural network models produced more robust results. Forecasted results using the neural network models show that South Korea will consume around 37 MTOE of transport energy in 2025. - Highlights: → Transport energy demand of South Korea was forecasted using artificial neural network. → Various variables (GDP, population, oil price, number of registrations, etc.) were considered. → Results of artificial neural network were compared with those of multiple linear regression.

Energy model for rumor propagation on social networks

Science.gov (United States)

Han, Shuo; Zhuang, Fuzhen; He, Qing; Shi, Zhongzhi; Ao, Xiang

2014-01-01

With the development of social networks, the impact of rumor propagation on human lives is more and more significant. Due to the change of propagation mode, traditional rumor propagation models designed for word-of-mouth process may not be suitable for describing the rumor spreading on social networks. To overcome this shortcoming, we carefully analyze the mechanisms of rumor propagation and the topological properties of large-scale social networks, then propose a novel model based on the physical theory. In this model, heat energy calculation formula and Metropolis rule are introduced to formalize this problem and the amount of heat energy is used to measure a rumor’s impact on a network. Finally, we conduct track experiments to show the evolution of rumor propagation, make comparison experiments to contrast the proposed model with the traditional models, and perform simulation experiments to study the dynamics of rumor spreading. The experiments show that (1) the rumor propagation simulated by our model goes through three stages: rapid growth, fluctuant persistence and slow decline; (2) individuals could spread a rumor repeatedly, which leads to the rumor’s resurgence; (3) rumor propagation is greatly influenced by a rumor’s attraction, the initial rumormonger and the sending probability.

Energy Harvesting Chip and the Chip Based Power Supply Development for a Wireless Sensor Network.

Science.gov (United States)

Lee, Dasheng

2008-12-02

In this study, an energy harvesting chip was developed to scavenge energy from artificial light to charge a wireless sensor node. The chip core is a miniature transformer with a nano-ferrofluid magnetic core. The chip embedded transformer can convert harvested energy from its solar cell to variable voltage output for driving multiple loads. This chip system yields a simple, small, and more importantly, a battery-less power supply solution. The sensor node is equipped with multiple sensors that can be enabled by the energy harvesting power supply to collect information about the human body comfort degree. Compared with lab instruments, the nodes with temperature, humidity and photosensors driven by harvested energy had variation coefficient measurement precision of less than 6% deviation under low environmental light of 240 lux. The thermal comfort was affected by the air speed. A flow sensor equipped on the sensor node was used to detect airflow speed. Due to its high power consumption, this sensor node provided 15% less accuracy than the instruments, but it still can meet the requirement of analysis for predicted mean votes (PMV) measurement. The energy harvesting wireless sensor network (WSN) was deployed in a 24-hour convenience store to detect thermal comfort degree from the air conditioning control. During one year operation, the sensor network powered by the energy harvesting chip retained normal functions to collect the PMV index of the store. According to the one month statistics of communication status, the packet loss rate (PLR) is 2.3%, which is as good as the presented results of those WSNs powered by battery. Referring to the electric power records, almost 54% energy can be saved by the feedback control of an energy harvesting sensor network. These results illustrate that, scavenging energy not only creates a reliable power source for electronic devices, such as wireless sensor nodes, but can also be an energy source by building an energy efficient

Energy Harvesting Chip and the Chip Based Power Supply Development for a Wireless Sensor Network

Science.gov (United States)

Lee, Dasheng

2008-01-01

In this study, an energy harvesting chip was developed to scavenge energy from artificial light to charge a wireless sensor node. The chip core is a miniature transformer with a nano-ferrofluid magnetic core. The chip embedded transformer can convert harvested energy from its solar cell to variable voltage output for driving multiple loads. This chip system yields a simple, small, and more importantly, a battery-less power supply solution. The sensor node is equipped with multiple sensors that can be enabled by the energy harvesting power supply to collect information about the human body comfort degree. Compared with lab instruments, the nodes with temperature, humidity and photosensors driven by harvested energy had variation coefficient measurement precision of less than 6% deviation under low environmental light of 240 lux. The thermal comfort was affected by the air speed. A flow sensor equipped on the sensor node was used to detect airflow speed. Due to its high power consumption, this sensor node provided 15% less accuracy than the instruments, but it still can meet the requirement of analysis for predicted mean votes (PMV) measurement. The energy harvesting wireless sensor network (WSN) was deployed in a 24-hour convenience store to detect thermal comfort degree from the air conditioning control. During one year operation, the sensor network powered by the energy harvesting chip retained normal functions to collect the PMV index of the store. According to the one month statistics of communication status, the packet loss rate (PLR) is 2.3%, which is as good as the presented results of those WSNs powered by battery. Referring to the electric power records, almost 54% energy can be saved by the feedback control of an energy harvesting sensor network. These results illustrate that, scavenging energy not only creates a reliable power source for electronic devices, such as wireless sensor nodes, but can also be an energy source by building an energy efficient

