Energy-efficient algorithm for classification of states of wireless sensor network using machine learning methods

Science.gov (United States)

Yuldashev, M. N.; Vlasov, A. I.; Novikov, A. N.

2018-05-01

This paper focuses on the development of an energy-efficient algorithm for classification of states of a wireless sensor network using machine learning methods. The proposed algorithm reduces energy consumption by: 1) elimination of monitoring of parameters that do not affect the state of the sensor network, 2) reduction of communication sessions over the network (the data are transmitted only if their values can affect the state of the sensor network). The studies of the proposed algorithm have shown that at classification accuracy close to 100%, the number of communication sessions can be reduced by 80%.

A Distributed and Energy-Efficient Algorithm for Event K-Coverage in Underwater Sensor Networks

Directory of Open Access Journals (Sweden)

Peng Jiang

2017-01-01

Full Text Available For event dynamic K-coverage algorithms, each management node selects its assistant node by using a greedy algorithm without considering the residual energy and situations in which a node is selected by several events. This approach affects network energy consumption and balance. Therefore, this study proposes a distributed and energy-efficient event K-coverage algorithm (DEEKA. After the network achieves 1-coverage, the nodes that detect the same event compete for the event management node with the number of candidate nodes and the average residual energy, as well as the distance to the event. Second, each management node estimates the probability of its neighbor nodes’ being selected by the event it manages with the distance level, the residual energy level, and the number of dynamic coverage event of these nodes. Third, each management node establishes an optimization model that uses expectation energy consumption and the residual energy variance of its neighbor nodes and detects the performance of the events it manages as targets. Finally, each management node uses a constrained non-dominated sorting genetic algorithm (NSGA-II to obtain the Pareto set of the model and the best strategy via technique for order preference by similarity to an ideal solution (TOPSIS. The algorithm first considers the effect of harsh underwater environments on information collection and transmission. It also considers the residual energy of a node and a situation in which the node is selected by several other events. Simulation results show that, unlike the on-demand variable sensing K-coverage algorithm, DEEKA balances and reduces network energy consumption, thereby prolonging the network’s best service quality and lifetime.

Hybrid Swarm Intelligence Energy Efficient Clustered Routing Algorithm for Wireless Sensor Networks

Directory of Open Access Journals (Sweden)

Rajeev Kumar

2016-01-01

Full Text Available Currently, wireless sensor networks (WSNs are used in many applications, namely, environment monitoring, disaster management, industrial automation, and medical electronics. Sensor nodes carry many limitations like low battery life, small memory space, and limited computing capability. To create a wireless sensor network more energy efficient, swarm intelligence technique has been applied to resolve many optimization issues in WSNs. In many existing clustering techniques an artificial bee colony (ABC algorithm is utilized to collect information from the field periodically. Nevertheless, in the event based applications, an ant colony optimization (ACO is a good solution to enhance the network lifespan. In this paper, we combine both algorithms (i.e., ABC and ACO and propose a new hybrid ABCACO algorithm to solve a Nondeterministic Polynomial (NP hard and finite problem of WSNs. ABCACO algorithm is divided into three main parts: (i selection of optimal number of subregions and further subregion parts, (ii cluster head selection using ABC algorithm, and (iii efficient data transmission using ACO algorithm. We use a hierarchical clustering technique for data transmission; the data is transmitted from member nodes to the subcluster heads and then from subcluster heads to the elected cluster heads based on some threshold value. Cluster heads use an ACO algorithm to discover the best route for data transmission to the base station (BS. The proposed approach is very useful in designing the framework for forest fire detection and monitoring. The simulation results show that the ABCACO algorithm enhances the stability period by 60% and also improves the goodput by 31% against LEACH and WSNCABC, respectively.

Energy-Efficient Algorithm for Sensor Networks with Non-Uniform Maximum Transmission Range

Directory of Open Access Journals (Sweden)

Yimin Yu

2011-06-01

Full Text Available In wireless sensor networks (WSNs, the energy hole problem is a key factor affecting the network lifetime. In a circular multi-hop sensor network (modeled as concentric coronas, the optimal transmission ranges of all coronas can effectively improve network lifetime. In this paper, we investigate WSNs with non-uniform maximum transmission ranges, where sensor nodes deployed in different regions may differ in their maximum transmission range. Then, we propose an Energy-efficient algorithm for Non-uniform Maximum Transmission range (ENMT, which can search approximate optimal transmission ranges of all coronas in order to prolong network lifetime. Furthermore, the simulation results indicate that ENMT performs better than other algorithms.

Profiling high performance dense linear algebra algorithms on multicore architectures for power and energy efficiency

KAUST Repository

Ltaief, Hatem

2011-08-31

This paper presents the power profile of two high performance dense linear algebra libraries i.e., LAPACK and PLASMA. The former is based on block algorithms that use the fork-join paradigm to achieve parallel performance. The latter uses fine-grained task parallelism that recasts the computation to operate on submatrices called tiles. In this way tile algorithms are formed. We show results from the power profiling of the most common routines, which permits us to clearly identify the different phases of the computations. This allows us to isolate the bottlenecks in terms of energy efficiency. Our results show that PLASMA surpasses LAPACK not only in terms of performance but also in terms of energy efficiency. © 2011 Springer-Verlag.

Energy efficient model based algorithm for control of building HVAC systems.

Science.gov (United States)

Kirubakaran, V; Sahu, Chinmay; Radhakrishnan, T K; Sivakumaran, N

2015-11-01

Energy efficient designs are receiving increasing attention in various fields of engineering. Heating ventilation and air conditioning (HVAC) control system designs involve improved energy usage with an acceptable relaxation in thermal comfort. In this paper, real time data from a building HVAC system provided by BuildingLAB is considered. A resistor-capacitor (RC) framework for representing thermal dynamics of the building is estimated using particle swarm optimization (PSO) algorithm. With objective costs as thermal comfort (deviation of room temperature from required temperature) and energy measure (Ecm) explicit MPC design for this building model is executed based on its state space representation of the supply water temperature (input)/room temperature (output) dynamics. The controllers are subjected to servo tracking and external disturbance (ambient temperature) is provided from the real time data during closed loop control. The control strategies are ported on a PIC32mx series microcontroller platform. The building model is implemented in MATLAB and hardware in loop (HIL) testing of the strategies is executed over a USB port. Results indicate that compared to traditional proportional integral (PI) controllers, the explicit MPC's improve both energy efficiency and thermal comfort significantly. Copyright © 2015 Elsevier Inc. All rights reserved.

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...

Development of a thermal control algorithm using artificial neural network models for improved thermal comfort and energy efficiency in accommodation buildings

International Nuclear Information System (INIS)

Moon, Jin Woo; Jung, Sung Kwon

2016-01-01

Highlights: • An ANN model for predicting optimal start moment of the cooling system was developed. • An ANN model for predicting the amount of cooling energy consumption was developed. • An optimal control algorithm was developed employing two ANN models. • The algorithm showed the advanced thermal comfort and energy efficiency. - Abstract: The aim of this study was to develop a control algorithm to demonstrate the improved thermal comfort and building energy efficiency of accommodation buildings in the cooling season. For this, two artificial neural network (ANN)-based predictive and adaptive models were developed and employed in the algorithm. One model predicted the cooling energy consumption during the unoccupied period for different setback temperatures and the other predicted the time required for restoring current indoor temperature to the normal set-point temperature. Using numerical simulation methods, the prediction accuracy of the two ANN models and the performance of the algorithm were tested. Through the test result analysis, the two ANN models showed their prediction accuracy with an acceptable error rate when applied in the control algorithm. In addition, the two ANN models based algorithm can be used to provide a more comfortable and energy efficient indoor thermal environment than the two conventional control methods, which respectively employed a fixed set-point temperature for the entire day and a setback temperature during the unoccupied period. Therefore, the operating range was 23–26 °C during the occupied period and 25–28 °C during the unoccupied period. Based on the analysis, it can be concluded that the optimal algorithm with two predictive and adaptive ANN models can be used to design a more comfortable and energy efficient indoor thermal environment for accommodation buildings in a comprehensive manner.

An energy efficient distance-aware routing algorithm with multiple mobile sinks for wireless sensor networks.

Science.gov (United States)

Wang, Jin; Li, Bin; Xia, Feng; Kim, Chang-Seob; Kim, Jeong-Uk

2014-08-18

Traffic patterns in wireless sensor networks (WSNs) usually follow a many-to-one model. Sensor nodes close to static sinks will deplete their limited energy more rapidly than other sensors, since they will have more data to forward during multihop transmission. This will cause network partition, isolated nodes and much shortened network lifetime. Thus, how to balance energy consumption for sensor nodes is an important research issue. In recent years, exploiting sink mobility technology in WSNs has attracted much research attention because it can not only improve energy efficiency, but prolong network lifetime. In this paper, we propose an energy efficient distance-aware routing algorithm with multiple mobile sink for WSNs, where sink nodes will move with a certain speed along the network boundary to collect monitored data. We study the influence of multiple mobile sink nodes on energy consumption and network lifetime, and we mainly focus on the selection of mobile sink node number and the selection of parking positions, as well as their impact on performance metrics above. We can see that both mobile sink node number and the selection of parking position have important influence on network performance. Simulation results show that our proposed routing algorithm has better performance than traditional routing ones in terms of energy consumption.

An Energy Efficient Distance-Aware Routing Algorithm with Multiple Mobile Sinks for Wireless Sensor Networks

Directory of Open Access Journals (Sweden)

Jin Wang

2014-08-01

Full Text Available Traffic patterns in wireless sensor networks (WSNs usually follow a many-to-one model. Sensor nodes close to static sinks will deplete their limited energy more rapidly than other sensors, since they will have more data to forward during multihop transmission. This will cause network partition, isolated nodes and much shortened network lifetime. Thus, how to balance energy consumption for sensor nodes is an important research issue. In recent years, exploiting sink mobility technology in WSNs has attracted much research attention because it can not only improve energy efficiency, but prolong network lifetime. In this paper, we propose an energy efficient distance-aware routing algorithm with multiple mobile sink for WSNs, where sink nodes will move with a certain speed along the network boundary to collect monitored data. We study the influence of multiple mobile sink nodes on energy consumption and network lifetime, and we mainly focus on the selection of mobile sink node number and the selection of parking positions, as well as their impact on performance metrics above. We can see that both mobile sink node number and the selection of parking position have important influence on network performance. Simulation results show that our proposed routing algorithm has better performance than traditional routing ones in terms of energy consumption.

Distributed Energy-Efficient Topology Control Algorithm in Home M2M Networks

OpenAIRE

Lee, Chao-Yang; Yang, Chu-Sing

2012-01-01

Because machine-to-machine (M2M) technology enables machines to communicate with each other without human intervention, it could play a big role in sensor network systems. Through wireless sensor network (WSN) gateways, various information can be collected by sensors for M2M systems. For home M2M networks, this study proposes a distributed energy-efficient topology control algorithm for both topology construction and topology maintenance. Topology control is an effective method of enhancing e...

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.

CPAC: Energy-Efficient Data Collection through Adaptive Selection of Compression Algorithms for Sensor Networks

Science.gov (United States)

Lee, HyungJune; Kim, HyunSeok; Chang, Ik Joon

2014-01-01

We propose a technique to optimize the energy efficiency of data collection in sensor networks by exploiting a selective data compression. To achieve such an aim, we need to make optimal decisions regarding two aspects: (1) which sensor nodes should execute compression; and (2) which compression algorithm should be used by the selected sensor nodes. We formulate this problem into binary integer programs, which provide an energy-optimal solution under the given latency constraint. Our simulation results show that the optimization algorithm significantly reduces the overall network-wide energy consumption for data collection. In the environment having a stationary sink from stationary sensor nodes, the optimized data collection shows 47% energy savings compared to the state-of-the-art collection protocol (CTP). More importantly, we demonstrate that our optimized data collection provides the best performance in an intermittent network under high interference. In such networks, we found that the selective compression for frequent packet retransmissions saves up to 55% energy compared to the best known protocol. PMID:24721763

A Low Power Consumption Algorithm for Efficient Energy Consumption in ZigBee Motes.

Science.gov (United States)

Vaquerizo-Hdez, Daniel; Muñoz, Pablo; R-Moreno, María D; F Barrero, David

2017-09-22

Wireless Sensor Networks (WSNs) are becoming increasingly popular since they can gather information from different locations without wires. This advantage is exploited in applications such as robotic systems, telecare, domotic or smart cities, among others. To gain independence from the electricity grid, WSNs devices are equipped with batteries, therefore their operational time is determined by the time that the batteries can power on the device. As a consequence, engineers must consider low energy consumption as a critical objective to design WSNs. Several approaches can be taken to make efficient use of energy in WSNs, for instance low-duty-cycling sensor networks (LDC-WSN). Based on the LDC-WSNs, we present LOKA, a LOw power Konsumption Algorithm to minimize WSNs energy consumption using different power modes in a sensor mote. The contribution of the work is a novel algorithm called LOKA that implements two duty-cycling mechanisms using the end-device of the ZigBee protocol (of the Application Support Sublayer) and an external microcontroller (Cortex M0+) in order to minimize the energy consumption of a delay tolerant networking. Experiments show that using LOKA, the energy required by the sensor device is reduced to half with respect to the same sensor device without using LOKA.

A Low Power Consumption Algorithm for Efficient Energy Consumption in ZigBee Motes

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Daniel Vaquerizo-Hdez

2017-09-01

Full Text Available Wireless Sensor Networks (WSNs are becoming increasingly popular since they can gather information from different locations without wires. This advantage is exploited in applications such as robotic systems, telecare, domotic or smart cities, among others. To gain independence from the electricity grid, WSNs devices are equipped with batteries, therefore their operational time is determined by the time that the batteries can power on the device. As a consequence, engineers must consider low energy consumption as a critical objective to design WSNs. Several approaches can be taken to make efficient use of energy in WSNs, for instance low-duty-cycling sensor networks (LDC-WSN. Based on the LDC-WSNs, we present LOKA, a LOw power Konsumption Algorithm to minimize WSNs energy consumption using different power modes in a sensor mote. The contribution of the work is a novel algorithm called LOKA that implements two duty-cycling mechanisms using the end-device of the ZigBee protocol (of the Application Support Sublayer and an external microcontroller (Cortex M0+ in order to minimize the energy consumption of a delay tolerant networking. Experiments show that using LOKA, the energy required by the sensor device is reduced to half with respect to the same sensor device without using LOKA.

An Energy Efficient Adaptive Sampling Algorithm in a Sensor Network for Automated Water Quality Monitoring.

Science.gov (United States)

Shu, Tongxin; Xia, Min; Chen, Jiahong; Silva, Clarence de

2017-11-05

Power management is crucial in the monitoring of a remote environment, especially when long-term monitoring is needed. Renewable energy sources such as solar and wind may be harvested to sustain a monitoring system. However, without proper power management, equipment within the monitoring system may become nonfunctional and, as a consequence, the data or events captured during the monitoring process will become inaccurate as well. This paper develops and applies a novel adaptive sampling algorithm for power management in the automated monitoring of the quality of water in an extensive and remote aquatic environment. Based on the data collected on line using sensor nodes, a data-driven adaptive sampling algorithm (DDASA) is developed for improving the power efficiency while ensuring the accuracy of sampled data. The developed algorithm is evaluated using two distinct key parameters, which are dissolved oxygen (DO) and turbidity. It is found that by dynamically changing the sampling frequency, the battery lifetime can be effectively prolonged while maintaining a required level of sampling accuracy. According to the simulation results, compared to a fixed sampling rate, approximately 30.66% of the battery energy can be saved for three months of continuous water quality monitoring. Using the same dataset to compare with a traditional adaptive sampling algorithm (ASA), while achieving around the same Normalized Mean Error (NME), DDASA is superior in saving 5.31% more battery energy.

An Energy Efficient Adaptive Sampling Algorithm in a Sensor Network for Automated Water Quality Monitoring

Directory of Open Access Journals (Sweden)

Tongxin Shu

2017-11-01

Full Text Available Power management is crucial in the monitoring of a remote environment, especially when long-term monitoring is needed. Renewable energy sources such as solar and wind may be harvested to sustain a monitoring system. However, without proper power management, equipment within the monitoring system may become nonfunctional and, as a consequence, the data or events captured during the monitoring process will become inaccurate as well. This paper develops and applies a novel adaptive sampling algorithm for power management in the automated monitoring of the quality of water in an extensive and remote aquatic environment. Based on the data collected on line using sensor nodes, a data-driven adaptive sampling algorithm (DDASA is developed for improving the power efficiency while ensuring the accuracy of sampled data. The developed algorithm is evaluated using two distinct key parameters, which are dissolved oxygen (DO and turbidity. It is found that by dynamically changing the sampling frequency, the battery lifetime can be effectively prolonged while maintaining a required level of sampling accuracy. According to the simulation results, compared to a fixed sampling rate, approximately 30.66% of the battery energy can be saved for three months of continuous water quality monitoring. Using the same dataset to compare with a traditional adaptive sampling algorithm (ASA, while achieving around the same Normalized Mean Error (NME, DDASA is superior in saving 5.31% more battery energy.

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.

Genetic algorithm-based fuzzy-PID control methodologies for enhancement of energy efficiency of a dynamic energy system

International Nuclear Information System (INIS)

Jahedi, G.; Ardehali, M.M.

2011-01-01

The simplicity in coding the heuristic judgment of experienced operator by means of fuzzy logic can be exploited for enhancement of energy efficiency. Fuzzy logic has been used as an effective tool for scheduling conventional PID controllers gain coefficients (F-PID). However, to search for the most desirable fuzzy system characteristics that allow for best performance of the energy system with minimum energy input, optimization techniques such as genetic algorithm (GA) could be utilized and the control methodology is identified as GA-based F-PID (GA-F-PID). The objective of this study is to examine the performance of PID, F-PID, and GA-F-PID controllers for enhancement of energy efficiency of a dynamic energy system. The performance evaluation of the controllers is accomplished by means of two cost functions that are based on the quadratic forms of the energy input and deviation from a setpoint temperature, referred to as energy and comfort costs, respectively. The GA-F-PID controller is examined in two different forms, namely, global form and local form. For the global form, all possible combinations of fuzzy system characteristics in the search domain are explored by GA for finding the fittest chromosome for all discrete time intervals during the entire operation period. For the local form, however, GA is used in each discrete time interval to find the fittest chromosome for implementation. The results show that the global form GA-F-PID and local form GA-F-PID control methodologies, in comparison with PID controller, achieve higher energy efficiency by lowering energy costs by 51.2%, and 67.8%, respectively. Similarly, the comfort costs for deviation from setpoint are enhanced by 54.4%, and 62.4%, respectively. It is determined that GA-F-PID performs better in local from than global form.

A Pareto-based multi-objective optimization algorithm to design energy-efficient shading devices

International Nuclear Information System (INIS)

Khoroshiltseva, Marina; Slanzi, Debora; Poli, Irene

2016-01-01

Highlights: • We present a multi-objective optimization algorithm for shading design. • We combine Harmony search and Pareto-based procedures. • Thermal and daylighting performances of external shading were considered. • We applied the optimization process to a residential social housing in Madrid. - Abstract: In this paper we address the problem of designing new energy-efficient static daylight devices that will surround the external windows of a residential building in Madrid. Shading devices can in fact largely influence solar gains in a building and improve thermal and lighting comforts by selectively intercepting the solar radiation and by reducing the undesirable glare. A proper shading device can therefore significantly increase the thermal performance of a building by reducing its energy demand in different climate conditions. In order to identify the set of optimal shading devices that allow a low energy consumption of the dwelling while maintaining high levels of thermal and lighting comfort for the inhabitants we derive a multi-objective optimization methodology based on Harmony Search and Pareto front approaches. The results show that the multi-objective approach here proposed is an effective procedure in designing energy efficient shading devices when a large set of conflicting objectives characterizes the performance of the proposed solutions.

Energy-Efficient Scheduling Problem Using an Effective Hybrid Multi-Objective Evolutionary Algorithm

Directory of Open Access Journals (Sweden)

Lvjiang Yin

2016-12-01

Full Text Available Nowadays, manufacturing enterprises face the challenge of just-in-time (JIT production and energy saving. Therefore, study of JIT production and energy consumption is necessary and important in manufacturing sectors. Moreover, energy saving can be attained by the operational method and turn off/on idle machine method, which also increases the complexity of problem solving. Thus, most researchers still focus on small scale problems with one objective: a single machine environment. However, the scheduling problem is a multi-objective optimization problem in real applications. In this paper, a single machine scheduling model with controllable processing and sequence dependence setup times is developed for minimizing the total earliness/tardiness (E/T, cost, and energy consumption simultaneously. An effective multi-objective evolutionary algorithm called local multi-objective evolutionary algorithm (LMOEA is presented to tackle this multi-objective scheduling problem. To accommodate the characteristic of the problem, a new solution representation is proposed, which can convert discrete combinational problems into continuous problems. Additionally, a multiple local search strategy with self-adaptive mechanism is introduced into the proposed algorithm to enhance the exploitation ability. The performance of the proposed algorithm is evaluated by instances with comparison to other multi-objective meta-heuristics such as Nondominated Sorting Genetic Algorithm II (NSGA-II, Strength Pareto Evolutionary Algorithm 2 (SPEA2, Multiobjective Particle Swarm Optimization (OMOPSO, and Multiobjective Evolutionary Algorithm Based on Decomposition (MOEA/D. Experimental results demonstrate that the proposed LMOEA algorithm outperforms its counterparts for this kind of scheduling problems.

Power Analysis of Energy Efficient DES Algorithm and Implementation on 28nm FPGA

DEFF Research Database (Denmark)

Thind, Vandana; Pandey, Bishwajeet; Hussain, Dil muhammed Akbar

2016-01-01

In this work, we have done power analysis ofData Encryption Standard (DES) algorithm using Xilinx ISE software development kit. We have analyzed the amount of power utilized by selective components on board i.e., FPGA Artix-7, where DES algorithm is implemented. The components taken into consider......In this work, we have done power analysis ofData Encryption Standard (DES) algorithm using Xilinx ISE software development kit. We have analyzed the amount of power utilized by selective components on board i.e., FPGA Artix-7, where DES algorithm is implemented. The components taken...... into consideration areclock power, logic power, signals power, IOs power, leakage powerand supply power (dynamic and quiescent). We have used four different WLAN frequencies (2.4 GHz, 3.6 GHz, 4.9GHz, and 5.9 GHz) and four different IO standards like HSTL-I, HSTL-II, HSTL-II-18, HSTL-I-18 for power analysis. We have...... achieved13-47% saving in power at different frequencies and withdifferent energy efficient HSTL IO standard. We calculated the percentage change in the IO power with respect to the mean values of IO power at four different frequencies. We notified that there is minimum of -37.5% and maximum of +35...

Experiences with Implementing a Distributed and Self-Organizing Scheduling Algorithm for Energy-Efficient Data Gathering on a Real-Life Sensor Network Platform

NARCIS (Netherlands)

Zhang, Y.; Chatterjea, Supriyo; Havinga, Paul J.M.

2007-01-01

We report our experiences with implementing a distributed and self-organizing scheduling algorithm designed for energy-efficient data gathering on a 25-node multihop wireless sensor network (WSN). The algorithm takes advantage of spatial correlations that exist in readings of adjacent sensor nodes

Energy Efficient and Safe Weighted Clustering Algorithm for Mobile Wireless Sensor Networks

Directory of Open Access Journals (Sweden)

Amine Dahane

2015-01-01

Full Text Available The main concern of clustering approaches for mobile wireless sensor networks (WSNs is to prolong the battery life of the individual sensors and the network lifetime. For a successful clustering approach the need of a powerful mechanism to safely elect a cluster head remains a challenging task in many research works that take into account the mobility of the network. The approach based on the computing of the weight of each node in the network is one of the proposed techniques to deal with this problem. In this paper, we propose an energy efficient and safe weighted clustering algorithm (ES-WCA for mobile WSNs using a combination of five metrics. Among these metrics lies the behavioral level metric which promotes a safe choice of a cluster head in the sense where this last one will never be a malicious node. Moreover, the highlight of our work is summarized in a comprehensive strategy for monitoring the network, in order to detect and remove the malicious nodes. We use simulation study to demonstrate the performance of the proposed algorithm.

Energy-driven scheduling algorithm for nanosatellite energy harvesting maximization

Science.gov (United States)

Slongo, L. K.; Martínez, S. V.; Eiterer, B. V. B.; Pereira, T. G.; Bezerra, E. A.; Paiva, K. V.

2018-06-01

The number of tasks that a satellite may execute in orbit is strongly related to the amount of energy its Electrical Power System (EPS) is able to harvest and to store. The manner the stored energy is distributed within the satellite has also a great impact on the CubeSat's overall efficiency. Most CubeSat's EPS do not prioritize energy constraints in their formulation. Unlike that, this work proposes an innovative energy-driven scheduling algorithm based on energy harvesting maximization policy. The energy harvesting circuit is mathematically modeled and the solar panel I-V curves are presented for different temperature and irradiance levels. Considering the models and simulations, the scheduling algorithm is designed to keep solar panels working close to their maximum power point by triggering tasks in the appropriate form. Tasks execution affects battery voltage, which is coupled to the solar panels through a protection circuit. A software based Perturb and Observe strategy allows defining the tasks to be triggered. The scheduling algorithm is tested in FloripaSat, which is an 1U CubeSat. A test apparatus is proposed to emulate solar irradiance variation, considering the satellite movement around the Earth. Tests have been conducted to show that the scheduling algorithm improves the CubeSat energy harvesting capability by 4.48% in a three orbit experiment and up to 8.46% in a single orbit cycle in comparison with the CubeSat operating without the scheduling algorithm.

Evaluating the energy efficiency of a one pedal driving algorithm

NARCIS (Netherlands)

Wang, J.; Besselink, I.J.M.; van Boekel, J.J.P.; Nijmeijer, H.

2015-01-01

Regenerative braking of electric vehicles (EVs) is important to improve the energy efficiency and increase the vehicle range. However, the additional friction braking during deceleration may limit the amount of recuperated energy. To improve the energy efficiency and driving comfort of EVs, a one

Evaluation of stochastic algorithms for financial mathematics problems from point of view of energy-efficiency

Science.gov (United States)

Atanassov, E.; Dimitrov, D.; Gurov, T.

2015-10-01

The recent developments in the area of high-performance computing are driven not only by the desire for ever higher performance but also by the rising costs of electricity. The use of various types of accelerators like GPUs, Intel Xeon Phi has become mainstream and many algorithms and applications have been ported to make use of them where available. In Financial Mathematics the question of optimal use of computational resources should also take into account the limitations on space, because in many use cases the servers are deployed close to the exchanges. In this work we evaluate various algorithms for option pricing that we have implemented for different target architectures in terms of their energy and space efficiency. Since it has been established that low-discrepancy sequences may be better than pseudorandom numbers for these types of algorithms, we also test the Sobol and Halton sequences. We present the raw results, the computed metrics and conclusions from our tests.

Evaluation of stochastic algorithms for financial mathematics problems from point of view of energy-efficiency

Energy Technology Data Exchange (ETDEWEB)

Atanassov, E.; Dimitrov, D., E-mail: d.slavov@bas.bg, E-mail: emanouil@parallel.bas.bg, E-mail: gurov@bas.bg; Gurov, T. [Institute of Information and Communication Technologies, BAS, Acad. G. Bonchev str., bl. 25A, 1113 Sofia (Bulgaria)

2015-10-28

The recent developments in the area of high-performance computing are driven not only by the desire for ever higher performance but also by the rising costs of electricity. The use of various types of accelerators like GPUs, Intel Xeon Phi has become mainstream and many algorithms and applications have been ported to make use of them where available. In Financial Mathematics the question of optimal use of computational resources should also take into account the limitations on space, because in many use cases the servers are deployed close to the exchanges. In this work we evaluate various algorithms for option pricing that we have implemented for different target architectures in terms of their energy and space efficiency. Since it has been established that low-discrepancy sequences may be better than pseudorandom numbers for these types of algorithms, we also test the Sobol and Halton sequences. We present the raw results, the computed metrics and conclusions from our tests.

Energy-Efficient Train Operation Using Nature-Inspired Algorithms

Directory of Open Access Journals (Sweden)

Kemal Keskin

2017-01-01

Full Text Available A train operation optimization by minimizing its traction energy subject to various constraints is carried out using nature-inspired evolutionary algorithms. The optimization process results in switching points that initiate cruising and coasting phases of the driving. Due to nonlinear optimization formulation of the problem, nature-inspired evolutionary search methods, Genetic Simulated Annealing, Firefly, and Big Bang-Big Crunch algorithms were employed in this study. As a case study a real-like train and test track from a part of Eskisehir light rail network were modeled. Speed limitations, various track alignments, maximum allowable trip time, and changes in train mass were considered, and punctuality was put into objective function as a penalty factor. Results have shown that all three evolutionary methods generated effective and consistent solutions. However, it has also been shown that each one has different accuracy and convergence characteristics.

Optimal Energy Efficiency Fairness of Nodes in Wireless Powered Communication Networks.

Science.gov (United States)

Zhang, Jing; Zhou, Qingjie; Ng, Derrick Wing Kwan; Jo, Minho

2017-09-15

In wireless powered communication networks (WPCNs), it is essential to research energy efficiency fairness in order to evaluate the balance of nodes for receiving information and harvesting energy. In this paper, we propose an efficient iterative algorithm for optimal energy efficiency proportional fairness in WPCN. The main idea is to use stochastic geometry to derive the mean proportionally fairness utility function with respect to user association probability and receive threshold. Subsequently, we prove that the relaxed proportionally fairness utility function is a concave function for user association probability and receive threshold, respectively. At the same time, a sub-optimal algorithm by exploiting alternating optimization approach is proposed. Through numerical simulations, we demonstrate that our sub-optimal algorithm can obtain a result close to optimal energy efficiency proportional fairness with significant reduction of computational complexity.

Energy Efficient Position-Based Three Dimensional Routing for Wireless Sensor Networks

Directory of Open Access Journals (Sweden)

Jeongdae Kim

2008-04-01

Full Text Available In this paper, we focus on an energy efficient position-based three dimensional (3D routing algorithm using distance information, which affects transmission power consumption between nodes as a metric. In wireless sensor networks, energy efficiency is one of the primary objectives of research. In addition, recent interest in sensor networks is extended to the need to understand how to design networks in a 3D space. Generally, most wireless sensor networks are based on two dimensional (2D designs. However, in reality, such networks operate in a 3D space. Since 2D designs are simpler and easier to implement than 3D designs for routing algorithms in wireless sensor networks, the 2D assumption is somewhat justified and usually does not lead to major inaccuracies. However, in some applications such as an airborne to terrestrial sensor networks or sensor networks, which are deployed in mountains, taking 3D designs into consideration is reasonable. In this paper, we propose the Minimum Sum of Square distance (MSoS algorithm as an energy efficient position-based three dimensional routing algorithm. In addition, we evaluate and compare the performance of the proposed routing algorithm with other algorithms through simulation. Finally, the results of the simulation show that the proposed routing algorithm is more energy efficient than other algorithms in a 3D space.

Sparse RNA folding revisited: space-efficient minimum free energy structure prediction.

Science.gov (United States)

Will, Sebastian; Jabbari, Hosna

2016-01-01

RNA secondary structure prediction by energy minimization is the central computational tool for the analysis of structural non-coding RNAs and their interactions. Sparsification has been successfully applied to improve the time efficiency of various structure prediction algorithms while guaranteeing the same result; however, for many such folding problems, space efficiency is of even greater concern, particularly for long RNA sequences. So far, space-efficient sparsified RNA folding with fold reconstruction was solved only for simple base-pair-based pseudo-energy models. Here, we revisit the problem of space-efficient free energy minimization. Whereas the space-efficient minimization of the free energy has been sketched before, the reconstruction of the optimum structure has not even been discussed. We show that this reconstruction is not possible in trivial extension of the method for simple energy models. Then, we present the time- and space-efficient sparsified free energy minimization algorithm SparseMFEFold that guarantees MFE structure prediction. In particular, this novel algorithm provides efficient fold reconstruction based on dynamically garbage-collected trace arrows. The complexity of our algorithm depends on two parameters, the number of candidates Z and the number of trace arrows T; both are bounded by [Formula: see text], but are typically much smaller. The time complexity of RNA folding is reduced from [Formula: see text] to [Formula: see text]; the space complexity, from [Formula: see text] to [Formula: see text]. Our empirical results show more than 80 % space savings over RNAfold [Vienna RNA package] on the long RNAs from the RNA STRAND database (≥2500 bases). The presented technique is intentionally generalizable to complex prediction algorithms; due to their high space demands, algorithms like pseudoknot prediction and RNA-RNA-interaction prediction are expected to profit even stronger than "standard" MFE folding. SparseMFEFold is free

Diagnostic information system dynamics in the evaluation of machine learning algorithms for the supervision of energy efficiency of district heating-supplied buildings

International Nuclear Information System (INIS)

Kiluk, Sebastian

2017-01-01

Highlights: • Energy efficiency classification sustainability benefits from knowledge prediction. • Diagnostic classification can be validated with its dynamics and current data. • Diagnostic classification dynamics provides novelty extraction for knowledge update. • Data mining comparison can be performed with knowledge dynamics and uncertainty. • Diagnostic information refinement benefits form comparing classifiers dynamics. - Abstract: Modern ways of exploring the diagnostic knowledge provided by data mining and machine learning raise some concern about the ways of evaluating the quality of output knowledge, usually represented by information systems. Especially in district heating, the stationarity of efficiency models, and thus the relevance of diagnostic classification system, cannot be ensured due to the impact of social, economic or technological changes, which are hard to identify or predict. Therefore, data mining and machine learning have become an attractive strategy for automatically and continuously absorbing such dynamics. This paper presents a new method of evaluation and comparison of diagnostic information systems gathered algorithmically in district heating efficiency supervision based on exploring the evolution of information system and analyzing its dynamic features. The process of data mining and knowledge discovery was applied to the data acquired from district heating substations’ energy meters to provide the automated discovery of diagnostic knowledge base necessary for the efficiency supervision of district heating-supplied buildings. The implemented algorithm consists of several steps of processing the billing data, including preparation, segmentation, aggregation and knowledge discovery stage, where classes of abstract models representing energy efficiency constitute an information system representing diagnostic knowledge about the energy efficiency of buildings favorably operating under similar climate conditions and

Service-Aware Clustering: An Energy-Efficient Model for the Internet-of-Things.

Science.gov (United States)

Bagula, Antoine; Abidoye, Ademola Philip; Zodi, Guy-Alain Lusilao

2015-12-23

Current generation wireless sensor routing algorithms and protocols have been designed based on a myopic routing approach, where the motes are assumed to have the same sensing and communication capabilities. Myopic routing is not a natural fit for the IoT, as it may lead to energy imbalance and subsequent short-lived sensor networks, routing the sensor readings over the most service-intensive sensor nodes, while leaving the least active nodes idle. This paper revisits the issue of energy efficiency in sensor networks to propose a clustering model where sensor devices' service delivery is mapped into an energy awareness model, used to design a clustering algorithm that finds service-aware clustering (SAC) configurations in IoT settings. The performance evaluation reveals the relative energy efficiency of the proposed SAC algorithm compared to related routing algorithms in terms of energy consumption, the sensor nodes' life span and its traffic engineering efficiency in terms of throughput and delay. These include the well-known low energy adaptive clustering hierarchy (LEACH) and LEACH-centralized (LEACH-C) algorithms, as well as the most recent algorithms, such as DECSA and MOCRN.

Service-Aware Clustering: An Energy-Efficient Model for the Internet-of-Things

Directory of Open Access Journals (Sweden)

Antoine Bagula

2015-12-01

Full Text Available Current generation wireless sensor routing algorithms and protocols have been designed based on a myopic routing approach, where the motes are assumed to have the same sensing and communication capabilities. Myopic routing is not a natural fit for the IoT, as it may lead to energy imbalance and subsequent short-lived sensor networks, routing the sensor readings over the most service-intensive sensor nodes, while leaving the least active nodes idle. This paper revisits the issue of energy efficiency in sensor networks to propose a clustering model where sensor devices’ service delivery is mapped into an energy awareness model, used to design a clustering algorithm that finds service-aware clustering (SAC configurations in IoT settings. The performance evaluation reveals the relative energy efficiency of the proposed SAC algorithm compared to related routing algorithms in terms of energy consumption, the sensor nodes’ life span and its traffic engineering efficiency in terms of throughput and delay. These include the well-known low energy adaptive clustering hierarchy (LEACH and LEACH-centralized (LEACH-C algorithms, as well as the most recent algorithms, such as DECSA and MOCRN.

Efficient GPS Position Determination Algorithms

National Research Council Canada - National Science Library

Nguyen, Thao Q

2007-01-01

... differential GPS algorithm for a network of users. The stand-alone user GPS algorithm is a direct, closed-form, and efficient new position determination algorithm that exploits the closed-form solution of the GPS trilateration equations and works...

Energy-efficient computing and networking. Revised selected papers

Energy Technology Data Exchange (ETDEWEB)

Hatziargyriou, Nikos; Dimeas, Aris [Ethnikon Metsovion Polytechneion, Athens (Greece); Weidlich, Anke (eds.) [SAP Research Center, Karlsruhe (Germany); Tomtsi, Thomai

2011-07-01

This book constitutes the postproceedings of the First International Conference on Energy-Efficient Computing and Networking, E-Energy, held in Passau, Germany in April 2010. The 23 revised papers presented were carefully reviewed and selected for inclusion in the post-proceedings. The papers are organized in topical sections on energy market and algorithms, ICT technology for the energy market, implementation of smart grid and smart home technology, microgrids and energy management, and energy efficiency through distributed energy management and buildings. (orig.)

Energetic and exergetic efficiency modeling of a cargo aircraft by a topology improving neuro-evolution algorithm

International Nuclear Information System (INIS)

Baklacioglu, Tolga; Aydin, Hakan; Turan, Onder

2016-01-01

An aircraft is a complex system that requires methodologies for an efficient thermodynamic design process. So, it is important to gain a deeper understanding of energy and exergy use throughout an aircraft. The aim of this study is to propose a topology improving NE (neuro-evolution) algorithm modeling for assessing energy and exergy efficiency of a cargo aircraft for the phases of a flight. In this regard, energy and exergy data of the aircraft achieved from several engine runs at different power settings have been utilized to derive the ANN (artificial neural network) models optimized by a GA (genetic algorithm). NE of feed-forward networks trained by a BP (backpropagation) algorithm with momentum has assured the accomplishment of optimum initial network weights as well as the improvement of the network topology. The linear correlation coefficients very close to unity obtained for the derived ANN models have proved the tight fitting of the real data and the estimated values of the efficiencies provided by the models. Finally, compared to the trial-and-error case, evolving the networks by GAs has enhanced the accuracy of the modeling simply further as the reduction in the MSE (mean squared errors) for the energy and exergy efficiencies indicates. - Highlights: • Optimization using neuro-evolution algorithm. • Improved backpropagation algorithm using momentum factor. • Turboprop parameters as independent variables. • Energy and exergy efficiency modeling of a cargo aircraft.

A Traffic Prediction Algorithm for Street Lighting Control Efficiency

Directory of Open Access Journals (Sweden)

POPA Valentin

2013-01-01

Full Text Available This paper presents the development of a traffic prediction algorithm that can be integrated in a street lighting monitoring and control system. The prediction algorithm must enable the reduction of energy costs and improve energy efficiency by decreasing the light intensity depending on the traffic level. The algorithm analyses and processes the information received at the command center based on the traffic level at different moments. The data is collected by means of the Doppler vehicle detection sensors integrated within the system. Thus, two methods are used for the implementation of the algorithm: a neural network and a k-NN (k-Nearest Neighbor prediction algorithm. For 500 training cycles, the mean square error of the neural network is 9.766 and for 500.000 training cycles the error amounts to 0.877. In case of the k-NN algorithm the error increases from 8.24 for k=5 to 12.27 for a number of 50 neighbors. In terms of a root means square error parameter, the use of a neural network ensures the highest performance level and can be integrated in a street lighting control system.

Energy-balanced algorithm for RFID estimation

Science.gov (United States)

Zhao, Jumin; Wang, Fangyuan; Li, Dengao; Yan, Lijuan

2016-10-01

RFID has been widely used in various commercial applications, ranging from inventory control, supply chain management to object tracking. It is necessary for us to estimate the number of RFID tags deployed in a large area periodically and automatically. Most of the prior works use passive tags to estimate and focus on designing time-efficient algorithms that can estimate tens of thousands of tags in seconds. But for a RFID reader to access tags in a large area, active tags are likely to be used due to their longer operational ranges. But these tags use their own battery as energy supplier. Hence, conserving energy for active tags becomes critical. Some prior works have studied how to reduce energy expenditure of a RFID reader when it reads tags IDs. In this paper, we study how to reduce the amount of energy consumed by active tags during the process of estimating the number of tags in a system and make the energy every tag consumed balanced approximately. We design energy-balanced estimation algorithm that can achieve our goal we mentioned above.

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 Efficient Multiresource Allocation of Virtual Machine Based on PSO in Cloud Data Center

Directory of Open Access Journals (Sweden)

An-ping Xiong

2014-01-01

Full Text Available Presently, massive energy consumption in cloud data center tends to be an escalating threat to the environment. To reduce energy consumption in cloud data center, an energy efficient virtual machine allocation algorithm is proposed in this paper based on a proposed energy efficient multiresource allocation model and the particle swarm optimization (PSO method. In this algorithm, the fitness function of PSO is defined as the total Euclidean distance to determine the optimal point between resource utilization and energy consumption. This algorithm can avoid falling into local optima which is common in traditional heuristic algorithms. Compared to traditional heuristic algorithms MBFD and MBFH, our algorithm shows significantly energy savings in cloud data center and also makes the utilization of system resources reasonable at the same time.

Wireless-Uplinks-Based Energy-Efficient Scheduling in Mobile Cloud Computing

Directory of Open Access Journals (Sweden)

Xing Liu

2015-01-01

Full Text Available Mobile cloud computing (MCC combines cloud computing and mobile internet to improve the computational capabilities of resource-constrained mobile devices (MDs. In MCC, mobile users could not only improve the computational capability of MDs but also save operation consumption by offloading the mobile applications to the cloud. However, MCC faces the problem of energy efficiency because of time-varying channels when the offloading is being executed. In this paper, we address the issue of energy-efficient scheduling for wireless uplink in MCC. By introducing Lyapunov optimization, we first propose a scheduling algorithm that can dynamically choose channel to transmit data based on queue backlog and channel statistics. Then, we show that the proposed scheduling algorithm can make a tradeoff between queue backlog and energy consumption in a channel-aware MCC system. Simulation results show that the proposed scheduling algorithm can reduce the time average energy consumption for offloading compared to the existing algorithm.

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.)

ALGORITHM TO CHOOSE ENERGY GENERATION MULTIPLE ROLE STATION

Directory of Open Access Journals (Sweden)

Alexandru STĂNESCU

2014-05-01

Full Text Available This paper proposes an algorithm that is based on a complex analysis method that is used for choosing the configuration of a power station. The station generates electric energy and hydrogen, and serves a "green" highway. The elements that need to be considered are: energy efficiency, location, availability of primary energy sources in the area, investment cost, workforce, environmental impact, compatibility with existing systems, meantime between failure.

A novel minimum cost maximum power algorithm for future smart home energy management.

Science.gov (United States)

Singaravelan, A; Kowsalya, M

2017-11-01

With the latest development of smart grid technology, the energy management system can be efficiently implemented at consumer premises. In this paper, an energy management system with wireless communication and smart meter are designed for scheduling the electric home appliances efficiently with an aim of reducing the cost and peak demand. For an efficient scheduling scheme, the appliances are classified into two types: uninterruptible and interruptible appliances. The problem formulation was constructed based on the practical constraints that make the proposed algorithm cope up with the real-time situation. The formulated problem was identified as Mixed Integer Linear Programming (MILP) problem, so this problem was solved by a step-wise approach. This paper proposes a novel Minimum Cost Maximum Power (MCMP) algorithm to solve the formulated problem. The proposed algorithm was simulated with input data available in the existing method. For validating the proposed MCMP algorithm, results were compared with the existing method. The compared results prove that the proposed algorithm efficiently reduces the consumer electricity consumption cost and peak demand to optimum level with 100% task completion without sacrificing the consumer comfort.

Informatics Solution for Energy Efficiency Improvement and Consumption Management of Householders

Directory of Open Access Journals (Sweden)

Simona-Vasilica Oprea

2018-01-01

Full Text Available Although in 2012 the European Union (EU has promoted energy efficiency in order to ensure a gradual 20% reduction of energy consumption by 2020, its targets related to energy efficiency have increased and extended to new time horizons. Therefore, in 2016, a new proposal for 2030 of energy efficiency target of 30% has been agreed. However, during the last years, even if the electricity consumption by households decreased in the EU-28, the largest expansion was recorded in Romania. Taking into account that the projected consumption peak is increasing and energy consumption management for residential activities is an important measure for energy efficiency improvement since its ratio from total consumption can be around 25–30%, in this paper, we propose an informatics solution that assists both electricity suppliers/grid operators and consumers. It includes three models for electricity consumption optimization, profiles, clustering and forecast. By this solution, the daily operation of appliances can be optimized and scheduled to minimize the consumption peak and reduce the stress on the grid. For optimization purpose, we propose three algorithms for shifting the operation of the programmable appliances from peak to off-peak hours. This approach enables the supplier to apply attractive time-of-use tariffs due to the fact that by flattening the consumption peak, it becomes more predictable, and thus improves the strategies on the electricity markets. According to the results of the optimization process, we compare the proposed algorithms emphasizing the benefits. For building consumption profiles, we develop a clustering algorithm based on self-organizing maps. By running the algorithm for three scenarios, well-delimited profiles are obtained. As for the consumption forecast, highly accurate feedforward artificial neural networks algorithm with backpropagation is implemented. Finally, we test these algorithms using several datasets showing their

Energy Efficient Payload Aggregation in WSNs

Directory of Open Access Journals (Sweden)

Ákos MILÁNKOVICH

2015-06-01

Full Text Available Creating wireless sensor networks requires a different approach than traditional communication networks because energy efficiency plays a key role in sensor networks, which consist of devices without external power. The amount of energy used determines the lifetime of these devices. In most cases data packets are less sensitive to delay, thus can be aggregated, making it possible to gather more useful information reducing the energy required to transmit information. This article discusses the energy efficiency of different Forward Error Correction algorithms and presents a method to calculate the optimal amount of aggregation of the data packets in terms of power consumption, while taking into account the Bit Error Rate characteristics of the wireless channel. The contribution of this paper is a general method to improve the energy efficiency of wireless sensor networks by using the optimal amount of aggregation in case of different Forward Error Correction codes and channel characteristics. The presented results can be applied to any packet-based wireless protocol.

An efficient quantum algorithm for spectral estimation

Science.gov (United States)

Steffens, Adrian; Rebentrost, Patrick; Marvian, Iman; Eisert, Jens; Lloyd, Seth

2017-03-01

We develop an efficient quantum implementation of an important signal processing algorithm for line spectral estimation: the matrix pencil method, which determines the frequencies and damping factors of signals consisting of finite sums of exponentially damped sinusoids. Our algorithm provides a quantum speedup in a natural regime where the sampling rate is much higher than the number of sinusoid components. Along the way, we develop techniques that are expected to be useful for other quantum algorithms as well—consecutive phase estimations to efficiently make products of asymmetric low rank matrices classically accessible and an alternative method to efficiently exponentiate non-Hermitian matrices. Our algorithm features an efficient quantum-classical division of labor: the time-critical steps are implemented in quantum superposition, while an interjacent step, requiring much fewer parameters, can operate classically. We show that frequencies and damping factors can be obtained in time logarithmic in the number of sampling points, exponentially faster than known classical algorithms.

New energy technologies 4. Energy management and energy efficiency

International Nuclear Information System (INIS)

Sabonnadiere, J.C.; Caire, R.; Raison, B.; Quenard, D.; Verneau, G.; Zissis, G.

2007-01-01

This forth tome of the new energy technologies handbook is devoted to energy management and to the improvement of energy efficiency. The energy management by decentralized generation insertion and network-driven load control, analyzes the insertion and management means of small power generation in distribution networks and the means for load management by the network with the aim of saving energy and limiting peak loads. The second part, devoted to energy efficiency presents in a detailed way the technologies allowing an optimal management of energy in buildings and leading to the implementation of positive energy buildings. A special chapter treats of energy saving using new lighting technologies in the private and public sectors. Content: 1 - decentralized power generation - impacts and solutions: threat or opportunity; deregulation; emerging generation means; impact of decentralized generation on power networks; elements of solution; 2 - mastery of energy demand - loads control by the network: stakes of loads control; choice of loads to be controlled; communication needs; measurements and controls for loads control; model and algorithm needs for loads control. A better energy efficiency: 3 - towards positive energy buildings: key data for Europe; how to convert fossil energy consuming buildings into low-energy consuming and even energy generating buildings; the Minergie brand; the PassivHaus or 'passive house' label; the zero-energy house/zero-energy home (ZEH); the zero-energy building (ZEB); the positive energy house; comparison between the three Minergie/PassivHaus/ZEH types of houses; beyond the positive energy building; 4 - light sources and lighting systems - from technology to energy saving: lighting yesterday and today; light sources and energy conversion; energy saving in the domain of lighting: study of some type-cases; what future for light sources. (J.S.)

A constrained optimization algorithm for total energy minimization in electronic structure calculations

International Nuclear Information System (INIS)

Yang Chao; Meza, Juan C.; Wang Linwang

2006-01-01

A new direct constrained optimization algorithm for minimizing the Kohn-Sham (KS) total energy functional is presented in this paper. The key ingredients of this algorithm involve projecting the total energy functional into a sequence of subspaces of small dimensions and seeking the minimizer of total energy functional within each subspace. The minimizer of a subspace energy functional not only provides a search direction along which the KS total energy functional decreases but also gives an optimal 'step-length' to move along this search direction. Numerical examples are provided to demonstrate that this new direct constrained optimization algorithm can be more efficient than the self-consistent field (SCF) iteration

An Efficient ABC_DE_Based Hybrid Algorithm for Protein–Ligand Docking

Directory of Open Access Journals (Sweden)

Boxin Guan

2018-04-01

Full Text Available Protein–ligand docking is a process of searching for the optimal binding conformation between the receptor and the ligand. Automated docking plays an important role in drug design, and an efficient search algorithm is needed to tackle the docking problem. To tackle the protein–ligand docking problem more efficiently, An ABC_DE_based hybrid algorithm (ADHDOCK, integrating artificial bee colony (ABC algorithm and differential evolution (DE algorithm, is proposed in the article. ADHDOCK applies an adaptive population partition (APP mechanism to reasonably allocate the computational resources of the population in each iteration process, which helps the novel method make better use of the advantages of ABC and DE. The experiment tested fifty protein–ligand docking problems to compare the performance of ADHDOCK, ABC, DE, Lamarckian genetic algorithm (LGA, running history information guided genetic algorithm (HIGA, and swarm optimization for highly flexible protein–ligand docking (SODOCK. The results clearly exhibit the capability of ADHDOCK toward finding the lowest energy and the smallest root-mean-square deviation (RMSD on most of the protein–ligand docking problems with respect to the other five algorithms.

Green-Frag: Energy-Efficient Frame Fragmentation Scheme for Wireless Sensor Networks

KAUST Repository

Daghistani, Anas H.

2013-01-01

that is optimized to be energy efficient, which is originated from the chosen frame fragmentation scheme. This new energy-efficient frame fragmentation protocol is called (Green-Frag). Green-Frag uses an algorithm that gives sensor nodes the ability to transmit data

Energy Efficiency Maximization for WSNs with Simultaneous Wireless Information and Power Transfer.

Science.gov (United States)

Yu, Hongyan; Zhang, Yongqiang; Guo, Songtao; Yang, Yuanyuan; Ji, Luyue

2017-08-18

Recently, the simultaneous wireless information and power transfer (SWIPT) technique has been regarded as a promising approach to enhance performance of wireless sensor networks with limited energy supply. However, from a green communication perspective, energy efficiency optimization for SWIPT system design has not been investigated in Wireless Rechargeable Sensor Networks (WRSNs). In this paper, we consider the tradeoffs between energy efficiency and three factors including spectral efficiency, the transmit power and outage target rate for two different modes, i.e., power splitting (PS) and time switching modes (TS), at the receiver. Moreover, we formulate the energy efficiency maximization problem subject to the constraints of minimum Quality of Service (QoS), minimum harvested energy and maximum transmission power as non-convex optimization problem. In particular, we focus on optimizing power control and power allocation policy in PS and TS modes to maximize energy efficiency of data transmission. For PS and TS modes, we propose the corresponding algorithm to characterize a non-convex optimization problem that takes into account the circuit power consumption and the harvested energy. By exploiting nonlinear fractional programming and Lagrangian dual decomposition, we propose suboptimal iterative algorithms to obtain the solutions of non-convex optimization problems. Furthermore, we derive the outage probability and effective throughput from the scenarios that the transmitter does not or partially know the channel state information (CSI) of the receiver. Simulation results illustrate that the proposed optimal iterative algorithm can achieve optimal solutions within a small number of iterations and various tradeoffs between energy efficiency and spectral efficiency, transmit power and outage target rate, respectively.

Energy Efficiency Maximization for WSNs with Simultaneous Wireless Information and Power Transfer

Science.gov (United States)

Yu, Hongyan; Zhang, Yongqiang; Yang, Yuanyuan; Ji, Luyue

2017-01-01

Recently, the simultaneous wireless information and power transfer (SWIPT) technique has been regarded as a promising approach to enhance performance of wireless sensor networks with limited energy supply. However, from a green communication perspective, energy efficiency optimization for SWIPT system design has not been investigated in Wireless Rechargeable Sensor Networks (WRSNs). In this paper, we consider the tradeoffs between energy efficiency and three factors including spectral efficiency, the transmit power and outage target rate for two different modes, i.e., power splitting (PS) and time switching modes (TS), at the receiver. Moreover, we formulate the energy efficiency maximization problem subject to the constraints of minimum Quality of Service (QoS), minimum harvested energy and maximum transmission power as non-convex optimization problem. In particular, we focus on optimizing power control and power allocation policy in PS and TS modes to maximize energy efficiency of data transmission. For PS and TS modes, we propose the corresponding algorithm to characterize a non-convex optimization problem that takes into account the circuit power consumption and the harvested energy. By exploiting nonlinear fractional programming and Lagrangian dual decomposition, we propose suboptimal iterative algorithms to obtain the solutions of non-convex optimization problems. Furthermore, we derive the outage probability and effective throughput from the scenarios that the transmitter does not or partially know the channel state information (CSI) of the receiver. Simulation results illustrate that the proposed optimal iterative algorithm can achieve optimal solutions within a small number of iterations and various tradeoffs between energy efficiency and spectral efficiency, transmit power and outage target rate, respectively. PMID:28820496

T-L Plane Abstraction-Based Energy-Efficient Real-Time Scheduling for Multi-Core Wireless Sensors

Directory of Open Access Journals (Sweden)

Youngmin Kim

2016-07-01

Full Text Available Energy efficiency is considered as a critical requirement for wireless sensor networks. As more wireless sensor nodes are equipped with multi-cores, there are emerging needs for energy-efficient real-time scheduling algorithms. The T-L plane-based scheme is known to be an optimal global scheduling technique for periodic real-time tasks on multi-cores. Unfortunately, there has been a scarcity of studies on extending T-L plane-based scheduling algorithms to exploit energy-saving techniques. In this paper, we propose a new T-L plane-based algorithm enabling energy-efficient real-time scheduling on multi-core sensor nodes with dynamic power management (DPM. Our approach addresses the overhead of processor mode transitions and reduces fragmentations of the idle time, which are inherent in T-L plane-based algorithms. Our experimental results show the effectiveness of the proposed algorithm compared to other energy-aware scheduling methods on T-L plane abstraction.

Energy Efficiency in Self Organising Networks

DEFF Research Database (Denmark)

Kisielius, Edvinas; Popovska Avramova, Andrijana; Zakrzewska, Anna

2013-01-01

We evaluate the performance of an energy efficient algorithm that controls power emissions and the number of powered cell sites (eNBs) in overlaid Long Term Evolution (LTE) networks. Simulations are carried out in OPNET Modeler and we investigate cells cites designed to meet peak hours trac demand...

A novel minimum cost maximum power algorithm for future smart home energy management

Directory of Open Access Journals (Sweden)

A. Singaravelan

2017-11-01

Full Text Available With the latest development of smart grid technology, the energy management system can be efficiently implemented at consumer premises. In this paper, an energy management system with wireless communication and smart meter are designed for scheduling the electric home appliances efficiently with an aim of reducing the cost and peak demand. For an efficient scheduling scheme, the appliances are classified into two types: uninterruptible and interruptible appliances. The problem formulation was constructed based on the practical constraints that make the proposed algorithm cope up with the real-time situation. The formulated problem was identified as Mixed Integer Linear Programming (MILP problem, so this problem was solved by a step-wise approach. This paper proposes a novel Minimum Cost Maximum Power (MCMP algorithm to solve the formulated problem. The proposed algorithm was simulated with input data available in the existing method. For validating the proposed MCMP algorithm, results were compared with the existing method. The compared results prove that the proposed algorithm efficiently reduces the consumer electricity consumption cost and peak demand to optimum level with 100% task completion without sacrificing the consumer comfort.

Saving time in a space-efficient simulation algorithm

NARCIS (Netherlands)

Markovski, J.

2011-01-01

We present an efficient algorithm for computing the simulation preorder and equivalence for labeled transition systems. The algorithm improves an existing space-efficient algorithm and improves its time complexity by employing a variant of the stability condition and exploiting properties of the

Optimization of Energy Efficiency and Conservation in Green Building Design Using Duelist, Killer-Whale and Rain-Water Algorithms

Science.gov (United States)

Biyanto, T. R.; Matradji; Syamsi, M. N.; Fibrianto, H. Y.; Afdanny, N.; Rahman, A. H.; Gunawan, K. S.; Pratama, J. A. D.; Malwindasari, A.; Abdillah, A. I.; Bethiana, T. N.; Putra, Y. A.

2017-11-01

The development of green building has been growing in both design and quality. The development of green building was limited by the issue of expensive investment. Actually, green building can reduce the energy usage inside the building especially in utilization of cooling system. External load plays major role in reducing the usage of cooling system. External load is affected by type of wall sheathing, glass and roof. The proper selection of wall, type of glass and roof material are very important to reduce external load. Hence, the optimization of energy efficiency and conservation in green building design is required. Since this optimization consist of integer and non-linear equations, this problem falls into Mixed-Integer-Non-Linear-Programming (MINLP) that required global optimization technique such as stochastic optimization algorithms. In this paper the optimized variables i.e. type of glass and roof were chosen using Duelist, Killer-Whale and Rain-Water Algorithms to obtain the optimum energy and considering the minimal investment. The optimization results exhibited the single glass Planibel-G with the 3.2 mm thickness and glass wool insulation provided maximum ROI of 36.8486%, EUI reduction of 54 kWh/m2·year, CO2 emission reduction of 486.8971 tons/year and reduce investment of 4,078,905,465 IDR.

The Grover energy transfer algorithm for relativistic speeds

International Nuclear Information System (INIS)

Garcia-Escartin, Juan Carlos; Chamorro-Posada, Pedro

2010-01-01

Grover's algorithm for quantum search can also be applied to classical energy transfer. The procedure takes a system in which the total energy is equally distributed among N subsystems and transfers most of it to one marked subsystem. We show that in a relativistic setting the efficiency of this procedure can be improved. We will consider the transfer of relativistic kinetic energy in a series of elastic collisions. In this case, the number of steps of the energy transfer procedure approaches 1 as the initial velocities of the objects become closer to the speed of light. This is a consequence of introducing nonlinearities in the procedure. However, the maximum attainable transfer will depend on the particular combination of speed and number of objects. In the procedure, we will use N elements, as in the classical non-relativistic case, instead of the log 2 (N) states of the quantum algorithm.