Energy Harvesting Chip and the Chip Based Power Supply Development for a Wireless Sensor Network

Directory of Open Access Journals (Sweden)

Dasheng Lee

2008-12-01

Full Text Available In this study, an energy harvesting chip was developed to scavenge energy from artificial light to charge a wireless sensor node. The chip core is a miniature transformer with a nano-ferrofluid magnetic core. The chip embedded transformer can convert harvested energy from its solar cell to variable voltage output for driving multiple loads. This chip system yields a simple, small, and more importantly, a battery-less power supply solution. The sensor node is equipped with multiple sensors that can be enabled by the energy harvesting power supply to collect information about the human body comfort degree. Compared with lab instruments, the nodes with temperature, humidity and photosensors driven by harvested energy had variation coefficient measurement precision of less than 6% deviation under low environmental light of 240 lux. The thermal comfort was affected by the air speed. A flow sensor equipped on the sensor node was used to detect airflow speed. Due to its high power consumption, this sensor node provided 15% less accuracy than the instruments, but it still can meet the requirement of analysis for predicted mean votes (PMV measurement. The energy harvesting wireless sensor network (WSN was deployed in a 24-hour convenience store to detect thermal comfort degree from the air conditioning control. During one year operation, the sensor network powered by the energy harvesting chip retained normal functions to collect the PMV index of the store. According to the one month statistics of communication status, the packet loss rate (PLR is 2.3%, which is as good as the presented results of those WSNs powered by battery. Referring to the electric power records, almost 54% energy can be saved by the feedback control of an energy harvesting sensor network. These results illustrate that, scavenging energy not only creates a reliable power source for electronic devices, such as wireless sensor nodes, but can also be an energy source by building an

An Energy Balanced and Lifetime Extended Routing Protocol for Underwater Sensor Networks.

Science.gov (United States)

Wang, Hao; Wang, Shilian; Zhang, Eryang; Lu, Luxi

2018-05-17

Energy limitation is an adverse problem in designing routing protocols for underwater sensor networks (UWSNs). To prolong the network lifetime with limited battery power, an energy balanced and efficient routing protocol, called energy balanced and lifetime extended routing protocol (EBLE), is proposed in this paper. The proposed EBLE not only balances traffic loads according to the residual energy, but also optimizes data transmissions by selecting low-cost paths. Two phases are operated in the EBLE data transmission process: (1) candidate forwarding set selection phase and (2) data transmission phase. In candidate forwarding set selection phase, nodes update candidate forwarding nodes by broadcasting the position and residual energy level information. The cost value of available nodes is calculated and stored in each sensor node. Then in data transmission phase, high residual energy and relatively low-cost paths are selected based on the cost function and residual energy level information. We also introduce detailed analysis of optimal energy consumption in UWSNs. Numerical simulation results on a variety of node distributions and data load distributions prove that EBLE outperforms other routing protocols (BTM, BEAR and direct transmission) in terms of network lifetime and energy efficiency.

Power allocation strategies to minimize energy consumption in wireless body area networks.

Science.gov (United States)

Kailas, Aravind

2011-01-01

The wide scale deployment of wireless body area networks (WBANs) hinges on designing energy efficient communication protocols to support the reliable communication as well as to prolong the network lifetime. Cooperative communications, a relatively new idea in wireless communications, offers the benefits of multi-antenna systems, thereby improving the link reliability and boosting energy efficiency. In this short paper, the advantages of resorting to cooperative communications for WBANs in terms of minimized energy consumption are investigated. Adopting an energy model that encompasses energy consumptions in the transmitter and receiver circuits, and transmitting energy per bit, it is seen that cooperative transmission can improve energy efficiency of the wireless network. In particular, the problem of optimal power allocation is studied with the constraint of targeted outage probability. Two strategies of power allocation are considered: power allocation with and without posture state information. Using analysis and simulation-based results, two key points are demonstrated: (i) allocating power to the on-body sensors making use of the posture information can reduce the total energy consumption of the WBAN; and (ii) when the channel condition is good, it is better to recruit less relays for cooperation to enhance energy efficiency.

Energy Efficient Link Aware Routing with Power Control in Wireless Ad Hoc Networks.

Science.gov (United States)

Katiravan, Jeevaa; Sylvia, D; Rao, D Srinivasa

2015-01-01

In wireless ad hoc networks, the traditional routing protocols make the route selection based on minimum distance between the nodes and the minimum number of hop counts. Most of the routing decisions do not consider the condition of the network such as link quality and residual energy of the nodes. Also, when a link failure occurs, a route discovery mechanism is initiated which incurs high routing overhead. If the broadcast nature and the spatial diversity of the wireless communication are utilized efficiently it becomes possible to achieve improvement in the performance of the wireless networks. In contrast to the traditional routing scheme which makes use of a predetermined route for packet transmission, such an opportunistic routing scheme defines a predefined forwarding candidate list formed by using single network metrics. In this paper, a protocol is proposed which uses multiple metrics such as residual energy and link quality for route selection and also includes a monitoring mechanism which initiates a route discovery for a poor link, thereby reducing the overhead involved and improving the throughput of the network while maintaining network connectivity. Power control is also implemented not only to save energy but also to improve the network performance. Using simulations, we show the performance improvement attained in the network in terms of packet delivery ratio, routing overhead, and residual energy of the network.

Energy Efficient Link Aware Routing with Power Control in Wireless Ad Hoc Networks

Directory of Open Access Journals (Sweden)

Jeevaa Katiravan

2015-01-01

Full Text Available In wireless ad hoc networks, the traditional routing protocols make the route selection based on minimum distance between the nodes and the minimum number of hop counts. Most of the routing decisions do not consider the condition of the network such as link quality and residual energy of the nodes. Also, when a link failure occurs, a route discovery mechanism is initiated which incurs high routing overhead. If the broadcast nature and the spatial diversity of the wireless communication are utilized efficiently it becomes possible to achieve improvement in the performance of the wireless networks. In contrast to the traditional routing scheme which makes use of a predetermined route for packet transmission, such an opportunistic routing scheme defines a predefined forwarding candidate list formed by using single network metrics. In this paper, a protocol is proposed which uses multiple metrics such as residual energy and link quality for route selection and also includes a monitoring mechanism which initiates a route discovery for a poor link, thereby reducing the overhead involved and improving the throughput of the network while maintaining network connectivity. Power control is also implemented not only to save energy but also to improve the network performance. Using simulations, we show the performance improvement attained in the network in terms of packet delivery ratio, routing overhead, and residual energy of the network.

Energy Harvesting Hybrid Acoustic-Optical Underwater Wireless Sensor Networks Localization

Directory of Open Access Journals (Sweden)

Nasir Saeed

2017-12-01

Full Text Available Underwater wireless technologies demand to transmit at higher data rate for ocean exploration. Currently, large coverage is achieved by acoustic sensor networks with low data rate, high cost, high latency, high power consumption, and negative impact on marine mammals. Meanwhile, optical communication for underwater networks has the advantage of the higher data rate albeit for limited communication distances. Moreover, energy consumption is another major problem for underwater sensor networks, due to limited battery power and difficulty in replacing or recharging the battery of a sensor node. The ultimate solution to this problem is to add energy harvesting capability to the acoustic-optical sensor nodes. Localization of underwater sensor networks is of utmost importance because the data collected from underwater sensor nodes is useful only if the location of the nodes is known. Therefore, a novel localization technique for energy harvesting hybrid acoustic-optical underwater wireless sensor networks (AO-UWSNs is proposed. AO-UWSN employs optical communication for higher data rate at a short transmission distance and employs acoustic communication for low data rate and long transmission distance. A hybrid received signal strength (RSS based localization technique is proposed to localize the nodes in AO-UWSNs. The proposed technique combines the noisy RSS based measurements from acoustic communication and optical communication and estimates the final locations of acoustic-optical sensor nodes. A weighted multiple observations paradigm is proposed for hybrid estimated distances to suppress the noisy observations and give more importance to the accurate observations. Furthermore, the closed form solution for Cramer-Rao lower bound (CRLB is derived for localization accuracy of the proposed technique.