A Biologically Inspired Energy-Efficient Duty Cycle Design Method for Wireless Sensor Networks

Directory of Open Access Journals (Sweden)

Jie Zhou

2017-01-01

Full Text Available The recent success of emerging wireless sensor networks technology has encouraged researchers to develop new energy-efficient duty cycle design algorithm in this field. The energy-efficient duty cycle design problem is a typical NP-hard combinatorial optimization problem. In this paper, we investigate an improved elite immune evolutionary algorithm (IEIEA strategy to optimize energy-efficient duty cycle design scheme and monitored area jointly to enhance the network lifetimes. Simulation results show that the network lifetime of the proposed IEIEA method increased compared to the other two methods, which means that the proposed method improves the full coverage constraints.

Energy-Efficient Resource and Power Allocation for Underlay Multicast Device-to-Device Transmission

Directory of Open Access Journals (Sweden)

Fan Jiang

2017-11-01

Full Text Available In this paper, we present an energy-efficient resource allocation and power control scheme for D2D (Device-to-Device multicasting transmission. The objective is to maximize the overall energy-efficiency of D2D multicast clusters through effective resource allocation and power control schemes, while considering the quality of service (QoS requirements of both cellular users (CUs and D2D clusters. We first build the optimization model and a heuristic resource and power allocation algorithm is then proposed to solve the energy-efficiency problem with less computational complexity. Numerical results indicate that the proposed algorithm outperforms existing schemes in terms of throughput per energy consumption.

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.

The Grover energy transfer algorithm for relativistic speeds

Energy Technology Data Exchange (ETDEWEB)

Garcia-Escartin, Juan Carlos; Chamorro-Posada, Pedro, E-mail: juagar@yllera.tel.uva.e [Dpto. de TeorIa de la Senal y Comunicaciones e Ingenieria Telematica, Universidad de Valladolid, ETSI de Telecomunicacion, Campus Miguel Delibes, Paseo Belen 15, 47011 Valladolid (Spain)

2010-11-12

Grover's algorithm for quantum search can also be applied to classical energy transfer. The procedure takes a system in which the total energy is equally distributed among N subsystems and transfers most of it to one marked subsystem. We show that in a relativistic setting the efficiency of this procedure can be improved. We will consider the transfer of relativistic kinetic energy in a series of elastic collisions. In this case, the number of steps of the energy transfer procedure approaches 1 as the initial velocities of the objects become closer to the speed of light. This is a consequence of introducing nonlinearities in the procedure. However, the maximum attainable transfer will depend on the particular combination of speed and number of objects. In the procedure, we will use N elements, as in the classical non-relativistic case, instead of the log{sub 2}(N) states of the quantum algorithm.

An Efficient Biometric-Based Algorithm Using Heart Rate Variability for Securing Body Sensor Networks.

Science.gov (United States)

Pirbhulal, Sandeep; Zhang, Heye; Mukhopadhyay, Subhas Chandra; Li, Chunyue; Wang, Yumei; Li, Guanglin; Wu, Wanqing; Zhang, Yuan-Ting

2015-06-26

Body Sensor Network (BSN) is a network of several associated sensor nodes on, inside or around the human body to monitor vital signals, such as, Electroencephalogram (EEG), Photoplethysmography (PPG), Electrocardiogram (ECG), etc. Each sensor node in BSN delivers major information; therefore, it is very significant to provide data confidentiality and security. All existing approaches to secure BSN are based on complex cryptographic key generation procedures, which not only demands high resource utilization and computation time, but also consumes large amount of energy, power and memory during data transmission. However, it is indispensable to put forward energy efficient and computationally less complex authentication technique for BSN. In this paper, a novel biometric-based algorithm is proposed, which utilizes Heart Rate Variability (HRV) for simple key generation process to secure BSN. Our proposed algorithm is compared with three data authentication techniques, namely Physiological Signal based Key Agreement (PSKA), Data Encryption Standard (DES) and Rivest Shamir Adleman (RSA). Simulation is performed in Matlab and results suggest that proposed algorithm is quite efficient in terms of transmission time utilization, average remaining energy and total power consumption.

DESIGN OF ENERGY EFFICIENT ROUTING ALGORITHM FOR WIRELESS SENSOR NETWORK (WSN) USING PASCAL GRAPH

OpenAIRE

Deepali Panwar; Subhrendu Guha Neogi

2013-01-01

Development of energy efficient Wireless Sensor Network (WSN) routing protocol is nowadays main area of interest amongst researchers. This research is an effort in designing energy efficient Wireless Sensor Network (WSN) routing protocol under certain parameters consideration. Research report discusses various existing WSN routing protocols and propose a new WSN energy efficient routing protocol. Results show a significant improvement in life cycle of the nodes and enhancement ...

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.

An efficient macro-cell placement algorithm

NARCIS (Netherlands)

Aarts, E.H.L.; Bont, de F.M.J.; Korst, J.H.M.; Rongen, J.M.J.

1991-01-01

A new approximation algorithm is presented for the efficient handling of large macro-cell placement problems. The algorithm combines simulated annealing with new features based on a hierarchical approach and a divide-and-conquer technique. Numerical results show that these features can lead to a

Transmission Power and Antenna Allocation for Energy-Efficient RF Energy Harvesting Networks with Massive MIMO

Directory of Open Access Journals (Sweden)

Yu Min Hwang

2017-06-01

Full Text Available The optimum transmission strategy for maximizing energy efficiency (EE of a multi-user massive multiple-input multiple-output (MIMO system in radio frequency energy harvesting networks is investigated. We focus on dynamic time-switching (TS antennas, to avoid the practical problems of power-splitting antennas, such as complex architectures, power loss and signal distortion when splitting the power of the received signal into power for information decoding (ID and energy harvesting (EH. However, since a single TS antenna cannot serve ID and EH simultaneously, the MIMO system is considered in this paper. We thus formulate an EE optimization problem and propose an iterative algorithm as a tractable solution, including an antenna selection strategy to optimally switch each TS antenna between ID mode and EH mode using nonlinear fractional programming and the Lagrange dual method. Further, the problem is solved under practical constraints of maximum transmission power and outage probabilities for a minimum amount of harvested power and rate capacity for each user. Simulation results show that the proposed algorithm is more energy-efficient than that of baseline schemes, and demonstrates the trade-off between the required amount of harvested power and energy efficiency.

Energy-Efficient Multicast Transmission for Underlay Device-to-Device Communications: A Social-Aware Perspective

Directory of Open Access Journals (Sweden)

Fan Jiang

2017-01-01

Full Text Available In this paper, by utilizing the social relationships among mobile users, we present a framework of energy-efficient cluster formation and resource allocation for multicast D2D transmission. In particular, we first deal with D2D multicast cluster/group formation strategy from both physical distance and social trust level. Then we aim to maximize the overall energy-efficiency of D2D multicast groups through resource allocation and power control scheme, which considers the quality-of-service (QoS requirements of both cellular user equipment and D2D groups. A heuristic algorithm is proposed to solve above energy-efficiency problem with less complexity. After that, considering the limited battery capacity of mobile users, we propose an energy and social aware cluster head update algorithm, which incorporates both the energy constraint and social centrality measurement. Numerical results indicate that the proposed social-tie based D2D multicast group formation and update algorithm form a multicast group in an energy efficient way. Moreover, the proposed resource and power allocation scheme achieves better energy efficiency in terms of throughput per energy consumption. These results show that, by exploiting social domain information, underlay D2D multicast transmission has high practical potential in saving the source on wireless links and in the backhaul.

An Energy-Efficient Target-Tracking Strategy for Mobile Sensor Networks.

Science.gov (United States)

Mahboubi, Hamid; Masoudimansour, Walid; Aghdam, Amir G; Sayrafian-Pour, Kamran

2017-02-01

In this paper, an energy-efficient strategy is proposed for tracking a moving target in an environment with obstacles, using a network of mobile sensors. Typically, the most dominant sources of energy consumption in a mobile sensor network are sensing, communication, and movement. The proposed algorithm first divides the field into a grid of sufficiently small cells. The grid is then represented by a graph whose edges are properly weighted to reflect the energy consumption of sensors. The proposed technique searches for near-optimal locations for the sensors in different time instants to route information from the target to destination, using a shortest path algorithm. Simulations confirm the efficacy of the proposed algorithm.

A Novel Algorithm for Efficient Downlink Packet Scheduling for Multiple-Component-Carrier Cellular Systems

Directory of Open Access Journals (Sweden)

Yao-Liang Chung

2016-11-01

Full Text Available The simultaneous aggregation of multiple component carriers (CCs for use by a base station constitutes one of the more promising strategies for providing substantially enhanced bandwidths for packet transmissions in 4th and 5th generation cellular systems. To the best of our knowledge, however, few previous studies have undertaken a thorough investigation of various performance aspects of the use of a simple yet effective packet scheduling algorithm in which multiple CCs are aggregated for transmission in such systems. Consequently, the present study presents an efficient packet scheduling algorithm designed on the basis of the proportional fair criterion for use in multiple-CC systems for downlink transmission. The proposed algorithm includes a focus on providing simultaneous transmission support for both real-time (RT and non-RT traffic. This algorithm can, when applied with sufficiently efficient designs, provide adequate utilization of spectrum resources for the purposes of transmissions, while also improving energy efficiency to some extent. According to simulation results, the performance of the proposed algorithm in terms of system throughput, mean delay, and fairness constitute substantial improvements over those of an algorithm in which the CCs are used independently instead of being aggregated.

M4GB : Efficient Groebner Basis algorithm

NARCIS (Netherlands)

R.H. Makarim (Rusydi); M.M.J. Stevens (Marc)

2017-01-01

textabstractWe introduce a new efficient algorithm for computing Groebner-bases named M4GB. Like Faugere's algorithm F4 it is an extension of Buchberger's algorithm that describes: how to store already computed (tail-)reduced multiples of basis polynomials to prevent redundant work in the reduction

Energy-Efficient Deadline-Aware Data-Gathering Scheme Using Multiple Mobile Data Collectors.

Science.gov (United States)

Dasgupta, Rumpa; Yoon, Seokhoon

2017-04-01

In wireless sensor networks, the data collected by sensors are usually forwarded to the sink through multi-hop forwarding. However, multi-hop forwarding can be inefficient due to the energy hole problem and high communications overhead. Moreover, when the monitored area is large and the number of sensors is small, sensors cannot send the data via multi-hop forwarding due to the lack of network connectivity. In order to address those problems of multi-hop forwarding, in this paper, we consider a data collection scheme that uses mobile data collectors (MDCs), which visit sensors and collect data from them. Due to the recent breakthroughs in wireless power transfer technology, MDCs can also be used to recharge the sensors to keep them from draining their energy. In MDC-based data-gathering schemes, a big challenge is how to find the MDCs' traveling paths in a balanced way, such that their energy consumption is minimized and the packet-delay constraint is satisfied. Therefore, in this paper, we aim at finding the MDCs' paths, taking energy efficiency and delay constraints into account. We first define an optimization problem, named the delay-constrained energy minimization (DCEM) problem, to find the paths for MDCs. An integer linear programming problem is formulated to find the optimal solution. We also propose a two-phase path-selection algorithm to efficiently solve the DCEM problem. Simulations are performed to compare the performance of the proposed algorithms with two heuristics algorithms for the vehicle routing problem under various scenarios. The simulation results show that the proposed algorithms can outperform existing algorithms in terms of energy efficiency and packet delay.

A practical algorithm for distribution state estimation including renewable energy sources

Energy Technology Data Exchange (ETDEWEB)

Niknam, Taher [Electronic and Electrical Department, Shiraz University of Technology, Modares Blvd., P.O. 71555-313, Shiraz (Iran); Firouzi, Bahman Bahmani [Islamic Azad University Marvdasht Branch, Marvdasht (Iran)

2009-11-15

Renewable energy is energy that is in continuous supply over time. These kinds of energy sources are divided into five principal renewable sources of energy: the sun, the wind, flowing water, biomass and heat from within the earth. According to some studies carried out by the research institutes, about 25% of the new generation will be generated by Renewable Energy Sources (RESs) in the near future. Therefore, it is necessary to study the impact of RESs on the power systems, especially on the distribution networks. This paper presents a practical Distribution State Estimation (DSE) including RESs and some practical consideration. The proposed algorithm is based on the combination of Nelder-Mead simplex search and Particle Swarm Optimization (PSO) algorithms, called PSO-NM. The proposed algorithm can estimate load and RES output values by Weighted Least-Square (WLS) approach. Some practical considerations are var compensators, Voltage Regulators (VRs), Under Load Tap Changer (ULTC) transformer modeling, which usually have nonlinear and discrete characteristics, and unbalanced three-phase power flow equations. The comparison results with other evolutionary optimization algorithms such as original PSO, Honey Bee Mating Optimization (HBMO), Neural Networks (NNs), Ant Colony Optimization (ACO), and Genetic Algorithm (GA) for a test system demonstrate that PSO-NM is extremely effective and efficient for the DSE problems. (author)

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

Directory of Open Access Journals (Sweden)

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%.

A maximum power point tracking algorithm for buoy-rope-drum wave energy converters

Science.gov (United States)

Wang, J. Q.; Zhang, X. C.; Zhou, Y.; Cui, Z. C.; Zhu, L. S.

2016-08-01

The maximum power point tracking control is the key link to improve the energy conversion efficiency of wave energy converters (WEC). This paper presents a novel variable step size Perturb and Observe maximum power point tracking algorithm with a power classification standard for control of a buoy-rope-drum WEC. The algorithm and simulation model of the buoy-rope-drum WEC are presented in details, as well as simulation experiment results. The results show that the algorithm tracks the maximum power point of the WEC fast and accurately.

An Efficient Biometric-Based Algorithm Using Heart Rate Variability for Securing Body Sensor Networks

Directory of Open Access Journals (Sweden)

Sandeep Pirbhulal

2015-06-01

Full Text Available Body Sensor Network (BSN is a network of several associated sensor nodes on, inside or around the human body to monitor vital signals, such as, Electroencephalogram (EEG, Photoplethysmography (PPG, Electrocardiogram (ECG, etc. Each sensor node in BSN delivers major information; therefore, it is very significant to provide data confidentiality and security. All existing approaches to secure BSN are based on complex cryptographic key generation procedures, which not only demands high resource utilization and computation time, but also consumes large amount of energy, power and memory during data transmission. However, it is indispensable to put forward energy efficient and computationally less complex authentication technique for BSN. In this paper, a novel biometric-based algorithm is proposed, which utilizes Heart Rate Variability (HRV for simple key generation process to secure BSN. Our proposed algorithm is compared with three data authentication techniques, namely Physiological Signal based Key Agreement (PSKA, Data Encryption Standard (DES and Rivest Shamir Adleman (RSA. Simulation is performed in Matlab and results suggest that proposed algorithm is quite efficient in terms of transmission time utilization, average remaining energy and total power consumption.

An Efficient Biometric-Based Algorithm Using Heart Rate Variability for Securing Body Sensor Networks

Science.gov (United States)

Pirbhulal, Sandeep; Zhang, Heye; Mukhopadhyay, Subhas Chandra; Li, Chunyue; Wang, Yumei; Li, Guanglin; Wu, Wanqing; Zhang, Yuan-Ting

2015-01-01

Body Sensor Network (BSN) is a network of several associated sensor nodes on, inside or around the human body to monitor vital signals, such as, Electroencephalogram (EEG), Photoplethysmography (PPG), Electrocardiogram (ECG), etc. Each sensor node in BSN delivers major information; therefore, it is very significant to provide data confidentiality and security. All existing approaches to secure BSN are based on complex cryptographic key generation procedures, which not only demands high resource utilization and computation time, but also consumes large amount of energy, power and memory during data transmission. However, it is indispensable to put forward energy efficient and computationally less complex authentication technique for BSN. In this paper, a novel biometric-based algorithm is proposed, which utilizes Heart Rate Variability (HRV) for simple key generation process to secure BSN. Our proposed algorithm is compared with three data authentication techniques, namely Physiological Signal based Key Agreement (PSKA), Data Encryption Standard (DES) and Rivest Shamir Adleman (RSA). Simulation is performed in Matlab and results suggest that proposed algorithm is quite efficient in terms of transmission time utilization, average remaining energy and total power consumption. PMID:26131666

A new home energy management algorithm with voltage control in a smart home environment

International Nuclear Information System (INIS)

Elma, Onur; Selamogullari, Ugur Savas

2015-01-01

Energy management in electrical systems is one of the important issues for energy efficiency and future grid systems. Energy management is defined as a HEM (home energy management) on the residential consumer side. The HEM system plays a key role in residential demand response applications. In this study, a new HEM algorithm is proposed for smart home environments to reduce peak demand and increase the energy efficiency. The proposed algorithm includes VC (voltage control) methodology to reduce the power consumption of residential appliances so that the shifting of appliances is minimized. The results of the survey are used to produce representative load profiles for a weekday and for a weekend. Then, case studies are completed to test the proposed HEM algorithm in reducing the peak demand in the house. The main aim of the proposed HEM algorithm is to minimize the number of turned-off appliances to decrease demand so that the customer comfort is maximized. The smart home laboratory at Yildiz Technical University, Istanbul, Turkey is used in case studies. Experimental results show that the proposed HEM algorithm reduces the peak demand by 17.5% with the voltage control and by 38% with both the voltage control and the appliance shifting. - Highlights: • A new HEM (home energy management) algorithm is proposed. • Voltage control in the HEM is introduced as a solution for peak load reduction. • Customer comfort is maximized by minimizing the number of turned-off appliances. • The proposed HEM algorithm is experimentally validated at a smart home laboratory. • A survey is completed to produce typical load profiles of a Turkish family.

Energy and Delay Optimization of Heterogeneous Multicore Wireless Multimedia Sensor Nodes by Adaptive Genetic-Simulated Annealing Algorithm

Directory of Open Access Journals (Sweden)

Xing Liu

2018-01-01

Full Text Available Energy efficiency and delay optimization are significant for the proliferation of wireless multimedia sensor network (WMSN. In this article, an energy-efficient, delay-efficient, hardware and software cooptimization platform is researched to minimize the energy cost while guaranteeing the deadline of the real-time WMSN tasks. First, a multicore reconfigurable WMSN hardware platform is designed and implemented. This platform uses both the heterogeneous multicore architecture and the dynamic voltage and frequency scaling (DVFS technique. By this means, the nodes can adjust the hardware characteristics dynamically in terms of the software run-time contexts. Consequently, the software can be executed more efficiently with less energy cost and shorter execution time. Then, based on this hardware platform, an energy and delay multiobjective optimization algorithm and a DVFS adaption algorithm are investigated. These algorithms aim to search out the global energy optimization solution within the acceptable calculation time and strip the time redundancy in the task executing process. Thus, the energy efficiency of the WMSN node can be improved significantly even under strict constraint of the execution time. Simulation and real-world experiments proved that the proposed approaches can decrease the energy cost by more than 29% compared to the traditional single-core WMSN node. Moreover, the node can react quickly to the time-sensitive events.

Efficient scheduling request algorithm for opportunistic wireless access

KAUST Repository

Nam, Haewoon; Alouini, Mohamed-Slim

2011-01-01

An efficient scheduling request algorithm for opportunistic wireless access based on user grouping is proposed in this paper. Similar to the well-known opportunistic splitting algorithm, the proposed algorithm initially adjusts (or lowers

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.

On the efficiency of chaos optimization algorithms for global optimization

International Nuclear Information System (INIS)

Yang Dixiong; Li Gang; Cheng Gengdong

2007-01-01

Chaos optimization algorithms as a novel method of global optimization have attracted much attention, which were all based on Logistic map. However, we have noticed that the probability density function of the chaotic sequences derived from Logistic map is a Chebyshev-type one, which may affect the global searching capacity and computational efficiency of chaos optimization algorithms considerably. Considering the statistical property of the chaotic sequences of Logistic map and Kent map, the improved hybrid chaos-BFGS optimization algorithm and the Kent map based hybrid chaos-BFGS algorithm are proposed. Five typical nonlinear functions with multimodal characteristic are tested to compare the performance of five hybrid optimization algorithms, which are the conventional Logistic map based chaos-BFGS algorithm, improved Logistic map based chaos-BFGS algorithm, Kent map based chaos-BFGS algorithm, Monte Carlo-BFGS algorithm, mesh-BFGS algorithm. The computational performance of the five algorithms is compared, and the numerical results make us question the high efficiency of the chaos optimization algorithms claimed in some references. It is concluded that the efficiency of the hybrid optimization algorithms is influenced by the statistical property of chaotic/stochastic sequences generated from chaotic/stochastic algorithms, and the location of the global optimum of nonlinear functions. In addition, it is inappropriate to advocate the high efficiency of the global optimization algorithms only depending on several numerical examples of low-dimensional functions

An Efficient Algorithm for Unconstrained Optimization

Directory of Open Access Journals (Sweden)

Sergio Gerardo de-los-Cobos-Silva

2015-01-01

Full Text Available This paper presents an original and efficient PSO algorithm, which is divided into three phases: (1 stabilization, (2 breadth-first search, and (3 depth-first search. The proposed algorithm, called PSO-3P, was tested with 47 benchmark continuous unconstrained optimization problems, on a total of 82 instances. The numerical results show that the proposed algorithm is able to reach the global optimum. This work mainly focuses on unconstrained optimization problems from 2 to 1,000 variables.

Energy-Efficient Power Allocation for MIMO-SVD Systems

KAUST Repository

Sboui, Lokman

2017-05-24

In this paper, we address the problem of energyefficient power allocation in MIMO systems. In fact, the widely adopted water-filling power allocation does not ensure the maximization of the energy efficiency (EE). Since the EE maximization is a non-convex problem, numerical methods based on fractional programming were introduced to find the optimal power solutions. In this paper, we present a novel and simple power allocation scheme based on the explicit expressions of the optimal power. We also present a low-complexity algorithm that complements the proposed scheme for low circuit-power regime. Furthermore, we analyze power-constrained and rate-constrained systems and present the corresponding optimal power control. In the numerical results, we show that the presented analytical expressions are accurate and that the algorithm converges within two iterations. We also show that as the number of antenna increases, the system becomes more energy-efficient. Also, a saturation of the EE is observed at high power budget and low minimal rate regimes.

Efficient Implementation Algorithms for Homogenized Energy Models

National Research Council Canada - National Science Library

Braun, Thomas R; Smith, Ralph C

2005-01-01

... for real-time control implementation. In this paper, we develop algorithms employing lookup tables which permit the high speed implementation of formulations which incorporate relaxation mechanisms and electromechanical coupling...

Energy efficiency resource modeling in generation expansion planning

International Nuclear Information System (INIS)

Ghaderi, A.; Parsa Moghaddam, M.; Sheikh-El-Eslami, M.K.

2014-01-01

Energy efficiency plays an important role in mitigating energy security risks and emission problems. In this paper, energy efficiency resources are modeled as efficiency power plants (EPP) to evaluate their impacts on generation expansion planning (GEP). The supply curve of EPP is proposed using the production function of electricity consumption. A decision making framework is also presented to include EPP in GEP problem from an investor's point of view. The revenue of EPP investor is obtained from energy cost reduction of consumers and does not earn any income from electricity market. In each stage of GEP, a bi-level model for operation problem is suggested: the upper-level represents profit maximization of EPP investor and the lower-level corresponds to maximize the social welfare. To solve the bi-level problem, a fixed-point iteration algorithm is used known as diagonalization method. Energy efficiency feed-in tariff is investigated as a regulatory support scheme to encourage the investor. Results pertaining to a case study are simulated and discussed. - Highlights: • An economic model for energy efficiency programs is presented. • A framework is provided to model energy efficiency resources in GEP problem. • FIT is investigated as a regulatory support scheme to encourage the EPP investor. • The capacity expansion is delayed and reduced with considering EPP in GEP. • FIT-II can more effectively increase the energy saving compared to FIT-I

Energy efficiency

International Nuclear Information System (INIS)

2010-01-01

After a speech of the CEA's (Commissariat a l'Energie Atomique) general administrator about energy efficiency as a first rank challenge for the planet and for France, this publications proposes several contributions: a discussion of the efficiency of nuclear energy, an economic analysis of R and D's value in the field of fourth generation fast reactors, discussions about biofuels and the relationship between energy efficiency and economic competitiveness, and a discussion about solar photovoltaic efficiency

Energy Efficient Design for Two-Way AF Relay Networks

Directory of Open Access Journals (Sweden)

Yong Li

2014-01-01

Full Text Available Conventional designs on two-way relay networks mainly focus on the spectral efficiency (SE rather than energy efficiency (EE. In this paper, we consider a system where two source nodes communicate with each other via an amplify-and-forward (AF relay node and study the power allocation schemes to maximize EE while ensuring a certain data rate. We propose an optimal energy-efficient power allocation algorithm based on iterative search technique. In addition, a closed-form suboptimal solution is derived with reduced complexity and negligible performance degradation. Numerical results show that the proposed schemes can achieve considerable EE improvement compared with conventional designs.

Algorithm of Energy Efficiency Improvement for Intelligent Devices in Railway Transport

Directory of Open Access Journals (Sweden)

Beinaroviča Anna

2016-07-01

Full Text Available The present paper deals with the use of systems and devices with artificial intelligence in the motor vehicle driving. The main objective of transport operations is a transportation planning with minimum energy consumption. There are various methods for energy saving, and the paper discusses one of them – proper planning of transport operations. To gain proper planning it is necessary to involve the system and devices with artificial intelligence. They will display possible developments in the choice of one or another transport plan. Consequently, it can be supposed how much the plan is effective against the spent energy. The intelligent device considered in this paper consists of an algorithm, a database, and the internet for the connection to other intelligent devices. The main task of the target function is to minimize the total downtime at intermediate stations. A specific unique PHP-based computer model was created. It uses the MySQL database for simulation data storage and processing. Conclusions based on the experiments were made. The experiments showed that after optimization, a train can pass intermediate stations without making multiple stops breaking and accelerating, which leads to decreased energy consumption.

Prior-knowledge-independent equalization to improve battery uniformity with energy efficiency and time efficiency for lithium-ion battery

International Nuclear Information System (INIS)

Zhang, Shumei; Qiang, Jiaxi; Yang, Lin; Zhao, Xiaowei

2016-01-01

To improve battery uniformity as well as energy efficiency and time efficiency, a SOC (state of charge)-based equalization by AGA (adaptive genetic algorithm) is proposed on basis of two-stage DC/DC converters. The simulation results indicate that compared with FLC (fuzzy logic controller) equalization, the standard deviation of final SOC is improved by 78.7% while energy efficiency is improved by 6.01% and equalization time is decreased by 20% for AGA equalization of extreme dispersion. Additionally, AGA improves the battery uniformity by 30.77% with shortening equalization time by 16.29% and saving energy loss by 1.51% compared with FLC for equalization of regular dispersion. For further validation, the equalization optimization is verified by experiment based on the data-driven parameter identification method which is used to enhance the real-time capability of AGA. For AGA equalization of extreme dispersion, the standard deviation of final SOC is just 0.41% while equalization time prolongs only 14 min and energy efficiency is decreased by 0.81% compared with simulation results. Moreover, not only the standard deviation of final SOC is just 0.28% but also the energy efficiency is decreased by 0.69% and equalization time prolongs by 10.4 min compared with the simulation results for equalization of regular dispersion. - Highlights: • Issues of over equalization, time consumption and energy loss are addressed. • A SOC-based equalization is proposed based on adaptive genetic algorithm. • The equalization aims to improve battery uniformity, efficiency of energy and time. • Data-driven parameter identification is used to enhance the real-time capability.

Rigorous RG Algorithms and Area Laws for Low Energy Eigenstates in 1D

Science.gov (United States)

Arad, Itai; Landau, Zeph; Vazirani, Umesh; Vidick, Thomas

2017-11-01

One of the central challenges in the study of quantum many-body systems is the complexity of simulating them on a classical computer. A recent advance (Landau et al. in Nat Phys, 2015) gave a polynomial time algorithm to compute a succinct classical description for unique ground states of gapped 1D quantum systems. Despite this progress many questions remained unsolved, including whether there exist efficient algorithms when the ground space is degenerate (and of polynomial dimension in the system size), or for the polynomially many lowest energy states, or even whether such states admit succinct classical descriptions or area laws. In this paper we give a new algorithm, based on a rigorously justified RG type transformation, for finding low energy states for 1D Hamiltonians acting on a chain of n particles. In the process we resolve some of the aforementioned open questions, including giving a polynomial time algorithm for poly( n) degenerate ground spaces and an n O(log n) algorithm for the poly( n) lowest energy states (under a mild density condition). For these classes of systems the existence of a succinct classical description and area laws were not rigorously proved before this work. The algorithms are natural and efficient, and for the case of finding unique ground states for frustration-free Hamiltonians the running time is {\\tilde{O}(nM(n))} , where M( n) is the time required to multiply two n × n matrices.

A subzone reconstruction algorithm for efficient staggered compatible remapping

Energy Technology Data Exchange (ETDEWEB)

Starinshak, D.P., E-mail: starinshak1@llnl.gov; Owen, J.M., E-mail: mikeowen@llnl.gov

2015-09-01

Staggered-grid Lagrangian hydrodynamics algorithms frequently make use of subzonal discretization of state variables for the purposes of improved numerical accuracy, generality to unstructured meshes, and exact conservation of mass, momentum, and energy. For Arbitrary Lagrangian–Eulerian (ALE) methods using a geometric overlay, it is difficult to remap subzonal variables in an accurate and efficient manner due to the number of subzone–subzone intersections that must be computed. This becomes prohibitive in the case of 3D, unstructured, polyhedral meshes. A new procedure is outlined in this paper to avoid direct subzonal remapping. The new algorithm reconstructs the spatial profile of a subzonal variable using remapped zonal and nodal representations of the data. The reconstruction procedure is cast as an under-constrained optimization problem. Enforcing conservation at each zone and node on the remapped mesh provides the set of equality constraints; the objective function corresponds to a quadratic variation per subzone between the values to be reconstructed and a set of target reference values. Numerical results for various pure-remapping and hydrodynamics tests are provided. Ideas for extending the algorithm to staggered-grid radiation-hydrodynamics are discussed as well as ideas for generalizing the algorithm to include inequality constraints.