Energy Harvesting Hybrid Acoustic-Optical Underwater Wireless Sensor Networks Localization.

Science.gov (United States)

Saeed, Nasir; Celik, Abdulkadir; Al-Naffouri, Tareq Y; Alouini, Mohamed-Slim

2017-12-26

Underwater wireless technologies demand to transmit at higher data rate for ocean exploration. Currently, large coverage is achieved by acoustic sensor networks with low data rate, high cost, high latency, high power consumption, and negative impact on marine mammals. Meanwhile, optical communication for underwater networks has the advantage of the higher data rate albeit for limited communication distances. Moreover, energy consumption is another major problem for underwater sensor networks, due to limited battery power and difficulty in replacing or recharging the battery of a sensor node. The ultimate solution to this problem is to add energy harvesting capability to the acoustic-optical sensor nodes. Localization of underwater sensor networks is of utmost importance because the data collected from underwater sensor nodes is useful only if the location of the nodes is known. Therefore, a novel localization technique for energy harvesting hybrid acoustic-optical underwater wireless sensor networks (AO-UWSNs) is proposed. AO-UWSN employs optical communication for higher data rate at a short transmission distance and employs acoustic communication for low data rate and long transmission distance. A hybrid received signal strength (RSS) based localization technique is proposed to localize the nodes in AO-UWSNs. The proposed technique combines the noisy RSS based measurements from acoustic communication and optical communication and estimates the final locations of acoustic-optical sensor nodes. A weighted multiple observations paradigm is proposed for hybrid estimated distances to suppress the noisy observations and give more importance to the accurate observations. Furthermore, the closed form solution for Cramer-Rao lower bound (CRLB) is derived for localization accuracy of the proposed technique.

Energy Harvesting Hybrid Acoustic-Optical Underwater Wireless Sensor Networks Localization

KAUST Repository

Saeed, Nasir; Celik, Abdulkadir; Al-Naffouri, Tareq Y.; Alouini, Mohamed-Slim

2017-01-01

Underwater wireless technologies demand to transmit at higher data rate for ocean exploration. Currently, large coverage is achieved by acoustic sensor networks with low data rate, high cost, high latency, high power consumption, and negative impact on marine mammals. Meanwhile, optical communication for underwater networks has the advantage of the higher data rate albeit for limited communication distances. Moreover, energy consumption is another major problem for underwater sensor networks, due to limited battery power and difficulty in replacing or recharging the battery of a sensor node. The ultimate solution to this problem is to add energy harvesting capability to the acoustic-optical sensor nodes. Localization of underwater sensor networks is of utmost importance because the data collected from underwater sensor nodes is useful only if the location of the nodes is known. Therefore, a novel localization technique for energy harvesting hybrid acoustic-optical underwater wireless sensor networks (AO-UWSNs) is proposed. AO-UWSN employs optical communication for higher data rate at a short transmission distance and employs acoustic communication for low data rate and long transmission distance. A hybrid received signal strength (RSS) based localization technique is proposed to localize the nodes in AO-UWSNs. The proposed technique combines the noisy RSS based measurements from acoustic communication and optical communication and estimates the final locations of acoustic-optical sensor nodes. A weighted multiple observations paradigm is proposed for hybrid estimated distances to suppress the noisy observations and give more importance to the accurate observations. Furthermore, the closed form solution for Cramer-Rao lower bound (CRLB) is derived for localization accuracy of the proposed technique.

Energy Harvesting Hybrid Acoustic-Optical Underwater Wireless Sensor Networks Localization

KAUST Repository

Saeed, Nasir

2017-12-26

Underwater wireless technologies demand to transmit at higher data rate for ocean exploration. Currently, large coverage is achieved by acoustic sensor networks with low data rate, high cost, high latency, high power consumption, and negative impact on marine mammals. Meanwhile, optical communication for underwater networks has the advantage of the higher data rate albeit for limited communication distances. Moreover, energy consumption is another major problem for underwater sensor networks, due to limited battery power and difficulty in replacing or recharging the battery of a sensor node. The ultimate solution to this problem is to add energy harvesting capability to the acoustic-optical sensor nodes. Localization of underwater sensor networks is of utmost importance because the data collected from underwater sensor nodes is useful only if the location of the nodes is known. Therefore, a novel localization technique for energy harvesting hybrid acoustic-optical underwater wireless sensor networks (AO-UWSNs) is proposed. AO-UWSN employs optical communication for higher data rate at a short transmission distance and employs acoustic communication for low data rate and long transmission distance. A hybrid received signal strength (RSS) based localization technique is proposed to localize the nodes in AO-UWSNs. The proposed technique combines the noisy RSS based measurements from acoustic communication and optical communication and estimates the final locations of acoustic-optical sensor nodes. A weighted multiple observations paradigm is proposed for hybrid estimated distances to suppress the noisy observations and give more importance to the accurate observations. Furthermore, the closed form solution for Cramer-Rao lower bound (CRLB) is derived for localization accuracy of the proposed technique.

Optimal satisfaction degree in energy harvesting cognitive radio networks

Science.gov (United States)

Li, Zan; Liu, Bo-Yang; Si, Jiang-Bo; Zhou, Fu-Hui

2015-12-01

A cognitive radio (CR) network with energy harvesting (EH) is considered to improve both spectrum efficiency and energy efficiency. A hidden Markov model (HMM) is used to characterize the imperfect spectrum sensing process. In order to maximize the whole satisfaction degree (WSD) of the cognitive radio network, a tradeoff between the average throughput of the secondary user (SU) and the interference to the primary user (PU) is analyzed. We formulate the satisfaction degree optimization problem as a mixed integer nonlinear programming (MINLP) problem. The satisfaction degree optimization problem is solved by using differential evolution (DE) algorithm. The proposed optimization problem allows the network to adaptively achieve the optimal solution based on its required quality of service (Qos). Numerical results are given to verify our analysis. Project supported by the National Natural Science Foundation of China (Grant No. 61301179), the Doctorial Programs Foundation of the Ministry of Education of China (Grant No. 20110203110011), and the 111 Project (Grant No. B08038).

Power Efficient Service Differentiation Based on Traffic-Aware Survivable Elastic Optical Networks

DEFF Research Database (Denmark)

Turus, Ioan; Fagertun, Anna Manolova; Dittmann, Lars

2014-01-01

This study assesses the feasible energy savings whendefining different service classes based on protection schemesincore optical networks.Wepropose a dedicated energy savingstrategy for each of the service classes in order to minimize theoverall power consumption of the network.Four Classes of Se...... while for the proposed approach the difference in power consumption is almost negligible.Moreover, incase of the proposed approach,silver serviceclass can benefit for superior quality of service compared to the gold service class, due to the grooming mechanism.......This study assesses the feasible energy savings whendefining different service classes based on protection schemesincore optical networks.Wepropose a dedicated energy savingstrategy for each of the service classes in order to minimize theoverall power consumption of the network.Four Classes...... the sleep-mode capability of the opto-electronic devices as well as the elastic data-rateadaptation based on symbol-rate and modulation-format re-configurations. The results show that in the baseline approach the power consumption is strongly dependent on the ratio between the different service classes...

Minimizing the Energy Consumption in ‎Wireless Sensor Networks

Directory of Open Access Journals (Sweden)

Mohammed Saad Talib

2017-12-01

Full Text Available Energy in Wireless Sensor networks (WSNs represents an essential factor in designing, controlling and operating the sensor networks. Minimizing the consumed energy in WSNs application is a crucial issue for the network effectiveness and efficiency in terms of lifetime, cost and operation. Number of algorithms and protocols were proposed and implemented to decrease the energy consumption. WSNs operate with battery powered sensors. Sensors batteries have not easily rechargeable even though having restricted power. Frequently the network failure occurs due to the sensors energy insufficiency. MAC protocols in WSNs achieved low duty-cycle by employing periodic sleep and wakeup. Predictive Wakeup MAC (PW-MAC protocol was made use of the asynchronous duty cycling. It reduces the consumption of the node energy by allowing the senders to predict the receiver′s wakeup times. The WSN must be applied in an efficient manner to utilize the sensor nodes and their energy to ensure efficient network throughput. Prediction of the WSN lifetime previously to its installation represents a significant concern. To ensure energy efficiency the sensors duty cycles must be adjusted appropriately to meet the network traffic demands. The energy consumed in each node due to its switching between the active and the idle states were also estimated. The sensors are assumed to be randomly deployed. This paper aims to improve the randomly deployed network lifetime by scheduling the effects of transmission, reception and sleep states on the sensor node energy consumption. Results for these states with many performance metrics were also studied and discussed