Energy-Efficient Fault-Tolerant Dynamic Event Region Detection in Wireless Sensor Networks

DEFF Research Database (Denmark)

Enemark, Hans-Jacob; Zhang, Yue; Dragoni, Nicola

2015-01-01

to a hybrid algorithm for dynamic event region detection, such as real-time tracking of chemical leakage regions. Considering the characteristics of the moving away dynamic events, we propose a return back condition for the hybrid algorithm from distributed neighborhood collaboration, in which a node makes......Fault-tolerant event detection is fundamental to wireless sensor network applications. Existing approaches usually adopt neighborhood collaboration for better detection accuracy, while need more energy consumption due to communication. Focusing on energy efficiency, this paper makes an improvement...... its detection decision based on decisions received from its spatial and temporal neighbors, to local non-communicative decision making. The simulation results demonstrate that the improved algorithm does not degrade the detection accuracy of the original algorithm, while it has better energy...

An Efficient Demand Side Management System with a New Optimized Home Energy Management Controller in Smart Grid

Directory of Open Access Journals (Sweden)

Hafiz Majid Hussain

2018-01-01

Full Text Available The traditional power grid is inadequate to overcome modern day challenges. As the modern era demands the traditional power grid to be more reliable, resilient, and cost-effective, the concept of smart grid evolves and various methods have been developed to overcome these demands which make the smart grid superior over the traditional power grid. One of the essential components of the smart grid, home energy management system (HEMS enhances the energy efficiency of electricity infrastructure in a residential area. In this aspect, we propose an efficient home energy management controller (EHEMC based on genetic harmony search algorithm (GHSA to reduce electricity expense, peak to average ratio (PAR, and maximize user comfort. We consider EHEMC for a single home and multiple homes with real-time electricity pricing (RTEP and critical peak pricing (CPP tariffs. In particular, for multiple homes, we classify modes of operation for the appliances according to their energy consumption with varying operation time slots. The constrained optimization problem is solved using heuristic algorithms: wind-driven optimization (WDO, harmony search algorithm (HSA, genetic algorithm (GA, and proposed algorithm GHSA. The proposed algorithm GHSA shows higher search efficiency and dynamic capability to attain optimal solutions as compared to existing algorithms. Simulation results also show that the proposed algorithm GHSA outperforms the existing algorithms in terms of reduction in electricity cost, PAR, and maximize user comfort.

Efficient RNA structure comparison algorithms.

Science.gov (United States)

Arslan, Abdullah N; Anandan, Jithendar; Fry, Eric; Monschke, Keith; Ganneboina, Nitin; Bowerman, Jason

2017-12-01

Recently proposed relative addressing-based ([Formula: see text]) RNA secondary structure representation has important features by which an RNA structure database can be stored into a suffix array. A fast substructure search algorithm has been proposed based on binary search on this suffix array. Using this substructure search algorithm, we present a fast algorithm that finds the largest common substructure of given multiple RNA structures in [Formula: see text] format. The multiple RNA structure comparison problem is NP-hard in its general formulation. We introduced a new problem for comparing multiple RNA structures. This problem has more strict similarity definition and objective, and we propose an algorithm that solves this problem efficiently. We also develop another comparison algorithm that iteratively calls this algorithm to locate nonoverlapping large common substructures in compared RNAs. With the new resulting tools, we improved the RNASSAC website (linked from http://faculty.tamuc.edu/aarslan ). This website now also includes two drawing tools: one specialized for preparing RNA substructures that can be used as input by the search tool, and another one for automatically drawing the entire RNA structure from a given structure sequence.

Energy-efficient routing, modulation and spectrum allocation in elastic optical networks

Science.gov (United States)

Tan, Yanxia; Gu, Rentao; Ji, Yuefeng

2017-07-01

With tremendous growth in bandwidth demand, energy consumption problem in elastic optical networks (EONs) becomes a hot topic with wide concern. The sliceable bandwidth-variable transponder in EON, which can transmit/receive multiple optical flows, was recently proposed to improve a transponder's flexibility and save energy. In this paper, energy-efficient routing, modulation and spectrum allocation (EE-RMSA) in EONs with sliceable bandwidth-variable transponder is studied. To decrease the energy consumption, we develop a Mixed Integer Linear Programming (MILP) model with corresponding EE-RMSA algorithm for EONs. The MILP model jointly considers the modulation format and optical grooming in the process of routing and spectrum allocation with the objective of minimizing the energy consumption. With the help of genetic operators, the EE-RMSA algorithm iteratively optimizes the feasible routing path, modulation format and spectrum resources solutions by explore the whole search space. In order to save energy, the optical-layer grooming strategy is designed to transmit the lightpath requests. Finally, simulation results verify that the proposed scheme is able to reduce the energy consumption of the network while maintaining the blocking probability (BP) performance compare with the existing First-Fit-KSP algorithm, Iterative Flipping algorithm and EAMGSP algorithm especially in large network topology. Our results also demonstrate that the proposed EE-RMSA algorithm achieves almost the same performance as MILP on an 8-node network.

An efficient algorithm for bi-objective combined heat and power production planning under the emission trading scheme

International Nuclear Information System (INIS)

Rong, Aiying; Figueira, José Rui; Lahdelma, Risto

2014-01-01

Highlights: • Define fuel mix setting for the bi-objective CHP environmental/economic dispatch. • Develop an efficient algorithm for constructing the Pareto frontier for the problem. • Time complexity analysis is conducted for the proposed algorithm. • The algorithm is theoretically compared against a traditional algorithm. • The efficiency of the algorithm is justified by numerical results. - Abstract: The growing environmental awareness and the apparent conflicts between economic and environmental objectives turn energy planning problems naturally into multi-objective optimization problems. In the current study, mixed fuel combustion is considered as an option to achieve tradeoff between economic objective (associated with fuel cost) and emission objective (measured in CO 2 emission cost according to fuels and emission allowance price) because a fuel with higher emissions is usually cheaper than one with lower emissions. Combined heat and power (CHP) production is an important high-efficiency technology to promote under the emission trading scheme. In CHP production, the production planning of both commodities must be done in coordination. A long-term planning problem decomposes into thousands of hourly subproblems. In this paper, a bi-objective multi-period linear programming CHP planning model is presented first. Then, an efficient specialized merging algorithm for constructing the exact Pareto frontier (PF) of the problem is presented. The algorithm is theoretically and empirically compared against a modified dichotomic search algorithm. The efficiency and effectiveness of the algorithm is justified

Efficient algorithms of multidimensional γ-ray spectra compression

International Nuclear Information System (INIS)

Morhac, M.; Matousek, V.

2006-01-01

The efficient algorithms to compress multidimensional γ-ray events are presented. Two alternative kinds of compression algorithms based on both the adaptive orthogonal and randomizing transforms are proposed. In both algorithms we employ the reduction of data volume due to the symmetry of the γ-ray spectra

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.

Efficient motif finding algorithms for large-alphabet inputs

Directory of Open Access Journals (Sweden)

Pavlovic Vladimir

2010-10-01

Full Text Available Abstract Background We consider the problem of identifying motifs, recurring or conserved patterns, in the biological sequence data sets. To solve this task, we present a new deterministic algorithm for finding patterns that are embedded as exact or inexact instances in all or most of the input strings. Results The proposed algorithm (1 improves search efficiency compared to existing algorithms, and (2 scales well with the size of alphabet. On a synthetic planted DNA motif finding problem our algorithm is over 10× more efficient than MITRA, PMSPrune, and RISOTTO for long motifs. Improvements are orders of magnitude higher in the same setting with large alphabets. On benchmark TF-binding site problems (FNP, CRP, LexA we observed reduction in running time of over 12×, with high detection accuracy. The algorithm was also successful in rapidly identifying protein motifs in Lipocalin, Zinc metallopeptidase, and supersecondary structure motifs for Cadherin and Immunoglobin families. Conclusions Our algorithm reduces computational complexity of the current motif finding algorithms and demonstrate strong running time improvements over existing exact algorithms, especially in important and difficult cases of large-alphabet sequences.

Joint Optimized CPU and Networking Control Scheme for Improved Energy Efficiency in Video Streaming on Mobile Devices

Directory of Open Access Journals (Sweden)

Sung-Woong Jo

2017-01-01

Full Text Available Video streaming service is one of the most popular applications for mobile users. However, mobile video streaming services consume a lot of energy, resulting in a reduced battery life. This is a critical problem that results in a degraded user’s quality of experience (QoE. Therefore, in this paper, a joint optimization scheme that controls both the central processing unit (CPU and wireless networking of the video streaming process for improved energy efficiency on mobile devices is proposed. For this purpose, the energy consumption of the network interface and CPU is analyzed, and based on the energy consumption profile a joint optimization problem is formulated to maximize the energy efficiency of the mobile device. The proposed algorithm adaptively adjusts the number of chunks to be downloaded and decoded in each packet. Simulation results show that the proposed algorithm can effectively improve the energy efficiency when compared with the existing algorithms.

Energy-Efficient Neuromorphic Classifiers.

Science.gov (United States)

Martí, Daniel; Rigotti, Mattia; Seok, Mingoo; Fusi, Stefano

2016-10-01

Neuromorphic engineering combines the architectural and computational principles of systems neuroscience with semiconductor electronics, with the aim of building efficient and compact devices that mimic the synaptic and neural machinery of the brain. The energy consumptions promised by neuromorphic engineering are extremely low, comparable to those of the nervous system. Until now, however, the neuromorphic approach has been restricted to relatively simple circuits and specialized functions, thereby obfuscating a direct comparison of their energy consumption to that used by conventional von Neumann digital machines solving real-world tasks. Here we show that a recent technology developed by IBM can be leveraged to realize neuromorphic circuits that operate as classifiers of complex real-world stimuli. Specifically, we provide a set of general prescriptions to enable the practical implementation of neural architectures that compete with state-of-the-art classifiers. We also show that the energy consumption of these architectures, realized on the IBM chip, is typically two or more orders of magnitude lower than that of conventional digital machines implementing classifiers with comparable performance. Moreover, the spike-based dynamics display a trade-off between integration time and accuracy, which naturally translates into algorithms that can be flexibly deployed for either fast and approximate classifications, or more accurate classifications at the mere expense of longer running times and higher energy costs. This work finally proves that the neuromorphic approach can be efficiently used in real-world applications and has significant advantages over conventional digital devices when energy consumption is considered.

Energy efficiency analysis for flexible-grid OFDM-based optical networks

DEFF Research Database (Denmark)

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

2012-01-01

As the Internet traffic grows, the energy efficiency gains more attention as a design factor for the planning and operation of telecommunication networks. This paper is devoted to the study of energy efficiency in optical transport networks, comparing the performance of an innovative flexible......-grid network based on Orthogonal Frequency Division Multiplexing (OFDM) with that of conventional fixed-grid Wavelength Division Multiplexing (WDM) networks with a Single Line Rate (SLR) and with a Mixed Line Rate (MLR) operation. The power consumption values of the network elements are introduced. Energy......-aware heuristic algorithms are proposed for the resource allocation both in static (offline) and dynamic (online) scenarios with time-varying demands for the Elastic-bandwidth OFDM-based network and the WDM networks (with SLR and MLR). The energy efficiency performance of the two network technologies under...

Software Cuts Homebuilding Costs, Increases Energy Efficiency

Science.gov (United States)

2015-01-01

To sort out the best combinations of technologies for a crewed mission to Mars, NASA Headquarters awarded grants to MIT's Department of Aeronautics and Astronautics to develop an algorithm-based software tool that highlights the most reliable and cost-effective options. Utilizing the software, Professor Edward Crawley founded Cambridge, Massachussetts-based Ekotrope, which helps homebuilders choose cost- and energy-efficient floor plans and materials.

Energy Efficiency Plan 2009-2012; Energie Efficiency Plan 2009-2012

Energy Technology Data Exchange (ETDEWEB)

Meulen, M.M.W. (ed.)

2009-02-15

The aim of the Energy Efficiency Plan is to give an overview of the energy conservation plans of the Eindhoven University of Technology in Eindhoven, Netherlands, which must result in efficient use of energy conform the long-range agreements between businesses, industry and organizations and the Dutch government to improve energy efficiency (MJA3) [Dutch] Het doel van het EEP (Energie Efficiency Plan) is het in beeld brengen van de energiebesparingsplannen die leiden tot een efficienter gebruik van energie conform de MJA-3 afspraak (de derde Meerjaren Afspraak)

An integrated energy-efficient capacitive sensor digital interface circuit

KAUST Repository

Omran, Hesham

2014-06-19

In this paper, we propose an energy-efficient 13-bit capacitive sensor interface circuit. The proposed design fully relies on successive approximation algorithm, which eliminates the need for oversampling and digital decimation filtering, and thus low-power consumption is achieved. The proposed architecture employs a charge amplifier stage to acheive parasitic insensitive operation and fine absolute resolution. Moreover, the output code is not affected by offset voltages or charge injection. The successive approximation algorithm is implemented in the capacitance-domain using a coarse-fine programmable capacitor array, which allows digitizing wide capacitance range in compact area. Analysis for the maximum achievable resolution due to mismatch is provided. The proposed design is insensitive to any reference voltage or current which translates to low temperature sensitivity. The operation of a prototype fabricated in a standard CMOS technology is experimentally verified using both on-chip and off-chip capacitive sensors. Compared to similar prior work, the fabricated prototype achieves and excellent energy efficiency of 34 pJ/step.

Energy Efficiency Roadmap for Uganda, Making Energy Efficiency Count. Executive Summary

Energy Technology Data Exchange (ETDEWEB)

de la Rue du Can, Stephane; Pudleiner, David; Jones, David; Khan, Aleisha

2017-06-15

Like many countries in Sub-Saharan Africa, Uganda has focused its energy sector investments largely on increasing energy access by increasing energy supply. The links between energy efficiency and energy access, the importance of energy efficiency in new energy supply, and the multiple benefits of energy efficiency for the level and quality of energy available, have been largely overlooked. Implementing energy efficiency in parallel with expanding both the electricity grid and new clean energy generation reduces electricity demand and helps optimize the power supply so that it can serve more customers reliably at minimum cost. Ensuring efficient appliances are incorporated into energy access efforts provides improved energy services to customers. Energy efficiency is an important contributor to access to modern energy. This Energy Efficiency Roadmap for Uganda (Roadmap) is a response to the important role that electrical energy efficiency can play in meeting Uganda’s energy goals. Power Africa and the United Nations Sustainable Energy for All (SEforALL) initiatives collaborated with more than 24 stakeholders in Uganda to develop this document. The document estimates that if the most efficient technologies on the market were adopted, 2,224 gigawatt hours could be saved in 2030 across all sectors, representing 31% of the projected load. This translates into 341 megawatts of peak demand reductions, energy access to an additional 6 million rural customers and reduction of carbon dioxide emissions by 10.6 million tonnes in 2030. The Roadmap also finds that 91% of this technical potential is cost-effective, and 47% is achievable under conservative assumptions. The Roadmap prioritizes recommendations for implementing energy efficiency and maximizing benefits to meet the goals and priorities established in Uganda’s 2015 SEforALL Action Agenda. One important step is to create and increase demand for efficiency through long-term enabling policies and financial incentives

Energy efficient sensor nodes placement using Territorial Predator Scent Marking Algorithm (TPSMA)

International Nuclear Information System (INIS)

Abidin, H Z; Din, N M

2013-01-01

The positions of sensor nodes in a Wireless Sensor Network (WSN) must be able to provide maximum coverage with a longer lifetime. This paper proposed a sensor node placement technique that utilizes a new biologically inspired optimization technique that imitates the behavior of territorial predators in marking their territories with their odors known as Territorial Predator Scent Marking Algorithm (TPSMA). The TPSMA deployed in this paper uses the maximum coverage ratio as the objective function. The performance of the proposed technique is then compared with other schemes in terms of uniformity and average energy consumption. Simulation results show that the WSN deployed with the proposed sensor node placement scheme consumes lower energy compared to the other two schemes and is expected to provide longer lifetime.

Energy Storage System Control Algorithm by Operating Target Power to Improve Energy Sustainability of Smart Home

Directory of Open Access Journals (Sweden)

Byeongkwan Kang

2018-01-01

Full Text Available As energy issues are emerging around the world, a variety of smart home technologies aimed at realizing zero energy houses are being introduced. Energy storage system (ESS for smart home energy independence is increasingly gaining interest. However, limitations exist in that most of them are controlled according to time schedules or used in conjunction with photovoltaic (PV generation systems. In consideration of load usage patterns and PV generation of smart home, this study proposes an ESS control algorithm that uses constant energy of energy network while making maximum use of ESS. Constant energy means that the load consumes a certain amount of power under all conditions, which translates to low variability. The proposed algorithm makes a smart home a load of energy network with low uncertainty and complexity. The simulation results show that the optimal ESS operating target power not only makes the smart home use power constantly from the energy network, but also maximizes utilization of the ESS. In addition, since the smart home is a load that uses constant energy, it has the advantage of being able to operate an efficient energy network from the viewpoint of energy providers.

Reserch on energy absorption efficiency in full-duplex multi-user broadcast channel

Directory of Open Access Journals (Sweden)

JIANG Fengju

2015-02-01

Full Text Available This paper studies the user energy scenarios absorption efficiency optimization in multiuser broadcast channel.This paper assumed that the user terminals using full-duplex mode that the user receive uplink energy information and transfer uplink energy at the same time.In this paper,we maximize the minimum user uplink transmit power,when we ensure that each user′s energy absorption efficiency is greater than a threshold value and satisfies the premise of the base station downlink power emission limits.Finally,the simulation results confirm the effectiveness of the proposed algorithm.

An Improved Crow Search Algorithm Applied to Energy Problems

Directory of Open Access Journals (Sweden)

Primitivo Díaz

2018-03-01

Full Text Available The efficient use of energy in electrical systems has become a relevant topic due to its environmental impact. Parameter identification in induction motors and capacitor allocation in distribution networks are two representative problems that have strong implications in the massive use of energy. From an optimization perspective, both problems are considered extremely complex due to their non-linearity, discontinuity, and high multi-modality. These characteristics make difficult to solve them by using standard optimization techniques. On the other hand, metaheuristic methods have been widely used as alternative optimization algorithms to solve complex engineering problems. The Crow Search Algorithm (CSA is a recent metaheuristic method based on the intelligent group behavior of crows. Although CSA presents interesting characteristics, its search strategy presents great difficulties when it faces high multi-modal formulations. In this paper, an improved version of the CSA method is presented to solve complex optimization problems of energy. In the new algorithm, two features of the original CSA are modified: (I the awareness probability (AP and (II the random perturbation. With such adaptations, the new approach preserves solution diversity and improves the convergence to difficult high multi-modal optima. In order to evaluate its performance, the proposed algorithm has been tested in a set of four optimization problems which involve induction motors and distribution networks. The results demonstrate the high performance of the proposed method when it is compared with other popular approaches.

A DISTRIBUTED ENERGY EFFICIENT CLUSTERING ALGORITHM FOR DATA AGGREGATION IN WIRELESS SENSOR NETWORKS

Directory of Open Access Journals (Sweden)

Seyed Mohammad Bagher Musavi Shirazi

2018-06-01

Full Text Available Wireless sensor networks (WSNs are a new generation of networks typically consisting of a large number of inexpensive nodes with wireless communications. The main purpose of these networks is to collect information from the environment for further processing. Nodes in the network have been equipped with limited battery lifetime, so energy saving is one of the major issues in WSNs. If we balance the load among cluster heads and prevent having an extra load on just a few nodes in the network, we can reach longer network lifetime. One solution to control energy consumption and balance the load among nodes is to use clustering techniques. In this paper, we propose a new distributed energy-efficient clustering algorithm for data aggregation in wireless sensor networks, called Distributed Clustering for Data Aggregation (DCDA. In our new approach, an optimal transmission tree is constructed among sensor nodes with a new greedy method. Base station (BS is the root, cluster heads (CHs and relay nodes are intermediate nodes, and other nodes (cluster member nodes are the leaves of this transmission tree. DCDA balances load among CHs in intra-cluster and inter-cluster data communications using different cluster sizes. For efficient inter-cluster communications, some relay nodes will transfer data between CHs. Energy consumption, distance to the base station, and cluster heads’ centric metric are three main adjustment parameters for the cluster heads election. Simulation results show that the proposed protocol leads to the reduction of individual sensor nodes’ energy consumption and prolongs network lifetime, in comparison with other known methods. ABSTRAK: Rangkaian sensor wayarles (WSN adalah rangkaian generasi baru yang terdiri daripada nod-nod murah komunikasi wayarles. Tujuan rangkaian-rangkaian ini adalah bagi mengumpul maklumat sekeliling untuk proses seterusnya. Nod dalam rangkaian ini dilengkapi bateri kurang jangka hayat, jadi simpanan tenaga

An efficient algorithm for incompressible N-phase flows

International Nuclear Information System (INIS)

Dong, S.

2014-01-01

We present an efficient algorithm within the phase field framework for simulating the motion of a mixture of N (N⩾2) immiscible incompressible fluids, with possibly very different physical properties such as densities, viscosities, and pairwise surface tensions. The algorithm employs a physical formulation for the N-phase system that honors the conservations of mass and momentum and the second law of thermodynamics. We present a method for uniquely determining the mixing energy density coefficients involved in the N-phase model based on the pairwise surface tensions among the N fluids. Our numerical algorithm has several attractive properties that make it computationally very efficient: (i) it has completely de-coupled the computations for different flow variables, and has also completely de-coupled the computations for the (N−1) phase field functions; (ii) the algorithm only requires the solution of linear algebraic systems after discretization, and no nonlinear algebraic solve is needed; (iii) for each flow variable the linear algebraic system involves only constant and time-independent coefficient matrices, which can be pre-computed during pre-processing, despite the variable density and variable viscosity of the N-phase mixture; (iv) within a time step the semi-discretized system involves only individual de-coupled Helmholtz-type (including Poisson) equations, despite the strongly-coupled phase–field system of fourth spatial order at the continuum level; (v) the algorithm is suitable for large density contrasts and large viscosity contrasts among the N fluids. Extensive numerical experiments have been presented for several problems involving multiple fluid phases, large density contrasts and large viscosity contrasts. In particular, we compare our simulations with the de Gennes theory, and demonstrate that our method produces physically accurate results for multiple fluid phases. We also demonstrate the significant and sometimes dramatic effects of the

Energy efficient motion control of the electric bus on route

Science.gov (United States)

Kotiev, G. O.; Butarovich, D. O.; Kositsyn, B. B.

2018-02-01

At present, the urgent problem is the reduction of energy costs of urban motor transport. The article proposes a method of solving this problem by developing an energy-efficient law governing the movement of an electric bus along a city route. To solve this problem, an algorithm is developed based on the dynamic programming method. The proposed method allows you to take into account the constraints imposed on the phase coordinates, control action, as well as on the time of the route. In the course of solving the problem, the model of rectilinear motion of an electric bus on a horizontal reference surface is considered, taking into account the assumptions that allow it to be adapted for the implementation of the method. For the formation of a control action in the equations of motion dynamics, an algorithm for changing the traction / braking torque on the wheels of an electric bus is considered, depending on the magnitude of the control parameter and the speed of motion. An optimal phase trajectory was obtained on a selected section of the road for the prototype of an electric bus. The article presents the comparison of simulation results obtained with the optimal energy efficient control law with the results obtained by a test driver. The comparison proved feasibility of the energy efficient control law for the automobile city electric transport.

Computationally efficient optimisation algorithms for WECs arrays

DEFF Research Database (Denmark)

Ferri, Francesco

2017-01-01

In this paper two derivative-free global optimization algorithms are applied for the maximisation of the energy absorbed by wave energy converter (WEC) arrays. Wave energy is a large and mostly untapped source of energy that could have a key role in the future energy mix. The collection of this r...

Energy efficient cross layer design for spectrum sharing systems

KAUST Repository

Alabbasi, Abdulrahman

2016-10-06

We propose a cross layer design that optimizes the energy efficiency of spectrum sharing systems. The energy per good bit (EPG) is considered as an energy efficiency metric. We optimize the secondary user\\'s transmission power and media access frame length to minimize the EPG metric. We protect the primary user transmission via an outage probability constraint. The non-convex targeted problem is optimized by utilizing the generalized convexity theory and verifying the strictly pseudo-convex structure of the problem. Analytical results of the optimal power and frame length are derived. We also used these results in proposing an algorithm, which guarantees the existence of a global optimal solution. Selected numerical results show the improvement of the proposed system compared to other systems. © 2016 IEEE.

Comparing Whole Building Energy Implications of Sidelighting Systems with Alternate Manual Blind Control Algorithms

Directory of Open Access Journals (Sweden)

Christopher Dyke

2015-05-01

Full Text Available Currently, there is no manual blind control guideline used consistently throughout the energy modeling community. This paper identifies and compares five manual blind control algorithms with unique control patterns and reports blind occlusion, rate of change data, and annual building energy consumption. The blind control schemes detailed here represent five reasonable candidates for use in lighting and energy simulation based on difference driving factors. This study was performed on a medium-sized office building using EnergyPlus with the internal daylight harvesting engine. Results show that applying manual blind control algorithms affects the total annual consumption of the building by as much as 12.5% and 11.5% for interior and exterior blinds respectively, compared to the Always Retracted blinds algorithm. Peak demand was also compared showing blind algorithms affected zone load sizing by as much as 9.8%. The alternate algorithms were tested for their impact on American Society of Heating, Refrigeration and Air-Conditioning Engineers (ASHRAE Guideline 14 calibration metrics and all models were found to differ from the original calibrated baseline by more than the recommended ±15% for coefficient of variance of the mean square error (CVRMSE and ±5% for normalized mean bias error (NMBE. The paper recommends that energy modelers use one or more manual blind control algorithms during design stages when making decisions about energy efficiency and other design alternatives.

ERGC: an efficient referential genome compression algorithm.

Science.gov (United States)

Saha, Subrata; Rajasekaran, Sanguthevar

2015-11-01

Genome sequencing has become faster and more affordable. Consequently, the number of available complete genomic sequences is increasing rapidly. As a result, the cost to store, process, analyze and transmit the data is becoming a bottleneck for research and future medical applications. So, the need for devising efficient data compression and data reduction techniques for biological sequencing data is growing by the day. Although there exists a number of standard data compression algorithms, they are not efficient in compressing biological data. These generic algorithms do not exploit some inherent properties of the sequencing data while compressing. To exploit statistical and information-theoretic properties of genomic sequences, we need specialized compression algorithms. Five different next-generation sequencing data compression problems have been identified and studied in the literature. We propose a novel algorithm for one of these problems known as reference-based genome compression. We have done extensive experiments using five real sequencing datasets. The results on real genomes show that our proposed algorithm is indeed competitive and performs better than the best known algorithms for this problem. It achieves compression ratios that are better than those of the currently best performing algorithms. The time to compress and decompress the whole genome is also very promising. The implementations are freely available for non-commercial purposes. They can be downloaded from http://engr.uconn.edu/∼rajasek/ERGC.zip. rajasek@engr.uconn.edu. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Worst-Case Energy Efficiency Maximization in a 5G Massive MIMO-NOMA System.

Science.gov (United States)

Chinnadurai, Sunil; Selvaprabhu, Poongundran; Jeong, Yongchae; Jiang, Xueqin; Lee, Moon Ho

2017-09-18

In this paper, we examine the robust beamforming design to tackle the energy efficiency (EE) maximization problem in a 5G massive multiple-input multiple-output (MIMO)-non-orthogonal multiple access (NOMA) downlink system with imperfect channel state information (CSI) at the base station. A novel joint user pairing and dynamic power allocation (JUPDPA) algorithm is proposed to minimize the inter user interference and also to enhance the fairness between the users. This work assumes imperfect CSI by adding uncertainties to channel matrices with worst-case model, i.e., ellipsoidal uncertainty model (EUM). A fractional non-convex optimization problem is formulated to maximize the EE subject to the transmit power constraints and the minimum rate requirement for the cell edge user. The designed problem is difficult to solve due to its nonlinear fractional objective function. We firstly employ the properties of fractional programming to transform the non-convex problem into its equivalent parametric form. Then, an efficient iterative algorithm is proposed established on the constrained concave-convex procedure (CCCP) that solves and achieves convergence to a stationary point of the above problem. Finally, Dinkelbach's algorithm is employed to determine the maximum energy efficiency. Comprehensive numerical results illustrate that the proposed scheme attains higher worst-case energy efficiency as compared with the existing NOMA schemes and the conventional orthogonal multiple access (OMA) scheme.

Worst-Case Energy Efficiency Maximization in a 5G Massive MIMO-NOMA System

Directory of Open Access Journals (Sweden)

Sunil Chinnadurai

2017-09-01

Full Text Available In this paper, we examine the robust beamforming design to tackle the energy efficiency (EE maximization problem in a 5G massive multiple-input multiple-output (MIMO-non-orthogonal multiple access (NOMA downlink system with imperfect channel state information (CSI at the base station. A novel joint user pairing and dynamic power allocation (JUPDPA algorithm is proposed to minimize the inter user interference and also to enhance the fairness between the users. This work assumes imperfect CSI by adding uncertainties to channel matrices with worst-case model, i.e., ellipsoidal uncertainty model (EUM. A fractional non-convex optimization problem is formulated to maximize the EE subject to the transmit power constraints and the minimum rate requirement for the cell edge user. The designed problem is difficult to solve due to its nonlinear fractional objective function. We firstly employ the properties of fractional programming to transform the non-convex problem into its equivalent parametric form. Then, an efficient iterative algorithm is proposed established on the constrained concave-convex procedure (CCCP that solves and achieves convergence to a stationary point of the above problem. Finally, Dinkelbach’s algorithm is employed to determine the maximum energy efficiency. Comprehensive numerical results illustrate that the proposed scheme attains higher worst-case energy efficiency as compared with the existing NOMA schemes and the conventional orthogonal multiple access (OMA scheme.

Efficient sampling algorithms for Monte Carlo based treatment planning

International Nuclear Information System (INIS)

DeMarco, J.J.; Solberg, T.D.; Chetty, I.; Smathers, J.B.

1998-01-01

Efficient sampling algorithms are necessary for producing a fast Monte Carlo based treatment planning code. This study evaluates several aspects of a photon-based tracking scheme and the effect of optimal sampling algorithms on the efficiency of the code. Four areas were tested: pseudo-random number generation, generalized sampling of a discrete distribution, sampling from the exponential distribution, and delta scattering as applied to photon transport through a heterogeneous simulation geometry. Generalized sampling of a discrete distribution using the cutpoint method can produce speedup gains of one order of magnitude versus conventional sequential sampling. Photon transport modifications based upon the delta scattering method were implemented and compared with a conventional boundary and collision checking algorithm. The delta scattering algorithm is faster by a factor of six versus the conventional algorithm for a boundary size of 5 mm within a heterogeneous geometry. A comparison of portable pseudo-random number algorithms and exponential sampling techniques is also discussed

Energy conservation in Newmark based time integration algorithms

DEFF Research Database (Denmark)

Krenk, Steen

2006-01-01

Energy balance equations are established for the Newmark time integration algorithm, and for the derived algorithms with algorithmic damping introduced via averaging, the so-called a-methods. The energy balance equations form a sequence applicable to: Newmark integration of the undamped equations...... of motion, an extended form including structural damping, and finally the generalized form including structural as well as algorithmic damping. In all three cases the expression for energy, appearing in the balance equation, is the mechanical energy plus some additional terms generated by the discretization...

Energy efficiency through energy audit

International Nuclear Information System (INIS)

Esan, A. A.

2000-08-01

Energy is an essential factor to economic and social development and improved standards of living in developing countries. Nigeria in particular. There is a strong need for greater energy efficiency in every sector of economy in order to reduce costs. enhance competitiveness, conserve energy resources and reduce environmental impacts associated with production, distribution and use of energy. Energy auditing and monitoring has a significant role in any energy management and conservation project. Energy auditing as an important part of industrial energy management on plant level, represents a complex of activities aiming at the efficient use of energy. The activities are undertaken by a team of experts who use a set of measuring instruments to monitor and evaluate all the necessary data to elaborate a package of recommendations on improvements in the field of energy efficiency and possible product quality. The inefficient conversion and use of energy have been identified as a central problem for all developing countries, Nigeria inclusive, since they all consume significantly higher amounts of energy per unit of GDP than OECD countries. This aggravates energy-related environmental problems and is also a burden on domestic resources and foreign exchange. Energy prices have risen drastically in many developing countries, while energy intensities remain high. Price changes alone are not rapidly translating energy efficiency improvements. Identifying and removing the obstacles to greater energy efficiency should be priority for government in developing countries. This is why the Energy Commission, an apex organ of government on Energy matters in all its ramifications is out to encourage relatively low-cost energy audits for the Textile industries - such audits can identify ''good house-keeping's' measures, such as simply process improvements, that reduce energy consumption and operating costs. This will be followed by the training of plant workers/energy managers

Energy Efficient Cooperative Spectrum Sensing in Cognitive Radio Networks Using Distributed Dynamic Load Balanced Clustering Scheme

Directory of Open Access Journals (Sweden)

Muthukkumar R.

2017-04-01

Full Text Available Cognitive Radio (CR is a promising and potential technique to enable secondary users (SUs or unlicenced users to exploit the unused spectrum resources effectively possessed by primary users (PUs or licenced users. The proven clustering approach is used to organize nodes in the network into the logical groups to attain energy efficiency, network scalability, and stability for improving the sensing accuracy in CR through cooperative spectrum sensing (CSS. In this paper, a distributed dynamic load balanced clustering (DDLBC algorithm is proposed. In this algorithm, each member in the cluster is to calculate the cooperative gain, residual energy, distance, and sensing cost from the neighboring clusters to perform the optimal decision. Each member in a cluster participates in selecting a cluster head (CH through cooperative gain, and residual energy that minimises network energy consumption and enhances the channel sensing. First, we form the number of clusters using the Markov decision process (MDP model to reduce the energy consumption in a network. In this algorithm, CR users effectively utilize the PUs reporting time slots of unavailability. The simulation results reveal that the clusters convergence, energy efficiency, and accuracy of channel sensing increased considerably by using the proposed algorithm.

Energy Efficient Cooperative Spectrum Sensing in Cognitive Radio Networks Using Distributed Dynamic Load Balanced Clustering Scheme

Directory of Open Access Journals (Sweden)

Muthukkumar R.

2016-07-01

Full Text Available Cognitive Radio (CR is a promising and potential technique to enable secondary users (SUs or unlicenced users to exploit the unused spectrum resources effectively possessed by primary users (PUs or licenced users. The proven clustering approach is used to organize nodes in the network into the logical groups to attain energy efficiency, network scalability, and stability for improving the sensing accuracy in CR through cooperative spectrum sensing (CSS. In this paper, a distributed dynamic load balanced clustering (DDLBC algorithm is proposed. In this algorithm, each member in the cluster is to calculate the cooperative gain, residual energy, distance, and sensing cost from the neighboring clusters to perform the optimal decision. Each member in a cluster participates in selecting a cluster head (CH through cooperative gain, and residual energy that minimises network energy consumption and enhances the channel sensing. First, we form the number of clusters using the Markov decision process (MDP model to reduce the energy consumption in a network. In this algorithm, CR users effectively utilize the PUs reporting time slots of unavailability. The simulation results reveal that the clusters convergence, energy efficiency, and accuracy of channel sensing increased considerably by using the proposed algorithm.

Energy efficiency in the British housing stock: Energy demand and the Homes Energy Efficiency Database

International Nuclear Information System (INIS)

Hamilton, Ian G.; Steadman, Philip J.; Bruhns, Harry; Summerfield, Alex J.; Lowe, Robert

2013-01-01

The UK Government has unveiled an ambitious retrofit programme that seeks significant improvement to the energy efficiency of the housing stock. High quality data on the energy efficiency of buildings and their related energy demand is critical to supporting and targeting investment in energy efficiency. Using existing home improvement programmes over the past 15 years, the UK Government has brought together data on energy efficiency retrofits in approximately 13 million homes into the Homes Energy Efficiency Database (HEED), along with annual metered gas and electricity use for the period of 2004–2007. This paper describes the HEED sample and assesses its representativeness in terms of dwelling characteristics, the energy demand of different energy performance levels using linked gas and electricity meter data, along with an analysis of the impact retrofit measures has on energy demand. Energy savings are shown to be associated with the installation of loft and cavity insulation, and glazing and boiler replacement. The analysis illustrates this source of ‘in-action’ data can be used to provide empirical estimates of impacts of energy efficiency retrofit on energy demand and provides a source of empirical data from which to support the development of national housing energy efficiency retrofit policies. - Highlights: • The energy efficiency level for 50% of the British housing stock is described. • Energy demand is influenced by size and age and energy performance. • Housing retrofits (e.g. cavity insulation, glazing and boiler replacements) save energy. • Historic differences in energy performance show persistent long-term energy savings

DEHAR: a Distributed Energy Harvesting Aware Routing Algorithm for Ad-hoc Multi-hop Wireless Sensor Networks

DEFF Research Database (Denmark)

Jakobsen, Mikkel Koefoed; Madsen, Jan; Hansen, Michael Reichhardt

2010-01-01

One of the key design goals in Wireless Sensor Networks is long lasting or even continuous operation. Continuous operation is made possible through energy harvesting. Keeping the network operational imposes a demand to prevent network segmentation and power loss in nodes. It is therefore important...... that the best energy-wise route is found for each data transfer from a source node to the sink node. We present a new adaptive and distributed routing algorithm for finding energy optimised routes in a wireless sensor network with energy harvesting. The algorithm finds an energy efficient route from each source...

A method to identify energy efficiency measures for factory systems based on qualitative modeling

CERN Document Server

Krones, Manuela

2017-01-01

Manuela Krones develops a method that supports factory planners in generating energy-efficient planning solutions. The method provides qualitative description concepts for factory planning tasks and energy efficiency knowledge as well as an algorithm-based linkage between these measures and the respective planning tasks. Its application is guided by a procedure model which allows a general applicability in the manufacturing sector. The results contain energy efficiency measures that are suitable for a specific planning task and reveal the roles of various actors for the measures’ implementation. Contents Driving Concerns for and Barriers against Energy Efficiency Approaches to Increase Energy Efficiency in Factories Socio-Technical Description of Factory Planning Tasks Description of Energy Efficiency Measures Case Studies on Welding Processes and Logistics Systems Target Groups Lecturers and Students of Industrial Engineering, Production Engineering, Environmental Engineering, Mechanical Engineering Practi...

Renewable energy sources: Energy Efficiency Agency

International Nuclear Information System (INIS)

Bulgarensky, Mihael

2004-01-01

The paper presents the activities of the Energy Efficiency Agency, its main functions, as well as the new legislation stimulating the use of RES, stipulated in the new Energy Law of Bulgaria. The second part of the paper describes the potential of renewable energy in i.e. wind energy; solar energy; biomass energy; hydro energy; geothermal energy; draft of a National Program on RES 2005-2015. The third part describes the main issues of the new ENERGY EFFICIENCY LAW and the established Energy efficiency fund. (Author)

Energy-Efficient Transmissions for Remote Wireless Sensor Networks: An Integrated HAP/Satellite Architecture for Emergency Scenarios.

Science.gov (United States)

Dong, Feihong; Li, Hongjun; Gong, Xiangwu; Liu, Quan; Wang, Jingchao

2015-09-03

A typical application scenario of remote wireless sensor networks (WSNs) is identified as an emergency scenario. One of the greatest design challenges for communications in emergency scenarios is energy-efficient transmission, due to scarce electrical energy in large-scale natural and man-made disasters. Integrated high altitude platform (HAP)/satellite networks are expected to optimally meet emergency communication requirements. In this paper, a novel integrated HAP/satellite (IHS) architecture is proposed, and three segments of the architecture are investigated in detail. The concept of link-state advertisement (LSA) is designed in a slow flat Rician fading channel. The LSA is received and processed by the terminal to estimate the link state information, which can significantly reduce the energy consumption at the terminal end. Furthermore, the transmission power requirements of the HAPs and terminals are derived using the gradient descent and differential equation methods. The energy consumption is modeled at both the source and system level. An innovative and adaptive algorithm is given for the energy-efficient path selection. The simulation results validate the effectiveness of the proposed adaptive algorithm. It is shown that the proposed adaptive algorithm can significantly improve energy efficiency when combined with the LSA and the energy consumption estimation.

Energy-Efficient Transmissions for Remote Wireless Sensor Networks: An Integrated HAP/Satellite Architecture for Emergency Scenarios

Science.gov (United States)

Dong, Feihong; Li, Hongjun; Gong, Xiangwu; Liu, Quan; Wang, Jingchao

2015-01-01

A typical application scenario of remote wireless sensor networks (WSNs) is identified as an emergency scenario. One of the greatest design challenges for communications in emergency scenarios is energy-efficient transmission, due to scarce electrical energy in large-scale natural and man-made disasters. Integrated high altitude platform (HAP)/satellite networks are expected to optimally meet emergency communication requirements. In this paper, a novel integrated HAP/satellite (IHS) architecture is proposed, and three segments of the architecture are investigated in detail. The concept of link-state advertisement (LSA) is designed in a slow flat Rician fading channel. The LSA is received and processed by the terminal to estimate the link state information, which can significantly reduce the energy consumption at the terminal end. Furthermore, the transmission power requirements of the HAPs and terminals are derived using the gradient descent and differential equation methods. The energy consumption is modeled at both the source and system level. An innovative and adaptive algorithm is given for the energy-efficient path selection. The simulation results validate the effectiveness of the proposed adaptive algorithm. It is shown that the proposed adaptive algorithm can significantly improve energy efficiency when combined with the LSA and the energy consumption estimation. PMID:26404292

Energy-Efficient Transmissions for Remote Wireless Sensor Networks: An Integrated HAP/Satellite Architecture for Emergency Scenarios

Directory of Open Access Journals (Sweden)

Feihong Dong

2015-09-01

Full Text Available A typical application scenario of remote wireless sensor networks (WSNs is identified as an emergency scenario. One of the greatest design challenges for communications in emergency scenarios is energy-efficient transmission, due to scarce electrical energy in large-scale natural and man-made disasters. Integrated high altitude platform (HAP/satellite networks are expected to optimally meet emergency communication requirements. In this paper, a novel integrated HAP/satellite (IHS architecture is proposed, and three segments of the architecture are investigated in detail. The concept of link-state advertisement (LSA is designed in a slow flat Rician fading channel. The LSA is received and processed by the terminal to estimate the link state information, which can significantly reduce the energy consumption at the terminal end. Furthermore, the transmission power requirements of the HAPs and terminals are derived using the gradient descent and differential equation methods. The energy consumption is modeled at both the source and system level. An innovative and adaptive algorithm is given for the energy-efficient path selection. The simulation results validate the effectiveness of the proposed adaptive algorithm. It is shown that the proposed adaptive algorithm can significantly improve energy efficiency when combined with the LSA and the energy consumption estimation.

Energy Efficiency Collaboratives

Energy Technology Data Exchange (ETDEWEB)

Li, Michael [US Department of Energy, Washington, DC (United States); Bryson, Joe [US Environmental Protection Agency, Washington, DC (United States)

2015-09-01

Collaboratives for energy efficiency have a long and successful history and are currently used, in some form, in more than half of the states. Historically, many state utility commissions have used some form of collaborative group process to resolve complex issues that emerge during a rate proceeding. Rather than debate the issues through the formality of a commission proceeding, disagreeing parties are sent to discuss issues in a less-formal setting and bring back resolutions to the commission. Energy efficiency collaboratives take this concept and apply it specifically to energy efficiency programs—often in anticipation of future issues as opposed to reacting to a present disagreement. Energy efficiency collaboratives can operate long term and can address the full suite of issues associated with designing, implementing, and improving energy efficiency programs. Collaboratives can be useful to gather stakeholder input on changing program budgets and program changes in response to performance or market shifts, as well as to provide continuity while regulators come and go, identify additional energy efficiency opportunities and innovations, assess the role of energy efficiency in new regulatory contexts, and draw on lessons learned and best practices from a diverse group. Details about specific collaboratives in the United States are in the appendix to this guide. Collectively, they demonstrate the value of collaborative stakeholder processes in producing successful energy efficiency programs.

Automatic control algorithm effects on energy production

Science.gov (United States)

Mcnerney, G. M.

1981-01-01

A computer model was developed using actual wind time series and turbine performance data to simulate the power produced by the Sandia 17-m VAWT operating in automatic control. The model was used to investigate the influence of starting algorithms on annual energy production. The results indicate that, depending on turbine and local wind characteristics, a bad choice of a control algorithm can significantly reduce overall energy production. The model can be used to select control algorithms and threshold parameters that maximize long term energy production. The results from local site and turbine characteristics were generalized to obtain general guidelines for control algorithm design.

Damage localization using a power-efficient distributed on-board signal processing algorithm in a wireless sensor network

International Nuclear Information System (INIS)

Liu, Lei; Liu, Shuntao; Yuan, Fuh-Gwo

2012-01-01

A distributed on-board algorithm that is embedded and executed within a group of wireless sensors to locate structural damages in isotropic plates is presented. The algorithm is based on an energy-decay model of Lamb waves and singular value decomposition (SVD) to determine damage locations. A sensor group consists of a small number of sensors, each of which independently collects wave signals and evaluates wave energy upon an external triggering signal sent from a base station. The energy values, usually a few bytes in length, are then sent to the base station to determine the presence and location of damages. In comparison with traditional centralized approaches in which whole datasets are required to be transmitted, the proposed algorithm yields much less wireless communication traffic, yet with a modest amount of computation required within sensors. Experiments have shown that the algorithm is robust to locate damage for isotropic plate structures and is very power efficient, with more than an order-of-magnitude power saving

An energy-efficient leader election mechanism for wireless body area networks

OpenAIRE

Zhang , Rongrong; Moungla , Hassine; Mehaoua , Ahmed

2014-01-01

International audience; In Wireless Body Area Networks (WBANs), the energy consumption determines the lifetime of the entire network. As a result, how to conserve the energy to prolong the network lifetime becomes a key problem in WBANs. In this paper, to address the energy conservation problem in WBANs, we develop an Energy-Efficient Leader Election mechanism, called EELE. In EELE, each node competes for the leader following the distributed leader election algorithm in which a utility functi...

A Novel Energy-Aware Distributed Clustering Algorithm for Heterogeneous Wireless Sensor Networks in the Mobile Environment.

Science.gov (United States)

Gao, Ying; Wkram, Chris Hadri; Duan, Jiajie; Chou, Jarong

2015-12-10

In order to prolong the network lifetime, energy-efficient protocols adapted to the features of wireless sensor networks should be used. This paper explores in depth the nature of heterogeneous wireless sensor networks, and finally proposes an algorithm to address the problem of finding an effective pathway for heterogeneous clustering energy. The proposed algorithm implements cluster head selection according to the degree of energy attenuation during the network's running and the degree of candidate nodes' effective coverage on the whole network, so as to obtain an even energy consumption over the whole network for the situation with high degree of coverage. Simulation results show that the proposed clustering protocol has better adaptability to heterogeneous environments than existing clustering algorithms in prolonging the network lifetime.

An efficient non-dominated sorting method for evolutionary algorithms.

Science.gov (United States)

Fang, Hongbing; Wang, Qian; Tu, Yi-Cheng; Horstemeyer, Mark F

2008-01-01

We present a new non-dominated sorting algorithm to generate the non-dominated fronts in multi-objective optimization with evolutionary algorithms, particularly the NSGA-II. The non-dominated sorting algorithm used by NSGA-II has a time complexity of O(MN(2)) in generating non-dominated fronts in one generation (iteration) for a population size N and M objective functions. Since generating non-dominated fronts takes the majority of total computational time (excluding the cost of fitness evaluations) of NSGA-II, making this algorithm faster will significantly improve the overall efficiency of NSGA-II and other genetic algorithms using non-dominated sorting. The new non-dominated sorting algorithm proposed in this study reduces the number of redundant comparisons existing in the algorithm of NSGA-II by recording the dominance information among solutions from their first comparisons. By utilizing a new data structure called the dominance tree and the divide-and-conquer mechanism, the new algorithm is faster than NSGA-II for different numbers of objective functions. Although the number of solution comparisons by the proposed algorithm is close to that of NSGA-II when the number of objectives becomes large, the total computational time shows that the proposed algorithm still has better efficiency because of the adoption of the dominance tree structure and the divide-and-conquer mechanism.

Energy Efficient Routing in Wireless Sensor Networks Through Balanced Clustering

Directory of Open Access Journals (Sweden)

Christos Douligeris

2013-01-01

Full Text Available The wide utilization of Wireless Sensor Networks (WSNs is obstructed by the severely limited energy constraints of the individual sensor nodes. This is the reason why a large part of the research in WSNs focuses on the development of energy efficient routing protocols. In this paper, a new protocol called Equalized Cluster Head Election Routing Protocol (ECHERP, which pursues energy conservation through balanced clustering, is proposed. ECHERP models the network as a linear system and, using the Gaussian elimination algorithm, calculates the combinations of nodes that can be chosen as cluster heads in order to extend the network lifetime. The performance evaluation of ECHERP is carried out through simulation tests, which evince the effectiveness of this protocol in terms of network energy efficiency when compared against other well-known protocols.

Energy Efficiency Experiments on Samsung Exynos 5 Heterogeneous Multicore using OmpSs Task Based Programming

OpenAIRE

Holmgren, Rune

2015-01-01

This thesis explore the energy efficiency of task based programming with OpenMP SuperScalar (OmpSs) on the heterogeneous Samsung Exynos 5422 system on a chip. The system features small energy efficient cores, large high performance cores and a GPGPU, and OmpSs tasks were run on all three different processors. Experiments running a genetic algorithm and a Cholesky decomposition were used to gather results. The option of running applications on the energy efficient cores, on the high perfo...

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 ...

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.

Efficient Double Auction Mechanisms in the Energy Grid with Connected and Islanded Microgrids

Science.gov (United States)

Faqiry, Mohammad Nazif

The future energy grid is expected to operate in a decentralized fashion as a network of autonomous microgrids that are coordinated by a Distribution System Operator (DSO), which should allocate energy to them in an efficient manner. Each microgrid operating in either islanded or grid-connected mode may be considered to manage its own resources. This can take place through auctions with individual units of the microgrid as the agents. This research proposes efficient auction mechanisms for the energy grid, with is-landed and connected microgrids. The microgrid level auction is carried out by means of an intermediate agent called an aggregator. The individual consumer and producer units are modeled as selfish agents. With the microgrid in islanded mode, two aggregator-level auction classes are analyzed: (i) price-heterogeneous, and (ii) price homogeneous. Under the price heterogeneity paradigm, this research extends earlier work on the well-known, single-sided Kelly mechanism to double auctions. As in Kelly auctions, the proposed algorithm implements the bidding without using any agent level private infor-mation (i.e. generation capacity and utility functions). The proposed auction is shown to be an efficient mechanism that maximizes the social welfare, i.e. the sum of the utilities of all the agents. Furthermore, the research considers the situation where a subset of agents act as a coalition to redistribute the allocated energy and price using any other specific fairness criterion. The price homogeneous double auction algorithm proposed in this research ad-dresses the problem of price-anticipation, where each agent tries to influence the equilibri-um price of energy by placing strategic bids. As a result of this behavior, the auction's efficiency is lowered. This research proposes a novel approach that is implemented by the aggregator, called virtual bidding, where the efficiency can be asymptotically maximized, even in the presence of price anticipatory bidders

Efficient On-the-fly Algorithms for the Analysis of Timed Games

DEFF Research Database (Denmark)

Cassez, Franck; David, Alexandre; Fleury, Emmanuel

2005-01-01

In this paper, we propose the first efficient on-the-fly algorithm for solving games based on timed game automata with respect to reachability and safety properties The algorithm we propose is a symbolic extension of the on-the-fly algorithm suggested by Liu & Smolka [15] for linear-time model-ch...... symbolic algorithm are proposed as well as methods for obtaining time-optimal winning strategies (for reachability games). Extensive evaluation of an experimental implementation of the algorithm yields very encouraging performance results.......In this paper, we propose the first efficient on-the-fly algorithm for solving games based on timed game automata with respect to reachability and safety properties The algorithm we propose is a symbolic extension of the on-the-fly algorithm suggested by Liu & Smolka [15] for linear-time model...

Efficient conjugate gradient algorithms for computation of the manipulator forward dynamics

Science.gov (United States)

Fijany, Amir; Scheid, Robert E.

1989-01-01

The applicability of conjugate gradient algorithms for computation of the manipulator forward dynamics is investigated. The redundancies in the previously proposed conjugate gradient algorithm are analyzed. A new version is developed which, by avoiding these redundancies, achieves a significantly greater efficiency. A preconditioned conjugate gradient algorithm is also presented. A diagonal matrix whose elements are the diagonal elements of the inertia matrix is proposed as the preconditioner. In order to increase the computational efficiency, an algorithm is developed which exploits the synergism between the computation of the diagonal elements of the inertia matrix and that required by the conjugate gradient algorithm.

Reconsidering energy efficiency

International Nuclear Information System (INIS)

Goldoni, Giovanni

2007-01-01

Energy and environmental policies are reconsidering energy efficiency. In a perfect market, rational and well informed consumers reach economic efficiency which, at the given prices of energy and capital, corresponds to physical efficiency. In the real world, market failures and cognitive frictions distort the consumers from perfectly rational and informed choices. Green incentive schemes aim at balancing market failures and directing consumers toward more efficient goods and services. The problem is to fine tune the incentive schemes [it

Optimal Energy-Efficient Sensing and Power Allocation in Cognitive Radio Networks

Directory of Open Access Journals (Sweden)

Xia Wu

2014-01-01

Full Text Available We consider a joint optimization of sensing parameter and power allocation for an energy-efficient cognitive radio network (CRN in which the primary user (PU is protected. The optimization problem to maximize the energy efficiency of CRN is formulated as a function of two variables, which are sensing time and transmit power, subject to the average interference power to the PU and the target detection probability. During the optimizing process, the quality of service parameter (the minimum rate acceptable to secondary users (SUs has also been taken into consideration. The optimal solutions are analyzed and an algorithm combined with fractional programming that maximizes the energy efficiency for CRN is presented. Numerical results show that the performance improvement is achieved by the joint optimization of sensing time and power allocation.

EE-eICIC: Energy-Efficient Optimization of Joint User Association and ABS for eICIC in Heterogeneous Cellular Networks

Directory of Open Access Journals (Sweden)

Jie Zheng

2017-01-01

Full Text Available The densification and expansion of heterogeneous cellular networks (HetNets pose new challenges on interference management and reduction of energy consumption. The 3GPP has proposed enhanced intercell interference coordination (eICIC by making a macrocell silent in almost blank subframes (ABSs to mitigate interference for low power base stations (BSs in HetNets. However, energy efficiency (EE is very crucial for the deployment of a large number of low power nodes as they consume a lot of energy. In this work, we develop a novel EE-eICIC algorithm to determine the amount of ABSs and user equipment (UE that should associate with picocells or macrocells from energy efficiency perspective. Due to the nonsmooth and mixed combinatorial features of this formulation, we focus on a suboptimal algorithm design. Using generalized fractional programming and the convex programming theory, we propose an iterative and relaxed-rounding algorithm to solve the problem. Numerical results illustrate that the proposed EE-eICIC algorithm achieves superior performance in comparison with state-of-the-art methods in terms of energy efficiency of both system and user.

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.

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

Science.gov (United States)

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.

Mobility Aware Energy Efficient Clustering for MANET: A Bio-Inspired Approach with Particle Swarm Optimization

Directory of Open Access Journals (Sweden)

Naghma Khatoon

2017-01-01

Full Text Available Mobility awareness and energy efficiency are two indispensable optimization problems in mobile ad hoc networks (MANETs where nodes move unpredictably in any direction with restricted battery life, resulting in frequent change in topology. These constraints are widely studied to increase the lifetime of such networks. This paper focuses on the problems of mobility as well as energy efficiency to develop a clustering algorithm inspired by multiagent stochastic parallel search technique of particle swarm optimization. The election of cluster heads takes care of mobility and remaining energy as well as the degree of connectivity for selecting nodes to serve as cluster heads for longer duration of time. The cluster formation is presented by taking multiobjective fitness function using particle swarm optimization. The proposed work is experimented extensively in the NS-2 network simulator and compared with the other existing algorithms. The results show the effectiveness of our proposed algorithm in terms of network lifetime, average number of clusters formed, average number of reclustering required, energy consumption, and packet delivery ratio.

EDDA: An Efficient Distributed Data Replication Algorithm in VANETs.

Science.gov (United States)

Zhu, Junyu; Huang, Chuanhe; Fan, Xiying; Guo, Sipei; Fu, Bin

2018-02-10

Efficient data dissemination in vehicular ad hoc networks (VANETs) is a challenging issue due to the dynamic nature of the network. To improve the performance of data dissemination, we study distributed data replication algorithms in VANETs for exchanging information and computing in an arbitrarily-connected network of vehicle nodes. To achieve low dissemination delay and improve the network performance, we control the number of message copies that can be disseminated in the network and then propose an efficient distributed data replication algorithm (EDDA). The key idea is to let the data carrier distribute the data dissemination tasks to multiple nodes to speed up the dissemination process. We calculate the number of communication stages for the network to enter into a balanced status and show that the proposed distributed algorithm can converge to a consensus in a small number of communication stages. Most of the theoretical results described in this paper are to study the complexity of network convergence. The lower bound and upper bound are also provided in the analysis of the algorithm. Simulation results show that the proposed EDDA can efficiently disseminate messages to vehicles in a specific area with low dissemination delay and system overhead.

EDDA: An Efficient Distributed Data Replication Algorithm in VANETs

Science.gov (United States)

Zhu, Junyu; Huang, Chuanhe; Fan, Xiying; Guo, Sipei; Fu, Bin

2018-01-01

Efficient data dissemination in vehicular ad hoc networks (VANETs) is a challenging issue due to the dynamic nature of the network. To improve the performance of data dissemination, we study distributed data replication algorithms in VANETs for exchanging information and computing in an arbitrarily-connected network of vehicle nodes. To achieve low dissemination delay and improve the network performance, we control the number of message copies that can be disseminated in the network and then propose an efficient distributed data replication algorithm (EDDA). The key idea is to let the data carrier distribute the data dissemination tasks to multiple nodes to speed up the dissemination process. We calculate the number of communication stages for the network to enter into a balanced status and show that the proposed distributed algorithm can converge to a consensus in a small number of communication stages. Most of the theoretical results described in this paper are to study the complexity of network convergence. The lower bound and upper bound are also provided in the analysis of the algorithm. Simulation results show that the proposed EDDA can efficiently disseminate messages to vehicles in a specific area with low dissemination delay and system overhead. PMID:29439443

A Smart and Balanced Energy-Efficient Multihop Clustering Algorithm (Smart-BEEM) for MIMO IoT Systems in Future Networks.

Science.gov (United States)

Xu, Lina; O'Hare, Gregory M P; Collier, Rem

2017-07-05

Wireless Sensor Networks (WSNs) are typically composed of thousands of sensors powered by limited energy resources. Clustering techniques were introduced to prolong network longevity offering the promise of green computing. However, most existing work fails to consider the network coverage when evaluating the lifetime of a network. We believe that balancing the energy consumption in per unit area rather than on each single sensor can provide better-balanced power usage throughout the network. Our former work-Balanced Energy-Efficiency (BEE) and its Multihop version BEEM can not only extend the network longevity, but also maintain the network coverage. Following WSNs, Internet of Things (IoT) technology has been proposed with higher degree of diversities in terms of communication abilities and user scenarios, supporting a large range of real world applications. The IoT devices are embedded with multiple communication interfaces, normally referred as Multiple-In and Multiple-Out (MIMO) in 5G networks. The applications running on those devices can generate various types of data. Every interface has its own characteristics, which may be preferred and beneficial in some specific user scenarios. With MIMO becoming more available on the IoT devices, an advanced clustering solution for highly dynamic IoT systems is missing and also pressingly demanded in order to cater for differing user applications. In this paper, we present a smart clustering algorithm (Smart-BEEM) based on our former work BEE(M) to accomplish energy efficient and Quality of user Experience (QoE) supported communication in cluster based IoT networks. It is a user behaviour and context aware approach, aiming to facilitate IoT devices to choose beneficial communication interfaces and cluster headers for data transmission. Experimental results have proved that Smart-BEEM can further improve the performance of BEE and BEEM for coverage sensitive longevity.