Energy-Efficient Data Gathering Scheme Based on Broadcast Transmissions in Wireless Sensor Networks

Directory of Open Access Journals (Sweden)

Soobin Lee

2013-01-01

previous works have proposed ideas that reduce the energy consumption of the network by exploiting the spatial correlation between sensed information. In this paper, we propose a distributed data compression framework that exploits the broadcasting characteristic of the wireless medium to improve energy efficiency. We analyze the performance of the proposed framework numerically and compare it with the performance of previous works using simulation. The proposed scheme performs better when the sensing information is correlated.

From free energy to expected energy: Improving energy-based value function approximation in reinforcement learning.

Science.gov (United States)

Elfwing, Stefan; Uchibe, Eiji; Doya, Kenji

2016-12-01

Free-energy based reinforcement learning (FERL) was proposed for learning in high-dimensional state and action spaces. However, the FERL method does only really work well with binary, or close to binary, state input, where the number of active states is fewer than the number of non-active states. In the FERL method, the value function is approximated by the negative free energy of a restricted Boltzmann machine (RBM). In our earlier study, we demonstrated that the performance and the robustness of the FERL method can be improved by scaling the free energy by a constant that is related to the size of network. In this study, we propose that RBM function approximation can be further improved by approximating the value function by the negative expected energy (EERL), instead of the negative free energy, as well as being able to handle continuous state input. We validate our proposed method by demonstrating that EERL: (1) outperforms FERL, as well as standard neural network and linear function approximation, for three versions of a gridworld task with high-dimensional image state input; (2) achieves new state-of-the-art results in stochastic SZ-Tetris in both model-free and model-based learning settings; and (3) significantly outperforms FERL and standard neural network function approximation for a robot navigation task with raw and noisy RGB images as state input and a large number of actions. Copyright © 2016 The Author(s). Published by Elsevier Ltd.. All rights reserved.

A novel method for energy harvesting simulation based on scenario generation

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Wang, Zhe; Li, Taoshen; Xiao, Nan; Ye, Jin; Wu, Min

2018-06-01

Energy harvesting network (EHN) is a new form of computer networks. It converts ambient energy into usable electric energy and supply the electrical energy as a primary or secondary power source to the communication devices. However, most of the EHN uses the analytical probability distribution function to describe the energy harvesting process, which cannot accurately identify the actual situation for the lack of authenticity. We propose an EHN simulation method based on scenario generation in this paper. Firstly, instead of setting a probability distribution in advance, it uses optimal scenario reduction technology to generate representative scenarios in single period based on the historical data of the harvested energy. Secondly, it uses homogeneous simulated annealing algorithm to generate optimal daily energy harvesting scenario sequences to get a more accurate simulation of the random characteristics of the energy harvesting network. Then taking the actual wind power data as an example, the accuracy and stability of the method are verified by comparing with the real data. Finally, we cite an instance to optimize the network throughput, which indicate the feasibility and effectiveness of the method we proposed from the optimal solution and data analysis in energy harvesting simulation.

Towards energy aware optical networks and interconnects

Science.gov (United States)

Glesk, Ivan; Osadola, Tolulope; Idris, Siti

2013-10-01

In a today's world, information technology has been identified as one of the major factors driving economic prosperity. Datacenters businesses have been growing significantly in the past few years. The equipments in these datacenters need to be efficiently connected to each other and also to the outside world in order to enable effective exchange of information. This is why there is need for highly scalable, energy savvy and reliable network connectivity infrastructure that is capable of accommodating the large volume of data being exchanged at any time within the datacenter network and the outside network in general. These devices that can ensure such effective connectivity currently require large amount of energy in order to meet up with these increasing demands. In this paper, an overview of works being done towards realizing energy aware optical networks and interconnects for datacenters is presented. Also an OCDMA approach is discussed as potential multiple access technique for future optical network interconnections. We also presented some challenges that might inhibit effective implementation of the OCDMA multiplexing scheme.