An energy-efficient and secure hybrid algorithm for wireless sensor networks using a mobile data collector

Science.gov (United States)

Dayananda, Karanam Ravichandran; Straub, Jeremy

2017-05-01

This paper proposes a new hybrid algorithm for security, which incorporates both distributed and hierarchal approaches. It uses a mobile data collector (MDC) to collect information in order to save energy of sensor nodes in a wireless sensor network (WSN) as, in most networks, these sensor nodes have limited energy. Wireless sensor networks are prone to security problems because, among other things, it is possible to use a rogue sensor node to eavesdrop on or alter the information being transmitted. To prevent this, this paper introduces a security algorithm for MDC-based WSNs. A key use of this algorithm is to protect the confidentiality of the information sent by the sensor nodes. The sensor nodes are deployed in a random fashion and form group structures called clusters. Each cluster has a cluster head. The cluster head collects data from the other nodes using the time-division multiple access protocol. The sensor nodes send their data to the cluster head for transmission to the base station node for further processing. The MDC acts as an intermediate node between the cluster head and base station. The MDC, using its dynamic acyclic graph path, collects the data from the cluster head and sends it to base station. This approach is useful for applications including warfighting, intelligent building and medicine. To assess the proposed system, the paper presents a comparison of its performance with other approaches and algorithms that can be used for similar purposes.

Energy efficient design

International Nuclear Information System (INIS)

1991-01-01

Solar Applications and Energy Efficiency in Building Design and Town Planning (RER/87/006) is a United Nations Development Programme (UNDP) project of the Governments of Albania, Bulgaria, Cyprus, The Czech and Slovak Federal Republic, France, Hungary, Malta, Poland, Turkey, United Kingdom and Yugoslavia. The project began in 1988 and comes to a conclusion at the end of 1991. It is to enhance the professional skills of practicing architects, engineers and town planners in European countries to design energy efficient buildings which reduce energy consumption and make greater use of passive solar heating and natural cooling techniques. The United Nations Economic Commission for Europe (ECE) is the Executing Agency of the project which is implemented under the auspices of the Committee on Energy, General Energy Programme of Work for 1990-1994, sub-programme 5 Energy Conservation and Efficiency (ECE/ENERGY/15). The project has five main outputs or results: an international network of institutions for low energy building design; a state-of-the-art survey of energy use in the built environment of European IPF countries; a simple computer program for energy efficient building design; a design guide and computer program operators' manual; and a series of international training courses in participating European IPF countries. Energy Efficient Design is the fourth output of the project. It comprises the design guide for practicing architects and engineers, for use mainly in mid-career training courses, and the operators' manual for the project's computer program

Design strategy for improving the energy efficiency in series hydraulic/electric synergy system

International Nuclear Information System (INIS)

Ramakrishnan, R.; Hiremath, Somashekhar S.; Singaperumal, M.

2014-01-01

Battery is a vital subsystem in an electric vehicle with regenerative braking system. The energy efficiency of an electric vehicle is improved by storing the regenerated energy in an electric battery, during braking, and reusing it during subsequent acceleration. Battery possesses a relatively poor power density and slow charging of regenerated energy, when compared to hydro-pneumatic accumulators. A series hydraulic/electric synergy system – an energy efficient mechatronics system is proposed to overcome the drawbacks in the conventional electric vehicle with regenerative braking. Even though, electric battery provides higher energy density than the accumulator system, optimal sizing of the hydro-pneumatic accumulator and other process parameters in the system to provide better energy density and efficiency. However, a trade-off prevails between the system energy delivered and energy consumed. This gives rise to a multiple objective problem. The proposed multi-objective design optimization procedure based on an evolutionary strategy algorithm maximizes the energy efficiency of the system. The system simulation results after optimization show that, the optimal system parameters increase the energy efficiency by 3% and hydraulic regeneration efficiency by 17.3%. The suggested design methodology provides a basis for the design of a series hydraulic/electric synergy system as energy efficient and zero emission system. - Highlights: • Dynamic analysis of SHESS to investigate energy efficiency. • Optimization of system parameters based on multi-objective design strategy. • Evaluation of improvements in system energy efficiency and hydraulic regeneration energy. • Identification of conditions at which hydraulic regenerative efficiency is maximized for minimum energy consumption. • Results confirm advantages of using SHESS

A support approach for the conceptual design of energy-efficient cooker hoods

International Nuclear Information System (INIS)

Cicconi, Paolo; Landi, Daniele; Germani, Michele; Russo, Anna Costanza

2017-01-01

Highlights: •An eco-innovation approach to support the design of household appliances. •The research is focused on the energy labelling for kitchen hoods. •A software platform provides tools to configure and optimize new solutions. •A tool can calculate the energy efficiency indexes of a product configuration. -- Abstract: In Europe, kitchen hoods currently come with an energy label showing their energy efficiency class and other information regarding the energy consumption and noise level, as established by the European Energy Labelling Directive. Because of recent regulations, designs of cooker hoods must consider new issues, such as the evaluation of the energy efficiency, analysis of the energy consumption, and product lifecycle impact. Therefore, the development of eco-driven products requires Ecodesign tools to support eco-innovation and related sustainability improvements. The scope of the proposed research is to define a method and an agile and affordable platform tool that can support designers in the early estimation of product energy performance, including the calculation of energy efficiency indexes. The approach also considers the use of genetic algorithm methods to optimize the product configuration in terms of energy efficiency. The research context concerns large and small productions of kitchen hoods. The paper describes the methodological approach within the developed tool. The results show a good correlation between real efficiency values and calculated ones. A validation activity has been described, and a test case shows how to apply the proposed approach for the design of a new efficient product with an A-class Energy Efficiency Index.

Multi-objective exergy-based optimization of a polygeneration energy system using an evolutionary algorithm

International Nuclear Information System (INIS)

Ahmadi, Pouria; Rosen, Marc A.; Dincer, Ibrahim

2012-01-01

A comprehensive thermodynamic modeling and optimization is reported of a polygeneration energy system for the simultaneous production of heating, cooling, electricity and hot water from a common energy source. This polygeneration system is composed of four major parts: gas turbine (GT) cycle, Rankine cycle, absorption cooling cycle and domestic hot water heater. A multi-objective optimization method based on an evolutionary algorithm is applied to determine the best design parameters for the system. The two objective functions utilized in the analysis are the total cost rate of the system, which is the cost associated with fuel, component purchasing and environmental impact, and the system exergy efficiency. The total cost rate of the system is minimized while the cycle exergy efficiency is maximized by using an evolutionary algorithm. To provide a deeper insight, the Pareto frontier is shown for multi-objective optimization. In addition, a closed form equation for the relationship between exergy efficiency and total cost rate is derived. Finally, a sensitivity analysis is performed to assess the effects of several design parameters on the system total exergy destruction rate, CO 2 emission and exergy efficiency.

Enhanced Particle Swarm Optimization Algorithm: Efficient Training of ReaxFF Reactive Force Fields.

Science.gov (United States)

Furman, David; Carmeli, Benny; Zeiri, Yehuda; Kosloff, Ronnie

2018-05-04

Particle swarm optimization is a powerful metaheuristic population-based global optimization algorithm. However, when applied to non-separable objective functions its performance on multimodal landscapes is significantly degraded. Here we show that a significant improvement in the search quality and efficiency on multimodal functions can be achieved by enhancing the basic rotation-invariant particle swarm optimization algorithm with isotropic Gaussian mutation operators. The new algorithm demonstrates a superior performance across several nonlinear, multimodal benchmark functions compared to the rotation-invariant Particle Swam Optimization (PSO) algorithm and the well-established simulated annealing and sequential one-parameter parabolic interpolation methods. A search for the optimal set of parameters for the dispersion interaction model in ReaxFF-lg reactive force field is carried out with respect to accurate DFT-TS calculations. The resulting optimized force field accurately describes the equations of state of several high-energy molecular crystals where such interactions are of crucial importance. The improved algorithm also presents a better performance compared to a Genetic Algorithm optimization method in the optimization of a ReaxFF-lg correction model parameters. The computational framework is implemented in a standalone C++ code that allows a straightforward development of ReaxFF reactive force fields.

Investigating the Multi-memetic Mind Evolutionary Computation Algorithm Efficiency

Directory of Open Access Journals (Sweden)

M. K. Sakharov

2017-01-01

Full Text Available In solving practically significant problems of global optimization, the objective function is often of high dimensionality and computational complexity and of nontrivial landscape as well. Studies show that often one optimization method is not enough for solving such problems efficiently - hybridization of several optimization methods is necessary.One of the most promising contemporary trends in this field are memetic algorithms (MA, which can be viewed as a combination of the population-based search for a global optimum and the procedures for a local refinement of solutions (memes, provided by a synergy. Since there are relatively few theoretical studies concerning the MA configuration, which is advisable for use to solve the black-box optimization problems, many researchers tend just to adaptive algorithms, which for search select the most efficient methods of local optimization for the certain domains of the search space.The article proposes a multi-memetic modification of a simple SMEC algorithm, using random hyper-heuristics. Presents the software algorithm and memes used (Nelder-Mead method, method of random hyper-sphere surface search, Hooke-Jeeves method. Conducts a comparative study of the efficiency of the proposed algorithm depending on the set and the number of memes. The study has been carried out using Rastrigin, Rosenbrock, and Zakharov multidimensional test functions. Computational experiments have been carried out for all possible combinations of memes and for each meme individually.According to results of study, conducted by the multi-start method, the combinations of memes, comprising the Hooke-Jeeves method, were successful. These results prove a rapid convergence of the method to a local optimum in comparison with other memes, since all methods perform the fixed number of iterations at the most.The analysis of the average number of iterations shows that using the most efficient sets of memes allows us to find the optimal

Management of Sustainable Energy Efficient Development at the Local Level: Stakeholder-Oriented Approach

Directory of Open Access Journals (Sweden)

Horban Vasylyna B.

2016-11-01

Full Text Available There presented a theoretical rationale for the expediency of using the stakeholder-oriented approach to improve the process of management of sustainable energy efficient development at the local level. The evolution of theories by scientific schools that studied the concepts of «stakeholders» and «interested parties» is analyzed and generalized. A classification of types of stakeholders in the context of eighteen typological features is suggested, which allows to more effectively align their interests and contributes to establishing constructive forms of cooperation in order to achieve efficient final results. An algorithm of interaction with interested parties in achieving the goals of sustainable energy efficient development at the local level is elaborated. Typical motivational interests of stakeholders at the local level in the field of sustainable energy efficient development (on the example of Ukraine are identified. Instruments of prioritization of stakeholders depending on the life cycle stages of energy efficiency projects are proposed. The results obtained in the course of the research can be used to develop local energy efficient programs, business plans and feasibility studies for energy efficient projects.

Energy efficiency with QoS control in dynamic optical networks with SDN enabled integrated control plane

DEFF Research Database (Denmark)

Wang, Jiayuan; Chen, Xin; Phillips, Chris

2014-01-01

The paper presents energy efficient routing algorithms based on a novel integrated control plane platform. The centralized control plane structure enables the use of flexible heuristic algorithms for route selection in optical networks. Differentiated routing for various traffic types is used in ...

Transport Energy Efficiency

Energy Technology Data Exchange (ETDEWEB)

NONE

2010-07-01

Transport is the sector with the highest final energy consumption and, without any significant policy changes, is forecast to remain so. In 2008, the IEA published 25 energy efficiency recommendations, among which four are for the transport sector. The recommendations focus on road transport and include policies on improving tyre energy efficiency, fuel economy standards for both light-duty vehicles and heavy-duty vehicles, and eco-driving. Implementation of the recommendations has been weaker in the transport sector than others. This paper updates the progress that has been made in implementing the transport energy efficiency recommendations in IEA countries since March 2009. Many countries have in the last year moved from 'planning to implement' to 'implementation underway', but none have fully implemented all transport energy efficiency recommendations. The IEA calls therefore for full and immediate implementation of the recommendations.

Efficient scheduling request algorithm for opportunistic wireless access

KAUST Repository

Nam, Haewoon

2011-08-01

An efficient scheduling request algorithm for opportunistic wireless access based on user grouping is proposed in this paper. Similar to the well-known opportunistic splitting algorithm, the proposed algorithm initially adjusts (or lowers) the threshold during a guard period if no user sends a scheduling request. However, if multiple users make requests simultaneously and therefore a collision occurs, the proposed algorithm no longer updates the threshold but narrows down the user search space by splitting the users into multiple groups iteratively, whereas the opportunistic splitting algorithm keeps adjusting the threshold until a single user is found. Since the threshold is only updated when no user sends a request, it is shown that the proposed algorithm significantly alleviates the burden of the signaling for the threshold distribution to the users by the scheduler. More importantly, the proposed algorithm requires a less number of mini-slots to make a user selection given a certain scheduling outage probability. © 2011 IEEE.

Highly Efficient Compression Algorithms for Multichannel EEG.

Science.gov (United States)

Shaw, Laxmi; Rahman, Daleef; Routray, Aurobinda

2018-05-01

The difficulty associated with processing and understanding the high dimensionality of electroencephalogram (EEG) data requires developing efficient and robust compression algorithms. In this paper, different lossless compression techniques of single and multichannel EEG data, including Huffman coding, arithmetic coding, Markov predictor, linear predictor, context-based error modeling, multivariate autoregression (MVAR), and a low complexity bivariate model have been examined and their performances have been compared. Furthermore, a high compression algorithm named general MVAR and a modified context-based error modeling for multichannel EEG have been proposed. The resulting compression algorithm produces a higher relative compression ratio of 70.64% on average compared with the existing methods, and in some cases, it goes up to 83.06%. The proposed methods are designed to compress a large amount of multichannel EEG data efficiently so that the data storage and transmission bandwidth can be effectively used. These methods have been validated using several experimental multichannel EEG recordings of different subjects and publicly available standard databases. The satisfactory parametric measures of these methods, namely percent-root-mean square distortion, peak signal-to-noise ratio, root-mean-square error, and cross correlation, show their superiority over the state-of-the-art compression methods.

Efficient Record Linkage Algorithms Using Complete Linkage Clustering.

Science.gov (United States)

Mamun, Abdullah-Al; Aseltine, Robert; Rajasekaran, Sanguthevar

2016-01-01

Data from different agencies share data of the same individuals. Linking these datasets to identify all the records belonging to the same individuals is a crucial and challenging problem, especially given the large volumes of data. A large number of available algorithms for record linkage are prone to either time inefficiency or low-accuracy in finding matches and non-matches among the records. In this paper we propose efficient as well as reliable sequential and parallel algorithms for the record linkage problem employing hierarchical clustering methods. We employ complete linkage hierarchical clustering algorithms to address this problem. In addition to hierarchical clustering, we also use two other techniques: elimination of duplicate records and blocking. Our algorithms use sorting as a sub-routine to identify identical copies of records. We have tested our algorithms on datasets with millions of synthetic records. Experimental results show that our algorithms achieve nearly 100% accuracy. Parallel implementations achieve almost linear speedups. Time complexities of these algorithms do not exceed those of previous best-known algorithms. Our proposed algorithms outperform previous best-known algorithms in terms of accuracy consuming reasonable run times.

Energy efficient policy impact in India: case study of investment in industrial energy efficiency

International Nuclear Information System (INIS)

Yang, M.

2006-01-01

The objective of this paper is to identify the effectiveness of energy policy and capital investment in energy efficiency technologies in the industrial sector in India. Indian energy policies relating to industrial energy efficiency over the past 25 years are briefly reviewed, and a comparison study of these energy efficiency policies and strategies in India and China has been carried out. Interviews were conducted with a number of government policy-making institutions and a national industrial development bank. The accounts of 26 industrial enterprises which applied and used a loan of the Asian Development Bank were audited for data collection. Field-visits to seven industrial entrepreneurs were undertaken in a case study. Methodologies used in this study include documentation, cross-country reviews on energy policies, questionnaire design and distribution in the industrial sector, and on-site auditing of energy efficiency technologies. This paper concludes that current energy policies and strategies in India need further improvement to promote energy efficiency investment and energy efficiency technology development in the industrial sector. This paper will interest those policy makers and industrial entrepreneurs who are willing to finance energy efficiency projects and improve energy efficiency in the industrial sector. (author)

Energy efficiency policy impact in India: case study of investment in industrial energy efficiency

International Nuclear Information System (INIS)

Yang Ming

2006-01-01

The objective of this paper is to identify the effectiveness of energy policy and capital investment in energy efficiency technologies in the industrial sector in India. Indian energy policies relating to industrial energy efficiency over the past 25 years are briefly reviewed, and a comparison study of these energy efficiency policies and strategies in India and China has been carried out. Interviews were conducted with a number of government policy-making institutions and a national industrial development bank. The accounts of 26 industrial enterprises which applied and used a loan of the Asian Development Bank were audited for data collection. Field-visits to seven industrial entrepreneurs were undertaken in a case study. Methodologies used in this study include documentation, cross-country reviews on energy policies, questionnaire design and distribution in the industrial sector, and on-site auditing of energy efficiency technologies. This paper concludes that current energy policies and strategies in India need further improvement to promote energy efficiency investment and energy efficiency technology development in the industrial sector. This paper will interest those policy makers and industrial entrepreneurs who are willing to finance energy efficiency projects and improve energy efficiency in the industrial sector

Pap-smear Classification Using Efficient Second Order Neural Network Training Algorithms

DEFF Research Database (Denmark)

Ampazis, Nikolaos; Dounias, George; Jantzen, Jan

2004-01-01

In this paper we make use of two highly efficient second order neural network training algorithms, namely the LMAM (Levenberg-Marquardt with Adaptive Momentum) and OLMAM (Optimized Levenberg-Marquardt with Adaptive Momentum), for the construction of an efficient pap-smear test classifier. The alg......In this paper we make use of two highly efficient second order neural network training algorithms, namely the LMAM (Levenberg-Marquardt with Adaptive Momentum) and OLMAM (Optimized Levenberg-Marquardt with Adaptive Momentum), for the construction of an efficient pap-smear test classifier...

An energy efficient and dynamic time synchronization protocol for wireless sensor networks

Science.gov (United States)

Zhang, Anran; Bai, Fengshan

2017-01-01

Time synchronization is an important support technology of WSN(Wireless Sensor Network), and plays an irreplaceable role in the development of WSN. In view of the disadvantage of the traditional timing sync protocol for sensor networks (TPSN), we present a Physical Timing-sync Protocol (PTPSN) that aims at reducing the energy consumption of the synchronization process and realizes a dynamic Network. The algorithm broadcasts reference message to select some nodes in specific area. The receiver calculate offset of every selected node, and then calculate the average of offset to compensate for clock skew . At the same time ,we add time-filter process to ensure the security of the algorithm for time synchronization. The experiment results show that our algorithm is efficient in both saving energy consumption and dynamic network, and it can effectively resist attacks.

EDDA: An Efficient Distributed Data Replication Algorithm in VANETs

Directory of Open Access Journals (Sweden)

Junyu Zhu

2018-02-01

Full Text Available Efficient data dissemination in vehicular ad hoc networks (VANETs is a challenging issue due to the dynamic nature of the network. To improve the performance of data dissemination, we study distributed data replication algorithms in VANETs for exchanging information and computing in an arbitrarily-connected network of vehicle nodes. To achieve low dissemination delay and improve the network performance, we control the number of message copies that can be disseminated in the network and then propose an efficient distributed data replication algorithm (EDDA. The key idea is to let the data carrier distribute the data dissemination tasks to multiple nodes to speed up the dissemination process. We calculate the number of communication stages for the network to enter into a balanced status and show that the proposed distributed algorithm can converge to a consensus in a small number of communication stages. Most of the theoretical results described in this paper are to study the complexity of network convergence. The lower bound and upper bound are also provided in the analysis of the algorithm. Simulation results show that the proposed EDDA can efficiently disseminate messages to vehicles in a specific area with low dissemination delay and system 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.

Pap-smear Classification Using Efficient Second Order Neural Network Training Algorithms

DEFF Research Database (Denmark)

Ampazis, Nikolaos; Dounias, George; Jantzen, Jan

2004-01-01

In this paper we make use of two highly efficient second order neural network training algorithms, namely the LMAM (Levenberg-Marquardt with Adaptive Momentum) and OLMAM (Optimized Levenberg-Marquardt with Adaptive Momentum), for the construction of an efficient pap-smear test classifier. The alg......In this paper we make use of two highly efficient second order neural network training algorithms, namely the LMAM (Levenberg-Marquardt with Adaptive Momentum) and OLMAM (Optimized Levenberg-Marquardt with Adaptive Momentum), for the construction of an efficient pap-smear test classifier....... The algorithms are methodologically similar, and are based on iterations of the form employed in the Levenberg-Marquardt (LM) method for non-linear least squares problems with the inclusion of an additional adaptive momentum term arising from the formulation of the training task as a constrained optimization...

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

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 efficiency: 2004 world overview

International Nuclear Information System (INIS)

2004-01-01

Since 1992 the World Energy Council (WEC) has been collaborating with ADEME (Agency for Environment and Energy Efficiency, France) on a joint project 'Energy Efficiency Policies and Indicators'. APERC (Asia Pacific Energy Research Centre) and OLADE (Latin American Energy Organisation) have also participated in the study, which has been monitoring and evaluating energy efficiency policies and their impacts around the world. WEC Member Committees have been providing data and information and ENERDATA (France) has provided technical assistance. This report, published in August 2004, presents and evaluates energy efficiency policies in 63 countries, with a specific focus on five policy measures, for which in-depth case studies were prepared by selected experts: - Minimum energy efficiency standards for household electrical appliances; - Innovative energy efficiency funds; - Voluntary/negotiated agreements on energy efficiency/ CO 2 ; - Local energy information centres; - Packages of measures. In particular, the report identifies the policy measures, which have proven to be the most effective, and can be recommended to countries which have recently embarked on the development and implementation of energy demand management policies. During the past ten years, the Kyoto Protocol and, more recently, emerging concerns about security of supply have raised, both the public and the political profile of energy efficiency. Almost all OECD countries and an increasing number of other countries are implementing energy efficiency policies adapted to their national circumstances. In addition to the market instruments (voluntary agreements, labels, information, etc.), regulatory measures are widely introduced where the market fails to give the right signals (buildings, appliances). In developing countries, energy efficiency is equally important, even if the drivers are different compared to industrialized countries. Reduction of greenhouse gas emissions and local pollution often have a

Energy efficiency; Energieffektivisering

Energy Technology Data Exchange (ETDEWEB)

2009-06-15

The Low Energy Panel will halve the consumption in buildings. The Panel has proposed a halving of consumption in the construction within 2040 and 20 percent reduction in the consumption in the industry within 2020. The Panel consider it as possible to gradually reduce consumption in buildings from the current level of 80 TWh with 10 TWh in 2020, 25 TWh in 2030 and 40 TWh in 2040. According the committee one such halving can be reached by significant efforts relating to energy efficiency, by greater rehabilitations, energy efficiency in consisting building stock and stricter requirements for new construction. For the industry field the Panel recommend a political goal to be set at least 20 percent reduction in specific energy consumption in the industry and primary industry beyond general technological development by the end of 2020. This is equivalent to approximately 17 TWh based on current level of activity. The Panel believes that a 5 percent reduction should be achieved by the end of 2012 by carrying out simple measures. The Low Energy Panel has since March 2009 considered possibilities to strengthen the authorities' work with energy efficiency in Norway. The wide complex panel adds up proposals for a comprehensive approach for increased energy efficiency in particular in the building- and industry field. The Panel has looked into the potential for energy efficiency, barriers for energy efficiency, assessment of strengths and weaknesses in the existing policy instruments and members of the Panel's recommendations. In addition the report contains a review of theoretical principles for effects of instruments together with an extensive background. One of the committee members have chosen to take special notes on the main recommendations in the report. (AG)

Energy Efficiency Center - Overview

International Nuclear Information System (INIS)

Obryk, E.

2000-01-01

Full text: The Energy Efficiency Center (EEC) activities have been concentrated on Energy Efficiency Network (SEGE), education and training of energy auditors. EEC has started studies related to renewable fuels (bio fuel, wastes) and other topics related to environment protection. EEC has continued close collaboration with Institute for Energy Technology, Kjeller, Norway. It has been organized and conducted Seminar and Workshop on ''How to Reduce Energy and Water Cost in Higher Education Buildings'' for general and technical managers of the higher education institutions. This Seminar was proceeded by the working meeting on energy efficiency strategy in higher education at the Ministry of National Education. EEC has worked out proposal for activities of Cracow Regional Agency for Energy Efficiency and Environment and has made offer to provide services for this Agency in the field of training, education and consulting. The vast knowledge and experiences in the field of energy audits have been used by the members of EEC in lecturing at energy auditors courses authorized by the National Energy Efficiency Agency (KAPE). Altogether 20 lectures have been delivered. (author)

Energy efficiency; Efficacite energetique

Energy Technology Data Exchange (ETDEWEB)

NONE

2006-06-15

This road-map proposes by the Group Total aims to inform the public on the energy efficiency. It presents the energy efficiency and intensity around the world with a particular focus on Europe, the energy efficiency in industry and Total commitment. (A.L.B.)

Energy efficiency in Swedish industry

International Nuclear Information System (INIS)

Zhang, Shanshan; Lundgren, Tommy; Zhou, Wenchao

2016-01-01

This paper assesses energy efficiency in Swedish industry. Using unique firm-level panel data covering the years 2001–2008, the efficiency estimates are obtained for firms in 14 industrial sectors by using data envelopment analysis (DEA). The analysis accounts for multi-output technologies where undesirable outputs are produced alongside with the desirable output. The results show that there was potential to improve energy efficiency in all the sectors and relatively large energy inefficiencies existed in small energy-use industries in the sample period. Also, we assess how the EU ETS, the carbon dioxide (CO_2) tax and the energy tax affect energy efficiency by conducting a second-stage regression analysis. To obtain consistent estimates for the regression model, we apply a modified, input-oriented version of the double bootstrap procedure of Simar and Wilson (2007). The results of the regression analysis reveal that the EU ETS and the CO_2 tax did not have significant influences on energy efficiency in the sample period. However, the energy tax had a positive relation with the energy efficiency. - Highlights: • We use DEA to estimate firm-level energy efficiency in Swedish industry. • We examine impacts of climate and energy policies on energy efficiency. • The analyzed policies are Swedish carbon and energy taxes and the EU ETS. • Carbon tax and EU ETS did not have significant influences on energy efficiency. • The energy tax had a positive relation with energy efficiency.

Multi-sources model and control algorithm of an energy management system for light electric vehicles

International Nuclear Information System (INIS)

Hannan, M.A.; Azidin, F.A.; Mohamed, A.

2012-01-01

Highlights: ► An energy management system (EMS) is developed for a scooter under normal and heavy power load conditions. ► The battery, FC, SC, EMS, DC machine and vehicle dynamics are modeled and designed for the system. ► State-based logic control algorithms provide an efficient and feasible multi-source EMS for light electric vehicles. ► Vehicle’s speed and power are closely matched with the ECE-47 driving cycle under normal and heavy load conditions. ► Sources of energy changeover occurred at 50% of the battery state of charge level in heavy load conditions. - Abstract: This paper presents the multi-sources energy models and ruled based feedback control algorithm of an energy management system (EMS) for light electric vehicle (LEV), i.e., scooters. The multiple sources of energy, such as a battery, fuel cell (FC) and super-capacitor (SC), EMS and power controller, DC machine and vehicle dynamics are designed and modeled using MATLAB/SIMULINK. The developed control strategies continuously support the EMS of the multiple sources of energy for a scooter under normal and heavy power load conditions. The performance of the proposed system is analyzed and compared with that of the ECE-47 test drive cycle in terms of vehicle speed and load power. The results show that the designed vehicle’s speed and load power closely match those of the ECE-47 test driving cycle under normal and heavy load conditions. This study’s results suggest that the proposed control algorithm provides an efficient and feasible EMS for LEV.

Efficient sequential and parallel algorithms for planted motif search.

Science.gov (United States)

Nicolae, Marius; Rajasekaran, Sanguthevar

2014-01-31

Motif searching is an important step in the detection of rare events occurring in a set of DNA or protein sequences. One formulation of the problem is known as (l,d)-motif search or Planted Motif Search (PMS). In PMS we are given two integers l and d and n biological sequences. We want to find all sequences of length l that appear in each of the input sequences with at most d mismatches. The PMS problem is NP-complete. PMS algorithms are typically evaluated on certain instances considered challenging. Despite ample research in the area, a considerable performance gap exists because many state of the art algorithms have large runtimes even for moderately challenging instances. This paper presents a fast exact parallel PMS algorithm called PMS8. PMS8 is the first algorithm to solve the challenging (l,d) instances (25,10) and (26,11). PMS8 is also efficient on instances with larger l and d such as (50,21). We include a comparison of PMS8 with several state of the art algorithms on multiple problem instances. This paper also presents necessary and sufficient conditions for 3 l-mers to have a common d-neighbor. The program is freely available at http://engr.uconn.edu/~man09004/PMS8/. We present PMS8, an efficient exact algorithm for Planted Motif Search. PMS8 introduces novel ideas for generating common neighborhoods. We have also implemented a parallel version for this algorithm. PMS8 can solve instances not solved by any previous algorithms.

A Smart and Balanced Energy-Efficient Multihop Clustering Algorithm (Smart-BEEM) for MIMO IoT Systems in Future Networks †

Science.gov (United States)

O’Hare, Gregory M. P.; Collier, Rem

2017-01-01

Wireless Sensor Networks (WSNs) are typically composed of thousands of sensors powered by limited energy resources. Clustering techniques were introduced to prolong network longevity offering the promise of green computing. However, most existing work fails to consider the network coverage when evaluating the lifetime of a network. We believe that balancing the energy consumption in per unit area rather than on each single sensor can provide better-balanced power usage throughout the network. Our former work—Balanced Energy-Efficiency (BEE) and its Multihop version BEEM can not only extend the network longevity, but also maintain the network coverage. Following WSNs, Internet of Things (IoT) technology has been proposed with higher degree of diversities in terms of communication abilities and user scenarios, supporting a large range of real world applications. The IoT devices are embedded with multiple communication interfaces, normally referred as Multiple-In and Multiple-Out (MIMO) in 5G networks. The applications running on those devices can generate various types of data. Every interface has its own characteristics, which may be preferred and beneficial in some specific user scenarios. With MIMO becoming more available on the IoT devices, an advanced clustering solution for highly dynamic IoT systems is missing and also pressingly demanded in order to cater for differing user applications. In this paper, we present a smart clustering algorithm (Smart-BEEM) based on our former work BEE(M) to accomplish energy efficient and Quality of user Experience (QoE) supported communication in cluster based IoT networks. It is a user behaviour and context aware approach, aiming to facilitate IoT devices to choose beneficial communication interfaces and cluster headers for data transmission. Experimental results have proved that Smart-BEEM can further improve the performance of BEE and BEEM for coverage sensitive longevity. PMID:28678164

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.

Efficient classical simulation of the Deutsch-Jozsa and Simon's algorithms

Science.gov (United States)

Johansson, Niklas; Larsson, Jan-Åke

2017-09-01

A long-standing aim of quantum information research is to understand what gives quantum computers their advantage. This requires separating problems that need genuinely quantum resources from those for which classical resources are enough. Two examples of quantum speed-up are the Deutsch-Jozsa and Simon's problem, both efficiently solvable on a quantum Turing machine, and both believed to lack efficient classical solutions. Here we present a framework that can simulate both quantum algorithms efficiently, solving the Deutsch-Jozsa problem with probability 1 using only one oracle query, and Simon's problem using linearly many oracle queries, just as expected of an ideal quantum computer. The presented simulation framework is in turn efficiently simulatable in a classical probabilistic Turing machine. This shows that the Deutsch-Jozsa and Simon's problem do not require any genuinely quantum resources, and that the quantum algorithms show no speed-up when compared with their corresponding classical simulation. Finally, this gives insight into what properties are needed in the two algorithms and calls for further study of oracle separation between quantum and classical computation.

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.

USE Efficiency -- Universities and Students for Energy Efficiency

Energy Technology Data Exchange (ETDEWEB)

Melandri, Daniela

2010-09-15

Universities and Student for Energy Efficiency is a European Project within the Intelligent Energy Programme. It intends to create a common stream for energy efficiency systems in university buildings. Universities and students are proposed as shining examples for energy efficiency solutions and behaviour. The Project involves 10 countries and has the aim to improve energy efficiency in university buildings. Students are the main actors of the project together with professors and technicians. To act on students means to act on direct future market players in diffusion of public opinions. A strong communication action supports the succeeding of the action.

Energy efficiency

International Nuclear Information System (INIS)

Marvillet, Ch.; Tochon, P.; Mercier, P.

2004-01-01

World energy demand is constantly rising. This is a legitimate trend, insofar as access to energy enables enhanced quality of life and sanitation levels for populations. On the other hand, such increased consumption generates effects that may be catastrophic for the future of the planet (climate change, environmental imbalance), should this growth conform to the patterns followed, up to recent times, by most industrialized countries. Reduction of greenhouse gas emissions, development of new energy sources and energy efficiency are seen as the major challenges to be taken up for the world of tomorrow. In France, the National Energy Debate indeed emphasized, in 2003, the requirement to control both demand for, and offer of, energy, through a strategic orientation law for energy. The French position corresponds to a slightly singular situation - and a privileged one, compared to other countries - owing to massive use of nuclear power for electricity generation. This option allows France to be responsible for a mere 2% of worldwide greenhouse gas emissions. Real advances can nonetheless still be achieved as regards improved energy efficiency, particularly in the transportation and residential-tertiary sectors, following the lead, in this respect, shown by industry. These two sectors indeed account for over half of the country CO 2 emissions (26% and 25% respectively). With respect to transportation, the work carried out by CEA on the hydrogen pathway, energy converters, and electricity storage has been covered by the preceding chapters. As regards housing, a topic addressed by one of the papers in this chapter, investigations at CEA concern integration of the various devices enabling value-added use of renewable energies. At the same time, the organization is carrying through its activity in the extensive area of heat exchangers, allowing industry to benefit from improved understanding in the modeling of flows. An activity evidenced by advances in energy efficiency for

E-Token Energy-Aware Proportionate Sharing Scheduling Algorithm for Multiprocessor Systems

Directory of Open Access Journals (Sweden)

Pasupuleti Ramesh

2017-01-01

Full Text Available WSN plays vital role from small range healthcare surveillance systems to largescale environmental monitoring. Its design for energy constrained applications is a challenging issue. Sensors in WSNs are projected to run separately for longer periods. It is of excessive cost to substitute exhausted batteries which is not even possible in antagonistic situations. Multiprocessors are used in WSNs for high performance scientific computing, where each processor is assigned the same or different workload. When the computational demands of the system increase then the energy efficient approaches play an important role to increase system lifetime. Energy efficiency is commonly carried out by using proportionate fair scheduler. This introduces abnormal overloading effect. In order to overcome the existing problems E-token Energy-Aware Proportionate Sharing (EEAPS scheduling is proposed here. The power consumption for each thread/task is calculated and the tasks are allotted to the multiple processors through the auctioning mechanism. The algorithm is simulated by using the real-time simulator (RTSIM and the results are tested.

Green-Frag: Energy-Efficient Frame Fragmentation Scheme for Wireless Sensor Networks

KAUST Repository

Daghistani, Anas H.

2013-05-15

Power management is an active area of research in wireless sensor networks (WSNs). Efficient power management is necessary because WSNs are battery-operated devices that can be deployed in mission-critical applications. From the communications perspective, one main approach to reduce energy is to maximize throughput so the data can be transmitted in a short amount of time. Frame fragmentation techniques aim to achieve higher throughput by reducing retransmissions. Using experiments on a WSN testbed, we show that frame fragmentation helps to reduce energy consumption. We then study and compare recent frame fragmentation schemes to find the most energy-efficient scheme. Our main contribution is to propose a new frame fragmentation scheme that is optimized to be energy efficient, which is originated from the chosen frame fragmentation scheme. This new energy-efficient frame fragmentation protocol is called (Green-Frag). Green-Frag uses an algorithm that gives sensor nodes the ability to transmit data with optimal transmit power and optimal frame structure based on environmental conditions. Green-Frag takes into consideration the channel conditions, interference patterns and level, as well as the distance between sender and receiver. The thesis discusses various design and implementation considerations for Green-Frag. Also, it shows empirical results of comparing Green-Frag with other frame fragmentation protocols in terms of energy efficiency. Green-Frag performance results shows that it is capable of choosing the best transmit according to the channel conditions. Subsequently, Green-Frag achieves the least energy consumption in all environmental conditions.

Energy Efficiency Resources to Support State Energy Planning

Energy Technology Data Exchange (ETDEWEB)

Office of Strategic Programs, Strategic Priorities and Impact Analysis Team

2017-06-01

An early step for most energy efficiency planning is to identify and quantify energy savings opportunities, and then to understand how to access this potential. The U.S. Department of Energy’s Office of Energy Efficiency and Renewable Energy offers resources that can help with both of these steps. This fact sheet presents those resources. The resources are also available on the DOE State and Local Solution Center on the "Energy Efficiency: Savings Opportunities and Benefits" page: https://energy.gov/eere/slsc/energy-efficiency-savings-opportunities-and-benefits.

A fitting algorithm based on simulated annealing techniques for efficiency calibration of HPGe detectors using different mathematical functions

Energy Technology Data Exchange (ETDEWEB)

Hurtado, S. [Servicio de Radioisotopos, Centro de Investigacion, Tecnologia e Innovacion (CITIUS), Universidad de Sevilla, Avda. Reina Mercedes s/n, 41012 Sevilla (Spain)], E-mail: shurtado@us.es; Garcia-Leon, M. [Departamento de Fisica Atomica, Molecular y Nuclear, Facultad de Fisica, Universidad de Sevilla, Aptd. 1065, 41080 Sevilla (Spain); Garcia-Tenorio, R. [Departamento de Fisica Aplicada II, E.T.S.A. Universidad de Sevilla, Avda, Reina Mercedes 2, 41012 Sevilla (Spain)

2008-09-11

In this work several mathematical functions are compared in order to perform the full-energy peak efficiency calibration of HPGe detectors using a 126cm{sup 3} HPGe coaxial detector and gamma-ray energies ranging from 36 to 1460 keV. Statistical tests and Monte Carlo simulations were used to study the performance of the fitting curve equations. Furthermore the fitting procedure of these complex functional forms to experimental data is a non-linear multi-parameter minimization problem. In gamma-ray spectrometry usually non-linear least-squares fitting algorithms (Levenberg-Marquardt method) provide a fast convergence while minimizing {chi}{sub R}{sup 2}, however, sometimes reaching only local minima. In order to overcome that shortcoming a hybrid algorithm based on simulated annealing (HSA) techniques is proposed. Additionally a new function is suggested that models the efficiency curve of germanium detectors in gamma-ray spectrometry.

Applied Distributed Model Predictive Control for Energy Efficient Buildings and Ramp Metering

Science.gov (United States)

Koehler, Sarah Muraoka

suited for nonlinear optimization problems. The parallel computation of the algorithm exploits iterative linear algebra methods for the main linear algebra computations in the algorithm. We show that the splitting of the algorithm is flexible and can thus be applied to various distributed platform configurations. The two proposed algorithms are applied to two main energy and transportation control problems. The first application is energy efficient building control. Buildings represent 40% of energy consumption in the United States. Thus, it is significant to improve the energy efficiency of buildings. The goal is to minimize energy consumption subject to the physics of the building (e.g. heat transfer laws), the constraints of the actuators as well as the desired operating constraints (thermal comfort of the occupants), and heat load on the system. In this thesis, we describe the control systems of forced air building systems in practice. We discuss the "Trim and Respond" algorithm which is a distributed control algorithm that is used in practice, and show that it performs similarly to a one-step explicit DMPC algorithm. Then, we apply the novel distributed primal-dual active-set method and provide extensive numerical results for the building MPC problem. The second main application is the control of ramp metering signals to optimize traffic flow through a freeway system. This application is particularly important since urban congestion has more than doubled in the past few decades. The ramp metering problem is to maximize freeway throughput subject to freeway dynamics (derived from mass conservation), actuation constraints, freeway capacity constraints, and predicted traffic demand. In this thesis, we develop a hybrid model predictive controller for ramp metering that is guaranteed to be persistently feasible and stable. This contrasts to previous work on MPC for ramp metering where such guarantees are absent. We apply a smoothing method to the hybrid model predictive

Efficient irregular wavefront propagation algorithms on Intel® Xeon Phi™

Science.gov (United States)

Gomes, Jeremias M.; Teodoro, George; de Melo, Alba; Kong, Jun; Kurc, Tahsin; Saltz, Joel H.

2016-01-01

We investigate the execution of the Irregular Wavefront Propagation Pattern (IWPP), a fundamental computing structure used in several image analysis operations, on the Intel® Xeon Phi™ co-processor. An efficient implementation of IWPP on the Xeon Phi is a challenging problem because of IWPP’s irregularity and the use of atomic instructions in the original IWPP algorithm to resolve race conditions. On the Xeon Phi, the use of SIMD and vectorization instructions is critical to attain high performance. However, SIMD atomic instructions are not supported. Therefore, we propose a new IWPP algorithm that can take advantage of the supported SIMD instruction set. We also evaluate an alternate storage container (priority queue) to track active elements in the wavefront in an effort to improve the parallel algorithm efficiency. The new IWPP algorithm is evaluated with Morphological Reconstruction and Imfill operations as use cases. Our results show performance improvements of up to 5.63× on top of the original IWPP due to vectorization. Moreover, the new IWPP achieves speedups of 45.7× and 1.62×, respectively, as compared to efficient CPU and GPU implementations. PMID:27298591

Efficient irregular wavefront propagation algorithms on Intel® Xeon Phi™.

Science.gov (United States)

Gomes, Jeremias M; Teodoro, George; de Melo, Alba; Kong, Jun; Kurc, Tahsin; Saltz, Joel H

2015-10-01

We investigate the execution of the Irregular Wavefront Propagation Pattern (IWPP), a fundamental computing structure used in several image analysis operations, on the Intel ® Xeon Phi ™ co-processor. An efficient implementation of IWPP on the Xeon Phi is a challenging problem because of IWPP's irregularity and the use of atomic instructions in the original IWPP algorithm to resolve race conditions. On the Xeon Phi, the use of SIMD and vectorization instructions is critical to attain high performance. However, SIMD atomic instructions are not supported. Therefore, we propose a new IWPP algorithm that can take advantage of the supported SIMD instruction set. We also evaluate an alternate storage container (priority queue) to track active elements in the wavefront in an effort to improve the parallel algorithm efficiency. The new IWPP algorithm is evaluated with Morphological Reconstruction and Imfill operations as use cases. Our results show performance improvements of up to 5.63 × on top of the original IWPP due to vectorization. Moreover, the new IWPP achieves speedups of 45.7 × and 1.62 × , respectively, as compared to efficient CPU and GPU implementations.

An Efficient Supervised Training Algorithm for Multilayer Spiking Neural Networks.

Science.gov (United States)

Xie, Xiurui; Qu, Hong; Liu, Guisong; Zhang, Malu; Kurths, Jürgen

2016-01-01

The spiking neural networks (SNNs) are the third generation of neural networks and perform remarkably well in cognitive tasks such as pattern recognition. The spike emitting and information processing mechanisms found in biological cognitive systems motivate the application of the hierarchical structure and temporal encoding mechanism in spiking neural networks, which have exhibited strong computational capability. However, the hierarchical structure and temporal encoding approach require neurons to process information serially in space and time respectively, which reduce the training efficiency significantly. For training the hierarchical SNNs, most existing methods are based on the traditional back-propagation algorithm, inheriting its drawbacks of the gradient diffusion and the sensitivity on parameters. To keep the powerful computation capability of the hierarchical structure and temporal encoding mechanism, but to overcome the low efficiency of the existing algorithms, a new training algorithm, the Normalized Spiking Error Back Propagation (NSEBP) is proposed in this paper. In the feedforward calculation, the output spike times are calculated by solving the quadratic function in the spike response model instead of detecting postsynaptic voltage states at all time points in traditional algorithms. Besides, in the feedback weight modification, the computational error is propagated to previous layers by the presynaptic spike jitter instead of the gradient decent rule, which realizes the layer-wised training. Furthermore, our algorithm investigates the mathematical relation between the weight variation and voltage error change, which makes the normalization in the weight modification applicable. Adopting these strategies, our algorithm outperforms the traditional SNN multi-layer algorithms in terms of learning efficiency and parameter sensitivity, that are also demonstrated by the comprehensive experimental results in this paper.

DTU International Energy Report 2012: Energy efficiency improvements

DEFF Research Database (Denmark)

Increased energy efficiency can reduce global CO2 emissions over the period to 2050 with up to 25%. On the top of that large profits can be gained for very little investment. Energy efficiency improvements can save investment in new energy infrastructure, cut fuel costs, increase competitiveness...... and increase consumer welfare. Thus, it is natural for DTU International Energy Report 2012 to take up this issue and analyze the global, regional and national challenges in exploiting energy efficiency and promote research and development in energy efficiency....

The Efficiency Analysis of the Augmented Reality Algorithm

Directory of Open Access Journals (Sweden)

Dovilė Kurpytė

2013-05-01

Full Text Available The article presents the investigation of the efficiency of augmented reality algorithm that depends on the rotation angles and lighting conditions. The following were the target subject parameters: three degrees of freedom perspective of the rotation and side lighting that forms a shadow. Static parameters of subjects with the ability to change them were as follow: the distance between the marker and the camera, camera, processor, and the distance from the light source. The study is based on an open source Java programming language algorithm, where the algorithm is tested with 10 markers. It was found that the rotation error did not exceed 2%.Article in Lithuanian

Energy Efficient Distributed Fault Identification Algorithm in Wireless Sensor Networks

Directory of Open Access Journals (Sweden)

Meenakshi Panda

2014-01-01

Full Text Available A distributed fault identification algorithm is proposed here to find both hard and soft faulty sensor nodes present in wireless sensor networks. The algorithm is distributed, self-detectable, and can detect the most common byzantine faults such as stuck at zero, stuck at one, and random data. In the proposed approach, each sensor node gathered the observed data from the neighbors and computed the mean to check whether faulty sensor node is present or not. If a node found the presence of faulty sensor node, then compares observed data with the data of the neighbors and predict probable fault status. The final fault status is determined by diffusing the fault information from the neighbors. The accuracy and completeness of the algorithm are verified with the help of statistical model of the sensors data. The performance is evaluated in terms of detection accuracy, false alarm rate, detection latency and message complexity.

Energy-Efficient Cluster Based Routing Protocol in Mobile Ad Hoc Networks Using Network Coding

Directory of Open Access Journals (Sweden)

Srinivas Kanakala

2014-01-01

Full Text Available In mobile ad hoc networks, all nodes are energy constrained. In such situations, it is important to reduce energy consumption. In this paper, we consider the issues of energy efficient communication in MANETs using network coding. Network coding is an effective method to improve the performance of wireless networks. COPE protocol implements network coding concept to reduce number of transmissions by mixing the packets at intermediate nodes. We incorporate COPE into cluster based routing protocol to further reduce the energy consumption. The proposed energy-efficient coding-aware cluster based routing protocol (ECCRP scheme applies network coding at cluster heads to reduce number of transmissions. We also modify the queue management procedure of COPE protocol to further improve coding opportunities. We also use an energy efficient scheme while selecting the cluster head. It helps to increase the life time of the network. We evaluate the performance of proposed energy efficient cluster based protocol using simulation. Simulation results show that the proposed ECCRP algorithm reduces energy consumption and increases life time of the network.

Statistical physics inspired energy-efficient coded-modulation for optical communications.

Science.gov (United States)

Djordjevic, Ivan B; Xu, Lei; Wang, Ting

2012-04-15

Because Shannon's entropy can be obtained by Stirling's approximation of thermodynamics entropy, the statistical physics energy minimization methods are directly applicable to the signal constellation design. We demonstrate that statistical physics inspired energy-efficient (EE) signal constellation designs, in combination with large-girth low-density parity-check (LDPC) codes, significantly outperform conventional LDPC-coded polarization-division multiplexed quadrature amplitude modulation schemes. We also describe an EE signal constellation design algorithm. Finally, we propose the discrete-time implementation of D-dimensional transceiver and corresponding EE polarization-division multiplexed system. © 2012 Optical Society of America

National energy efficiency programme

International Nuclear Information System (INIS)

Anon.

1992-01-01

This paper focusses on energy conservation and specifically on energy efficiency which includes efficiency in the production, delivery and utilisation of energy as part of the total energy system of the economy. A National Energy Efficiency Programme is being launched in the Eighth Plan that will take into account both macro level and policy and planning considerations as well as micro level responses for different category of users in the industry, agriculture, transport and domestic sectors. The need for such a National Energy Efficiency Programme after making an assessment of existing energy conservation activities in the country is discussed. The broad framework and contents of the National Energy Efficiency Programme have been outlined and the Eighth Plan targets for energy conservation and their break-up have been given. These targets, as per the Eighth Plan document are 5000 MW in electricity installed capacity and 6 million tonnes of petroleum products by the terminal year of the Eighth Plan. The issues that need to be examined for each sector for achieving the above targets for energy conservation in the Eighth Plan are discussed briefly. They are: (a) policy and planning, (b) implementation arrangements which include the institutional setup and selective legislation, (c) technological requirements, and (d) resource requirements which include human resources and financial resources. (author)

Life Cycle Network Modeling Framework and Solution Algorithms for Systems Analysis and Optimization of the Water-Energy Nexus

Directory of Open Access Journals (Sweden)

Daniel J. Garcia

2015-07-01

Full Text Available The water footprint of energy systems must be considered, as future water scarcity has been identified as a major concern. This work presents a general life cycle network modeling and optimization framework for energy-based products and processes using a functional unit of liters of water consumed in the processing pathway. We analyze and optimize the water-energy nexus over the objectives of water footprint minimization, maximization of economic output per liter of water consumed (economic efficiency of water, and maximization of energy output per liter of water consumed (energy efficiency of water. A mixed integer, multiobjective nonlinear fractional programming (MINLFP model is formulated. A mixed integer linear programing (MILP-based branch and refine algorithm that incorporates both the parametric algorithm and nonlinear programming (NLP subproblems is developed to boost solving efficiency. A case study in bioenergy is presented, and the water footprint is considered from biomass cultivation to biofuel production, providing a novel perspective into the consumption of water throughout the value chain. The case study, optimized successively over the three aforementioned objectives, utilizes a variety of candidate biomass feedstocks to meet primary fuel products demand (ethanol, diesel, and gasoline. A minimum water footprint of 55.1 ML/year was found, economic efficiencies of water range from −$1.31/L to $0.76/L, and energy efficiencies of water ranged from 15.32 MJ/L to 27.98 MJ/L. These results show optimization provides avenues for process improvement, as reported values for the energy efficiency of bioethanol range from 0.62 MJ/L to 3.18 MJ/L. Furthermore, the proposed solution approach was shown to be an order of magnitude more efficient than directly solving the original MINLFP problem with general purpose solvers.

An algorithm for testing the efficient market hypothesis.

Directory of Open Access Journals (Sweden)

Ioana-Andreea Boboc

Full Text Available The objective of this research is to examine the efficiency of EUR/USD market through the application of a trading system. The system uses a genetic algorithm based on technical analysis indicators such as Exponential Moving Average (EMA, Moving Average Convergence Divergence (MACD, Relative Strength Index (RSI and Filter that gives buying and selling recommendations to investors. The algorithm optimizes the strategies by dynamically searching for parameters that improve profitability in the training period. The best sets of rules are then applied on the testing period. The results show inconsistency in finding a set of trading rules that performs well in both periods. Strategies that achieve very good returns in the training period show difficulty in returning positive results in the testing period, this being consistent with the efficient market hypothesis (EMH.

An algorithm for testing the efficient market hypothesis.

Science.gov (United States)

Boboc, Ioana-Andreea; Dinică, Mihai-Cristian

2013-01-01

The objective of this research is to examine the efficiency of EUR/USD market through the application of a trading system. The system uses a genetic algorithm based on technical analysis indicators such as Exponential Moving Average (EMA), Moving Average Convergence Divergence (MACD), Relative Strength Index (RSI) and Filter that gives buying and selling recommendations to investors. The algorithm optimizes the strategies by dynamically searching for parameters that improve profitability in the training period. The best sets of rules are then applied on the testing period. The results show inconsistency in finding a set of trading rules that performs well in both periods. Strategies that achieve very good returns in the training period show difficulty in returning positive results in the testing period, this being consistent with the efficient market hypothesis (EMH).

An efficient algorithm to compute subsets of points in ℤ n

OpenAIRE

Pacheco Martínez, Ana María; Real Jurado, Pedro

2012-01-01

In this paper we show a more efficient algorithm than that in [8] to compute subsets of points non-congruent by isometries. This algorithm can be used to reconstruct the object from the digital image. Both algorithms are compared, highlighting the improvements obtained in terms of CPU time.

Efficient sequential and parallel algorithms for record linkage.

Science.gov (United States)

Mamun, Abdullah-Al; Mi, Tian; Aseltine, Robert; Rajasekaran, Sanguthevar

2014-01-01

Integrating data from multiple sources is a crucial and challenging problem. Even though there exist numerous algorithms for record linkage or deduplication, they suffer from either large time needs or restrictions on the number of datasets that they can integrate. In this paper we report efficient sequential and parallel algorithms for record linkage which handle any number of datasets and outperform previous algorithms. Our algorithms employ hierarchical clustering algorithms as the basis. A key idea that we use is radix sorting on certain attributes to eliminate identical records before any further processing. Another novel idea is to form a graph that links similar records and find the connected components. Our sequential and parallel algorithms have been tested on a real dataset of 1,083,878 records and synthetic datasets ranging in size from 50,000 to 9,000,000 records. Our sequential algorithm runs at least two times faster, for any dataset, than the previous best-known algorithm, the two-phase algorithm using faster computation of the edit distance (TPA (FCED)). The speedups obtained by our parallel algorithm are almost linear. For example, we get a speedup of 7.5 with 8 cores (residing in a single node), 14.1 with 16 cores (residing in two nodes), and 26.4 with 32 cores (residing in four nodes). We have compared the performance of our sequential algorithm with TPA (FCED) and found that our algorithm outperforms the previous one. The accuracy is the same as that of this previous best-known algorithm.

The Energy-Efficient Operation Problem of a Freight Train Considering Long-Distance Steep Downhill Sections

Directory of Open Access Journals (Sweden)

Xuan Lin

2017-06-01

Full Text Available With the energy consumption rising in rail transport, the railway sector is showing increasing interest in the energy-efficient operation of freight trains. Freight trains require more complicated driving strategies than ordinary passenger trains do due to their heavy loads, especially in the long-distance steep downhill (LDSD sections that are very common in freight rail lines in China. This paper studies the energy-efficient operation of a freight train considering LDSD sections. An optimal control model including regenerative and pneumatic braking is developed for the freight train. Then, when a train leaves/enters the LDSD section, we verify the uniqueness of control transitions and discuss the speed profile linkage between LDSD and its adjacent sections, which indicates that the periodic braking should be applied on LDSD sections for optimality. Additionally, given the same running time for the entire journey, our analysis shows that electrical braking-full braking strategy is more energy-efficient than coasting-full braking strategy on LDSD sections. Finally, a numerical algorithm for the optimal driving solution is proposed. The simulation results demonstrate that the driving strategies generated by the proposed algorithm performs better than those from fuzzy predictive control and field operation regarding energy saving.

Energy efficiency in the world and Turkey and investigation of energy efficiency in Turkish Industry

International Nuclear Information System (INIS)

Kavak, K.

2005-09-01

The reserves of fossil fuels which currently respond to the major part of world energy requirements are being running out very fast. Because it is forecasted that reserves of some fossil fuels like oil and natural gas will come to an end in the second half of this century, exploiting all energy resources in an efficient manner has great importance. Throughout the world where the energy demand grows continuously but the resources decrease gradually, many types of programs are implemented to provide efficient energy use. In Turkey, although there have been some efforts in last two decades, the importance of the issue could not be undersood yet. Turkey'sgeneral energy policy still focuses on supply security and finding ways to meet the growing demand, rather than decreasing the demand by energy efficiency. In this study, the possible opportunities and benefits that Turkey would gain by energy efficiency is pointed out. The studies about energy efficiency which have been conducted in the world and Turkey are examined. The measurement that can be taken in the sectors such as industry, power plants, buildings, transportation and the utilities of these measures for energy economy are indicated. The successful practices of energy efficiency studies in various countries, the state of some countries which pioneer efficiency implementations. Turkey's situation in energy in the light of basic indicators such as energy consumption per capita and enrgy intensity, the energy efficiency studies that have been done and should be done in various sectors of Turkey are also discussed in this thesis. Turkish industry's energy comsumption is analyzed as a seperate chapter by taking into consideration energy efficiency, energy intensity and energy resources. The general energy consumption and energy intensity tendencies of main manufacturing industries between 1995 and 2002 are explored and resource utilization ratios are investigated. This chapter provides to find out what kind of

Efficient Actor-Critic Algorithm with Hierarchical Model Learning and Planning

Science.gov (United States)

Fu, QiMing

2016-01-01

To improve the convergence rate and the sample efficiency, two efficient learning methods AC-HMLP and RAC-HMLP (AC-HMLP with ℓ 2-regularization) are proposed by combining actor-critic algorithm with hierarchical model learning and planning. The hierarchical models consisting of the local and the global models, which are learned at the same time during learning of the value function and the policy, are approximated by local linear regression (LLR) and linear function approximation (LFA), respectively. Both the local model and the global model are applied to generate samples for planning; the former is used only if the state-prediction error does not surpass the threshold at each time step, while the latter is utilized at the end of each episode. The purpose of taking both models is to improve the sample efficiency and accelerate the convergence rate of the whole algorithm through fully utilizing the local and global information. Experimentally, AC-HMLP and RAC-HMLP are compared with three representative algorithms on two Reinforcement Learning (RL) benchmark problems. The results demonstrate that they perform best in terms of convergence rate and sample efficiency. PMID:27795704

Energy efficiency and behaviour

DEFF Research Database (Denmark)

Carstensen, Trine Agervig; Kunnasvirta, Annika; Kiviluoto, Katariina

separate key aspects hinders strategic energy efficiency planning. For this reason, the PLEEC project – “Planning for Energy Efficient Cities” – funded by the EU Seventh Framework Programme uses an integrative approach to achieve the sus‐ tainable, energy– efficient, smart city. By coordinating strategies...... to conduct behavioural interventions, to be presented in Deliverable 5.5., the final report. This report will also provide valuable information for the WP6 general model for an Energy-Smart City. Altogether 38 behavioural interventions are analysed in this report. Each collected and analysed case study...... of the European Union’s 20‐20‐20 plan is to improve energy efficiency by 20% in 2020. However, holistic knowledge about energy efficiency potentials in cities is far from complete. Currently, a WP4 location in PLEEC project page 3 variety of individual strategies and approaches by different stakeholders tackling...

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.

Efficient sequential and parallel algorithms for finding edit distance based motifs.

Science.gov (United States)

Pal, Soumitra; Xiao, Peng; Rajasekaran, Sanguthevar

2016-08-18

Motif search is an important step in extracting meaningful patterns from biological data. The general problem of motif search is intractable and there is a pressing need to develop efficient, exact and approximation algorithms to solve this problem. In this paper, we present several novel, exact, sequential and parallel algorithms for solving the (l,d) Edit-distance-based Motif Search (EMS) problem: given two integers l,d and n biological strings, find all strings of length l that appear in each input string with atmost d errors of types substitution, insertion and deletion. One popular technique to solve the problem is to explore for each input string the set of all possible l-mers that belong to the d-neighborhood of any substring of the input string and output those which are common for all input strings. We introduce a novel and provably efficient neighborhood exploration technique. We show that it is enough to consider the candidates in neighborhood which are at a distance exactly d. We compactly represent these candidate motifs using wildcard characters and efficiently explore them with very few repetitions. Our sequential algorithm uses a trie based data structure to efficiently store and sort the candidate motifs. Our parallel algorithm in a multi-core shared memory setting uses arrays for storing and a novel modification of radix-sort for sorting the candidate motifs. The algorithms for EMS are customarily evaluated on several challenging instances such as (8,1), (12,2), (16,3), (20,4), and so on. The best previously known algorithm, EMS1, is sequential and in estimated 3 days solves up to instance (16,3). Our sequential algorithms are more than 20 times faster on (16,3). On other hard instances such as (9,2), (11,3), (13,4), our algorithms are much faster. Our parallel algorithm has more than 600 % scaling performance while using 16 threads. Our algorithms have pushed up the state-of-the-art of EMS solvers and we believe that the techniques introduced in

Spectral-Efficiency - Illumination Pareto Front for Energy Harvesting Enabled VLC System

KAUST Repository

Abdelhady, Amr Mohamed Abdelaziz

2017-12-13

The continuous improvement in optical energy harvesting devices motivates visible light communication (VLC) system developers to utilize such available free energy sources. An outdoor VLC system is considered where an optical base station sends data to multiple users that are capable of harvesting the optical energy. The proposed VLC system serves multiple users using time division multiple access (TDMA) with unequal time and power allocation, which are allocated to improve the system performance. The adopted optical system provides users with illumination and data communication services. The outdoor optical design objective is to maximize the illumination, while the communication design objective is to maximize the spectral efficiency (SE). The design objectives are shown to be conflicting, therefore, a multiobjective optimization problem is formulated to obtain the Pareto front performance curve for the proposed system. To this end, the marginal optimization problems are solved first using low complexity algorithms. Then, based on the proposed algorithms, a low complexity algorithm is developed to obtain an inner bound of the Pareto front for the illumination-SE tradeoff. The inner bound for the Pareto-front is shown to be close to the optimal Pareto-frontier via several simulation scenarios for different system parameters.