Neural network model for proton-proton collision at high energy

International Nuclear Information System (INIS)

El-Bakry, M.Y.; El-Metwally, K.A.

2003-01-01

Developments in artificial intelligence (AI) techniques and their applications to physics have made it feasible to develop and implement new modeling techniques for high-energy interactions. In particular, AI techniques of artificial neural networks (ANN) have recently been used to design and implement more effective models. The primary purpose of this paper is to model the proton-proton (p-p) collision using the ANN technique. Following a review of the conventional techniques and an introduction to the neural network, the paper presents simulation test results using an p-p based ANN model trained with experimental data. The p-p based ANN model calculates the multiplicity distribution of charged particles and the inelastic cross section of the p-p collision at high energies. The results amply demonstrate the feasibility of such new technique in extracting the collision features and prove its effectiveness

Stochastic multi-objective model for optimal energy exchange optimization of networked microgrids with presence of renewable generation under risk-based strategies.

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Gazijahani, Farhad Samadi; Ravadanegh, Sajad Najafi; Salehi, Javad

2018-02-01

The inherent volatility and unpredictable nature of renewable generations and load demand pose considerable challenges for energy exchange optimization of microgrids (MG). To address these challenges, this paper proposes a new risk-based multi-objective energy exchange optimization for networked MGs from economic and reliability standpoints under load consumption and renewable power generation uncertainties. In so doing, three various risk-based strategies are distinguished by using conditional value at risk (CVaR) approach. The proposed model is specified as a two-distinct objective function. The first function minimizes the operation and maintenance costs, cost of power transaction between upstream network and MGs as well as power loss cost, whereas the second function minimizes the energy not supplied (ENS) value. Furthermore, the stochastic scenario-based approach is incorporated into the approach in order to handle the uncertainty. Also, Kantorovich distance scenario reduction method has been implemented to reduce the computational burden. Finally, non-dominated sorting genetic algorithm (NSGAII) is applied to minimize the objective functions simultaneously and the best solution is extracted by fuzzy satisfying method with respect to risk-based strategies. To indicate the performance of the proposed model, it is performed on the modified IEEE 33-bus distribution system and the obtained results show that the presented approach can be considered as an efficient tool for optimal energy exchange optimization of MGs. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

Energy aware swarm optimization with intercluster search for wireless sensor network.

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Thilagavathi, Shanmugasundaram; Geetha, Bhavani Gnanasambandan

2015-01-01

Wireless sensor networks (WSNs) are emerging as a low cost popular solution for many real-world challenges. The low cost ensures deployment of large sensor arrays to perform military and civilian tasks. Generally, WSNs are power constrained due to their unique deployment method which makes replacement of battery source difficult. Challenges in WSN include a well-organized communication platform for the network with negligible power utilization. In this work, an improved binary particle swarm optimization (PSO) algorithm with modified connected dominating set (CDS) based on residual energy is proposed for discovery of optimal number of clusters and cluster head (CH). Simulations show that the proposed BPSO-T and BPSO-EADS perform better than LEACH- and PSO-based system in terms of energy savings and QOS.

Joint Mobile Data Collection and Wireless Energy Transfer in Wireless Rechargeable Sensor Networks.

Science.gov (United States)

Zhong, Ping; Li, Ya-Ting; Liu, Wei-Rong; Duan, Gui-Hua; Chen, Ying-Wen; Xiong, Neal

2017-08-16

In wireless rechargeable sensor networks (WRSNs), there is a way to use mobile vehicles to charge node and collect data. It is a rational pattern to use two types of vehicles, one is for energy charging, and the other is for data collecting. These two types of vehicles, data collection vehicles (DCVs) and wireless charging vehicles (WCVs), are employed to achieve high efficiency in both data gathering and energy consumption. To handle the complex scheduling problem of multiple vehicles in large-scale networks, a twice-partition algorithm based on center points is proposed to divide the network into several parts. In addition, an anchor selection algorithm based on the tradeoff between neighbor amount and residual energy, named AS-NAE, is proposed to collect the zonal data. It can reduce the data transmission delay and the energy consumption for DCVs' movement in the zonal. Besides, we design an optimization function to achieve maximum data throughput by adjusting data rate and link rate of each node. Finally, the effectiveness of proposed algorithm is validated by numerical simulation results in WRSNs.