Efficient algorithms for conditional independence inference

Czech Academy of Sciences Publication Activity Database

Bouckaert, R.; Hemmecke, R.; Lindner, S.; Studený, Milan

2010-01-01

Roč. 11, č. 1 (2010), s. 3453-3479 ISSN 1532-4435 R&D Projects: GA ČR GA201/08/0539; GA MŠk 1M0572 Institutional research plan: CEZ:AV0Z10750506 Keywords : conditional independence inference * linear programming approach Subject RIV: BA - General Mathematics Impact factor: 2.949, year: 2010 http://library.utia.cas.cz/separaty/2010/MTR/studeny-efficient algorithms for conditional independence inference.pdf

Neural network fusion capabilities for efficient implementation of tracking algorithms

Science.gov (United States)

Sundareshan, Malur K.; Amoozegar, Farid

1997-03-01

The ability to efficiently fuse information of different forms to facilitate intelligent decision making is one of the major capabilities of trained multilayer neural networks that is now being recognized. While development of innovative adaptive control algorithms for nonlinear dynamical plants that attempt to exploit these capabilities seems to be more popular, a corresponding development of nonlinear estimation algorithms using these approaches, particularly for application in target surveillance and guidance operations, has not received similar attention. We describe the capabilities and functionality of neural network algorithms for data fusion and implementation of tracking filters. To discuss details and to serve as a vehicle for quantitative performance evaluations, the illustrative case of estimating the position and velocity of surveillance targets is considered. Efficient target- tracking algorithms that can utilize data from a host of sensing modalities and are capable of reliably tracking even uncooperative targets executing fast and complex maneuvers are of interest in a number of applications. The primary motivation for employing neural networks in these applications comes from the efficiency with which more features extracted from different sensor measurements can be utilized as inputs for estimating target maneuvers. A system architecture that efficiently integrates the fusion capabilities of a trained multilayer neural net with the tracking performance of a Kalman filter is described. The innovation lies in the way the fusion of multisensor data is accomplished to facilitate improved estimation without increasing the computational complexity of the dynamical state estimator itself.

Energy efficiency: Lever for the Energy Transition

International Nuclear Information System (INIS)

2012-12-01

The Eco-electric industry group (FFIE, FGME, Gimelec, IGNES, SERCE) has conducted a study to evaluate the energy saving potential of active energy efficiency solutions in the residential and commercial building sectors. Based on field implementations and demonstrators, it has been demonstrated that active energy efficiency can sustainably achieve substantial savings for households, companies and public authorities. Energy Efficiency - Lever for the energy transition presents the results and conclusions of that study, alongside with recommendations for public authority in terms of building retrofit policy for putting France on the best possible 'trajectory' from a budgetary and environmental point of view. (author)

Multi-Train Energy Saving for Maximum Usage of Regenerative Energy by Dwell Time Optimization in Urban Rail Transit Using Genetic Algorithm

Directory of Open Access Journals (Sweden)

Fei Lin

2016-03-01

Full Text Available With its large capacity, the total urban rail transit energy consumption is very high; thus, energy saving operations are quite meaningful. The effective use of regenerative braking energy is the mainstream method for improving the efficiency of energy saving. This paper examines the optimization of train dwell time and builds a multiple train operation model for energy conservation of a power supply system. By changing the dwell time, the braking energy can be absorbed and utilized by other traction trains as efficiently as possible. The application of genetic algorithms is proposed for the optimization, based on the current schedule. Next, to validate the correctness and effectiveness of the optimization, a real case is studied. Actual data from the Beijing subway Yizhuang Line are employed to perform the simulation, and the results indicate that the optimization method of the dwell time is effective.

An Energy-Efficient Link with Adaptive Transmit Power Control for Long Range Networks

DEFF Research Database (Denmark)

Lynggaard, P.; Blaszczyk, Tomasz

2016-01-01

A considerable amount of research is carried out to develop a reliable smart sensor system with high energy efficiency for battery operated wireless IoT devices in the agriculture sector. However, only a limited amount of research has covered automatic transmission power adjustment schemes...... and algorithms which are essential for deployment of wireless IoT nodes. This paper presents an adaptive link algorithm for farm applications with emphasis on power adjustment for long range communication networks....

Energy technologies and energy efficiency in economic modelling

DEFF Research Database (Denmark)

Klinge Jacobsen, Henrik

1998-01-01

This paper discusses different approaches to incorporating energy technologies and technological development in energy-economic models. Technological development is a very important issue in long-term energy demand projections and in environmental analyses. Different assumptions on technological ...... of renewable energy and especially wind power will increase the rate of efficiency improvement. A technologically based model in this case indirectly makes the energy efficiency endogenous in the aggregate energy-economy model....... technological development. This paper examines the effect on aggregate energy efficiency of using technological models to describe a number of specific technologies and of incorporating these models in an economic model. Different effects from the technology representation are illustrated. Vintage effects...... illustrates the dependence of average efficiencies and productivity on capacity utilisation rates. In the long run regulation induced by environmental policies are also very important for the improvement of aggregate energy efficiency in the energy supply sector. A Danish policy to increase the share...

Design for energy efficiency: Energy efficient industrialized housing research program. Progress report

Energy Technology Data Exchange (ETDEWEB)

Kellett, R.; Berg, R.; Paz, A.; Brown, G.Z.

1991-03-01

Since 1989, the U.S. Department of Energy has sponsored the Energy Efficient Industrialized Housing research program (EEIH) to improve the energy efficiency of industrialized housing. Two research centers share responsibility for this program: The Center for Housing Innovation at the University of Oregon and the Florida Solar Energy Center, a research institute of the University of Central Florida. Additional funding is provided through the participation of private industry, state governments and utilities. The program is guided by a steering committee comprised of industry and government representatives. This report summarizes Fiscal Year (FY) 1990 activities and progress, and proposed activities for FY 1991 in Task 2.1 Design for Energy Efficiency. This task establishes a vision of energy conservation opportunities in critical regions, market segments, climate zones and manufacturing strategies significant to industrialized housing in the 21st Century. In early FY 1990, four problem statements were developed to define future housing demand scenarios inclusive of issues of energy efficiency, housing design and manufacturing. Literature surveys were completed to assess seven areas of influence for industrialized housing and energy conservation in the future. Fifty-five future trends were identified in computing and design process; manufacturing process; construction materials, components and systems; energy and environment; demographic context; economic context; and planning policy and regulatory context.

Symbolic BDD and ADD Algorithms for Energy Games

Directory of Open Access Journals (Sweden)

Shahar Maoz

2016-11-01

Full Text Available Energy games, which model quantitative consumption of a limited resource, e.g., time or energy, play a central role in quantitative models for reactive systems. Reactive synthesis constructs a controller which satisfies a given specification, if one exists. For energy games a synthesized controller ensures to satisfy not only the safety constraints of the specification but also the quantitative constraints expressed in the energy game. A symbolic algorithm for energy games, recently presented by Chatterjee et al., is symbolic in its representation of quantitative values but concrete in the representation of game states and transitions. In this paper we present an algorithm that is symbolic both in the quantitative values and in the underlying game representation. We have implemented our algorithm using two different symbolic representations for reactive games, Binary Decision Diagrams (BDD and Algebraic Decision Diagrams (ADD. We investigate the commonalities and differences of the two implementations and compare their running times on specifications of energy games.

Generalized-ensemble molecular dynamics and Monte Carlo algorithms beyond the limit of the multicanonical algorithm

International Nuclear Information System (INIS)

Okumura, Hisashi

2010-01-01

I review two new generalized-ensemble algorithms for molecular dynamics and Monte Carlo simulations of biomolecules, that is, the multibaric–multithermal algorithm and the partial multicanonical algorithm. In the multibaric–multithermal algorithm, two-dimensional random walks not only in the potential-energy space but also in the volume space are realized. One can discuss the temperature dependence and pressure dependence of biomolecules with this algorithm. The partial multicanonical simulation samples a wide range of only an important part of potential energy, so that one can concentrate the effort to determine a multicanonical weight factor only on the important energy terms. This algorithm has higher sampling efficiency than the multicanonical and canonical algorithms. (review)

Resource allocation for phantom cellular networks: Energy efficiency vs spectral efficiency

KAUST Repository

Abdelhady, Amr Mohamed Abdelaziz; Amin, Osama; Alouini, Mohamed-Slim

2016-01-01

Multi-tier heterogeneous networks have become an essential constituent for next generation cellular networks. Mean-while, energy efficiency (EE) has been considered a critical design criterion along with the traditional spectral efficiency (SE) metric. In this context, we study power and spectrum allocation for the recently proposed two-tier network architecture known as phantom cellular networks. The optimization framework includes both EE and SE, where we propose an algorithm that finds the SE and EE resource allocation strategies for phantom cellular networks. Then, we compare the performance of both design strategies versus the number of users, and phantom cells share of the total number of available resource blocks. We aim to investigate the effect of some system parameters to achieve improved SE performance at a non-significant loss in EE performance, or vice versa. It was found that increasing phantom cells share of resource blocks decreases the SE performance loss due to EE optimization when compared with the optimized SE performance. © 2016 IEEE.

Resource allocation for phantom cellular networks: Energy efficiency vs spectral efficiency

KAUST Repository

Abdelhady, Amr M.

2016-07-26

Multi-tier heterogeneous networks have become an essential constituent for next generation cellular networks. Mean-while, energy efficiency (EE) has been considered a critical design criterion along with the traditional spectral efficiency (SE) metric. In this context, we study power and spectrum allocation for the recently proposed two-tier network architecture known as phantom cellular networks. The optimization framework includes both EE and SE, where we propose an algorithm that finds the SE and EE resource allocation strategies for phantom cellular networks. Then, we compare the performance of both design strategies versus the number of users, and phantom cells share of the total number of available resource blocks. We aim to investigate the effect of some system parameters to achieve improved SE performance at a non-significant loss in EE performance, or vice versa. It was found that increasing phantom cells share of resource blocks decreases the SE performance loss due to EE optimization when compared with the optimized SE performance. © 2016 IEEE.

Efficient Parallel Algorithms for Unsteady Incompressible Flows

KAUST Repository

Guermond, Jean-Luc; Minev, Peter D.

2013-01-01

The objective of this paper is to give an overview of recent developments on splitting schemes for solving the time-dependent incompressible Navier–Stokes equations and to discuss possible extensions to the variable density/viscosity case. A particular attention is given to algorithms that can be implemented efficiently on large parallel clusters.

A High-Efficiency Uneven Cluster Deployment Algorithm Based on Network Layered for Event Coverage in UWSNs

Directory of Open Access Journals (Sweden)

Shanen Yu

2016-12-01

Full Text Available Most existing deployment algorithms for event coverage in underwater wireless sensor networks (UWSNs usually do not consider that network communication has non-uniform characteristics on three-dimensional underwater environments. Such deployment algorithms ignore that the nodes are distributed at different depths and have different probabilities for data acquisition, thereby leading to imbalances in the overall network energy consumption, decreasing the network performance, and resulting in poor and unreliable late network operation. Therefore, in this study, we proposed an uneven cluster deployment algorithm based network layered for event coverage. First, according to the energy consumption requirement of the communication load at different depths of the underwater network, we obtained the expected value of deployment nodes and the distribution density of each layer network after theoretical analysis and deduction. Afterward, the network is divided into multilayers based on uneven clusters, and the heterogeneous communication radius of nodes can improve the network connectivity rate. The recovery strategy is used to balance the energy consumption of nodes in the cluster and can efficiently reconstruct the network topology, which ensures that the network has a high network coverage and connectivity rate in a long period of data acquisition. Simulation results show that the proposed algorithm improves network reliability and prolongs network lifetime by significantly reducing the blind movement of overall network nodes while maintaining a high network coverage and connectivity rate.

The Energy Efficient Enterprise

Energy Technology Data Exchange (ETDEWEB)

Ahmad, Bashir

2010-09-15

Since rising energy costs have become a crucial factor for the economy of production processes, the optimization of energy efficiency is of essential importance for industrial enterprises. Enterprises establish energy saving programs, specific to their needs. The most important elements of these energy efficiency programs are energy savings, energy controlling, energy optimization, and energy management. This article highlights the industrial enterprise approach to establish sustainable energy management programs based on the above elements. Globally, if organizations follow this approach, they can significantly reduce the overall energy consumption and cost.

The energy-efficiency business - Energy utility strategies

International Nuclear Information System (INIS)

Loebbe, S.

2009-01-01

This article takes a look at the energy-efficiency business and the advantages it offers. The author quotes that energy-efficiency can contribute to making savings in primary energy, minimise the economic impact of global warming, improve reliability of supply and protect the gross national product. The advantages of new products for the efficient use of energy are reviewed and the resulting advantages for power customers are noted. Also, possibilities for the positioning of electricity suppliers in the environmental niche is noted. The partial markets involved and estimates concerning the impact of energy-efficiency measures are reviewed. Climate protection, co-operation with energy agencies, consulting services and public relations aspects are also discussed. The prerequisites for successful marketing by the utilities are examined and new business models are discussed along with the clear strategies needed. The development from an electricity utility to a system-competence partner is reviewed

Energy efficiency: from principles to reality

International Nuclear Information System (INIS)

Baudry, Paul; Ballot-Miguel, Benedicte; Binet, Guillaume; Bordigoni, Mathieu; Decellas, Fabrice; Hauser, Chantal; Hita, Laurent; Laurent, Marie-Helene; Osso, Dominique; Peureux, Jean-Louis; Pham Van Cang, Christian

2015-01-01

This collective publication proposes a comprehensive overview of issues related to energy efficiency: associated stakes, methods of assessment of energy savings and of their costs, methods of action for energy efficiency policies, application in the housing, office building and industry sectors based on energy consumption modes in these different sectors, and main technologies aimed at improving energy efficiency. The first chapter proposes an historical perspective on energy, outlines the crucial role of energy efficiency in today's and tomorrow's contexts, and discusses which are the different levers of action to increase this efficiency. The next chapters address methods of assessment of energy efficiency, identify and discuss the use of different potential sources of energy saving, propose an overview of the various objectives and instruments of policies for energy efficiency, and address the issue of energy efficiency in the housing sector, in the office building sector, and in the industry sector by indicating the current levels of energy consumption, by identifying the various potential sources of energy saving, and by indicating available technologies aimed at improving energy efficiency

Where-Fi: a dynamic energy-efficient multimedia distribution framework for MANETs

Science.gov (United States)

Mohapatra, Shivajit; Carbunar, Bogdan; Pearce, Michael; Chaudhri, Rohit; Vasudevan, Venu

2008-01-01

Next generation mobile ad-hoc applications will revolve around users' need for sharing content/presence information with co-located devices. However, keeping such information fresh requires frequent meta-data exchanges, which could result in significant energy overheads. To address this issue, we propose distributed algorithms for energy efficient dissemination of presence and content usage information between nodes in mobile ad-hoc networks. First, we introduce a content dissemination protocol (called CPMP) for effectively distributing frequent small meta-data updates between co-located devices using multicast. We then develop two distributed algorithms that use the CPMP protocol to achieve "phase locked" wake up cycles for all the participating nodes in the network. The first algorithm is designed for fully-connected networks and then extended in the second to handle hidden terminals. The "phase locked" schedules are then exploited to adaptively transition the network interface to a deep sleep state for energy savings. We have implemented a prototype system (called "Where-Fi") on several Motorola Linux-based cell phone models. Our experimental results show that for all network topologies our algorithms were able to achieve "phase locking" between nodes even in the presence of hidden terminals. Moreover, we achieved battery lifetime extensions of as much as 28% for fully connected networks and about 20% for partially connected networks.

Energy efficient smartphone-based activity recognition using fixed-point arithmetic

OpenAIRE

Anguita, Davide; Ghio, Alessandro; Oneto, Luca; Llanas Parra, Francesc Xavier; Reyes Ortiz, Jorge Luis

2013-01-01

In this paper we propose a novel energy efficient approach for the recognition of human activities using smartphones as wearable sensing devices, targeting assisted living applications such as remote patient activity monitoring for the disabled and the elderly. The method exploits fixed-point arithmetic to propose a modified multiclass Support Vector Machine (SVM) learning algorithm, allowing to better pre- serve the smartphone battery lifetime with respect to the conventional flo...

Energy efficiency in Norway (1997). Cross Country Comparison on Energy Efficiency Indicators - Phase 5

Energy Technology Data Exchange (ETDEWEB)

Alm, Leif Kristian

2000-02-01

This is the national report for Norway in phase 5 of the SAVE project 'Cross country comparison of energy efficiency indicators'. The report deals with energy use and energy efficiency in Norway the last 20 years, with a special emphasis on the period after 1990. A detailed sector analysis has been done, applying Laspeyres indices to attribute changes in energy use to either activity, structure or intensity (efficiency). Aggregating sectors, we have found a total efficiency improvement of maximum 7-8 TWH from 1990 to 1997. This corresponds to a saving of 0.5% per year. In the same period, final energy use per Gross Domestic Product (GDP) was reduced by approx 2.4% per year. Thereby most of the reduction in final energy intensity can not be attributed to increased energy efficiency. Almost all data are taken from official Norwegian statistics (Statistics Norway). (author)

Energy conservation in industrial buildings. Higher energy efficiency with smart control systems; Energieeinsparung im Gewerbebau. Hoehere Energieeffizienz durch 'intelligente' Regeltechnik

Energy Technology Data Exchange (ETDEWEB)

Mayer, Edgar [CentraLine c/o Honeywell GmbH, Schoenaich (Germany)

2009-07-01

With smart control systems, the energy conservation potential of industrial buildings could be fully utilized. This means, e.g., that classic control algorithms must be replaced by new solutions. New methods will ensure higher energy efficiency with maximum comfort; they will also prolong the service life and the inspection intervals of the technical facilities. (orig.)

An efficient fractal image coding algorithm using unified feature and DCT

International Nuclear Information System (INIS)

Zhou Yiming; Zhang Chao; Zhang Zengke

2009-01-01

Fractal image compression is a promising technique to improve the efficiency of image storage and image transmission with high compression ratio, however, the huge time consumption for the fractal image coding is a great obstacle to the practical applications. In order to improve the fractal image coding, efficient fractal image coding algorithms using a special unified feature and a DCT coder are proposed in this paper. Firstly, based on a necessary condition to the best matching search rule during fractal image coding, the fast algorithm using a special unified feature (UFC) is addressed, and it can reduce the search space obviously and exclude most inappropriate matching subblocks before the best matching search. Secondly, on the basis of UFC algorithm, in order to improve the quality of the reconstructed image, a DCT coder is combined to construct a hybrid fractal image algorithm (DUFC). Experimental results show that the proposed algorithms can obtain good quality of the reconstructed images and need much less time than the baseline fractal coding algorithm.

Research on Energy-Saving Production Scheduling Based on a Clustering Algorithm for a Forging Enterprise

Directory of Open Access Journals (Sweden)

Yifei Tong

2016-02-01

Full Text Available Energy efficiency is a buzzword of the 21st century. With the ever growing need for energy efficient and low-carbon production, it is a big challenge for high energy-consumption enterprises to reduce their energy consumption. To this aim, a forging enterprise, DVR (the abbreviation of a forging enterprise, is researched. Firstly, an investigation into the production processes of DVR is given as well as an analysis of forging production. Then, the energy-saving forging scheduling is decomposed into two sub-problems. One is for cutting and machining scheduling, which is similar to traditional machining scheduling. The other one is for forging and heat treatment scheduling. Thirdly, former forging production scheduling is presented and solved based on an improved genetic algorithm. Fourthly, the latter is discussed in detail, followed by proposed dynamic clustering and stacking combination optimization. The proposed stacking optimization requires making the gross weight of forgings as close to the maximum batch capacity as possible. The above research can help reduce the heating times, and increase furnace utilization with high energy efficiency and low carbon emissions.

An efficient polyenergetic SART (pSART) reconstruction algorithm for quantitative myocardial CT perfusion

Energy Technology Data Exchange (ETDEWEB)

Lin, Yuan, E-mail: yuan.lin@duke.edu; Samei, Ehsan [Carl E. Ravin Advanced Imaging Laboratories, Duke University Medical Center, 2424 Erwin Road, Suite 302, Durham, North Carolina 27705 (United States)

2014-02-15

Purpose: In quantitative myocardial CT perfusion imaging, beam hardening effect due to dense bone and high concentration iodinated contrast agent can result in visible artifacts and inaccurate CT numbers. In this paper, an efficient polyenergetic Simultaneous Algebraic Reconstruction Technique (pSART) was presented to eliminate the beam hardening artifacts and to improve the CT quantitative imaging ability. Methods: Our algorithm made threea priori assumptions: (1) the human body is composed of several base materials (e.g., fat, breast, soft tissue, bone, and iodine); (2) images can be coarsely segmented to two types of regions, i.e., nonbone regions and noniodine regions; and (3) each voxel can be decomposed into a mixture of two most suitable base materials according to its attenuation value and its corresponding region type information. Based on the above assumptions, energy-independent accumulated effective lengths of all base materials can be fast computed in the forward ray-tracing process and be used repeatedly to obtain accurate polyenergetic projections, with which a SART-based equation can correctly update each voxel in the backward projecting process to iteratively reconstruct artifact-free images. This approach effectively reduces the influence of polyenergetic x-ray sources and it further enables monoenergetic images to be reconstructed at any arbitrarily preselected target energies. A series of simulation tests were performed on a size-variable cylindrical phantom and a realistic anthropomorphic thorax phantom. In addition, a phantom experiment was also performed on a clinical CT scanner to further quantitatively validate the proposed algorithm. Results: The simulations with the cylindrical phantom and the anthropomorphic thorax phantom showed that the proposed algorithm completely eliminated beam hardening artifacts and enabled quantitative imaging across different materials, phantom sizes, and spectra, as the absolute relative errors were reduced

An efficient polyenergetic SART (pSART) reconstruction algorithm for quantitative myocardial CT perfusion

International Nuclear Information System (INIS)

Lin, Yuan; Samei, Ehsan

2014-01-01

Purpose: In quantitative myocardial CT perfusion imaging, beam hardening effect due to dense bone and high concentration iodinated contrast agent can result in visible artifacts and inaccurate CT numbers. In this paper, an efficient polyenergetic Simultaneous Algebraic Reconstruction Technique (pSART) was presented to eliminate the beam hardening artifacts and to improve the CT quantitative imaging ability. Methods: Our algorithm made threea priori assumptions: (1) the human body is composed of several base materials (e.g., fat, breast, soft tissue, bone, and iodine); (2) images can be coarsely segmented to two types of regions, i.e., nonbone regions and noniodine regions; and (3) each voxel can be decomposed into a mixture of two most suitable base materials according to its attenuation value and its corresponding region type information. Based on the above assumptions, energy-independent accumulated effective lengths of all base materials can be fast computed in the forward ray-tracing process and be used repeatedly to obtain accurate polyenergetic projections, with which a SART-based equation can correctly update each voxel in the backward projecting process to iteratively reconstruct artifact-free images. This approach effectively reduces the influence of polyenergetic x-ray sources and it further enables monoenergetic images to be reconstructed at any arbitrarily preselected target energies. A series of simulation tests were performed on a size-variable cylindrical phantom and a realistic anthropomorphic thorax phantom. In addition, a phantom experiment was also performed on a clinical CT scanner to further quantitatively validate the proposed algorithm. Results: The simulations with the cylindrical phantom and the anthropomorphic thorax phantom showed that the proposed algorithm completely eliminated beam hardening artifacts and enabled quantitative imaging across different materials, phantom sizes, and spectra, as the absolute relative errors were reduced

Energy-Efficient Control with Harvesting Predictions for Solar-Powered Wireless Sensor Networks.

Science.gov (United States)

Zou, Tengyue; Lin, Shouying; Feng, Qijie; Chen, Yanlian

2016-01-04

Wireless sensor networks equipped with rechargeable batteries are useful for outdoor environmental monitoring. However, the severe energy constraints of the sensor nodes present major challenges for long-term applications. To achieve sustainability, solar cells can be used to acquire energy from the environment. Unfortunately, the energy supplied by the harvesting system is generally intermittent and considerably influenced by the weather. To improve the energy efficiency and extend the lifetime of the networks, we propose algorithms for harvested energy prediction using environmental shadow detection. Thus, the sensor nodes can adjust their scheduling plans accordingly to best suit their energy production and residual battery levels. Furthermore, we introduce clustering and routing selection methods to optimize the data transmission, and a Bayesian network is used for warning notifications of bottlenecks along the path. The entire system is implemented on a real-time Texas Instruments CC2530 embedded platform, and the experimental results indicate that these mechanisms sustain the networks' activities in an uninterrupted and efficient manner.

Energy-Efficient Control with Harvesting Predictions for Solar-Powered Wireless Sensor Networks

Directory of Open Access Journals (Sweden)

Tengyue Zou

2016-01-01

Full Text Available Wireless sensor networks equipped with rechargeable batteries are useful for outdoor environmental monitoring. However, the severe energy constraints of the sensor nodes present major challenges for long-term applications. To achieve sustainability, solar cells can be used to acquire energy from the environment. Unfortunately, the energy supplied by the harvesting system is generally intermittent and considerably influenced by the weather. To improve the energy efficiency and extend the lifetime of the networks, we propose algorithms for harvested energy prediction using environmental shadow detection. Thus, the sensor nodes can adjust their scheduling plans accordingly to best suit their energy production and residual battery levels. Furthermore, we introduce clustering and routing selection methods to optimize the data transmission, and a Bayesian network is used for warning notifications of bottlenecks along the path. The entire system is implemented on a real-time Texas Instruments CC2530 embedded platform, and the experimental results indicate that these mechanisms sustain the networks’ activities in an uninterrupted and efficient manner.

Improving the energy efficiency of sparse linear system solvers on multicore and manycore systems.

Science.gov (United States)

Anzt, H; Quintana-Ortí, E S

2014-06-28

While most recent breakthroughs in scientific research rely on complex simulations carried out in large-scale supercomputers, the power draft and energy spent for this purpose is increasingly becoming a limiting factor to this trend. In this paper, we provide an overview of the current status in energy-efficient scientific computing by reviewing different technologies used to monitor power draft as well as power- and energy-saving mechanisms available in commodity hardware. For the particular domain of sparse linear algebra, we analyse the energy efficiency of a broad collection of hardware architectures and investigate how algorithmic and implementation modifications can improve the energy performance of sparse linear system solvers, without negatively impacting their performance. © 2014 The Author(s) Published by the Royal Society. All rights reserved.

Monitoring changes in economy-wide energy efficiency: From energy-GDP ratio to composite efficiency index

International Nuclear Information System (INIS)

Ang, B.W.

2006-01-01

Since the 1973 world oil crisis, monitoring trends in energy efficiency at the economy-wide level has been an important component of energy strategy in many countries. To support this effort, various energy efficiency-related indicators have been developed. We examine some classical indicators which are often found in national and international energy studies in the 1970s and 1980s. We then describe the recent developments in using the index decomposition analysis to give an economy-wide composite energy efficiency index based on a bottom-up approach. This composite index is superior to the classical indicators as an economy-wide energy efficiency measure and has lately been adopted by a growing number of countries for national energy efficiency trend monitoring

Research on allocation efficiency of the daisy chain allocation algorithm

Science.gov (United States)

Shi, Jingping; Zhang, Weiguo

2013-03-01

With the improvement of the aircraft performance in reliability, maneuverability and survivability, the number of the control effectors increases a lot. How to distribute the three-axis moments into the control surfaces reasonably becomes an important problem. Daisy chain method is simple and easy to be carried out in the design of the allocation system. But it can not solve the allocation problem for entire attainable moment subset. For the lateral-directional allocation problem, the allocation efficiency of the daisy chain can be directly measured by the area of its subset of attainable moments. Because of the non-linear allocation characteristic, the subset of attainable moments of daisy-chain method is a complex non-convex polygon, and it is difficult to solve directly. By analyzing the two-dimensional allocation problems with a "micro-element" idea, a numerical calculation algorithm is proposed to compute the area of the non-convex polygon. In order to improve the allocation efficiency of the algorithm, a genetic algorithm with the allocation efficiency chosen as the fitness function is proposed to find the best pseudo-inverse matrix.

Measuring energy efficiency: Is energy intensity a good evidence base?

International Nuclear Information System (INIS)

Proskuryakova, L.; Kovalev, A.

2015-01-01

Highlights: • Energy intensity measure reflects consumption, not energy efficiency. • Thermodynamic indicators should describe energy efficiency at all levels. • These indicators should have no reference to economic or financial parameters. • A set of energy efficiency indicators should satisfy several basic principles. • There are trade-offs between energy efficiency, power and costs. - Abstract: There is a widespread assumption in energy statistics and econometrics that energy intensity and energy efficiency are equivalent measures of energy performance of economies. The paper points to the discrepancy between the engineering concept of energy efficiency and the energy intensity as it is understood in macroeconomic statistics. This double discrepancy concerns definitions (while engineering concept of energy efficiency is based on the thermodynamic definition, energy intensity includes economic measures) and use. With regard to the latter, the authors conclude that energy intensity can only provide indirect and delayed evidence of technological and engineering energy efficiency of energy conversion processes, which entails shortcomings for management and policymaking. Therefore, we suggest to stop considering subsectoral, sectoral and other levels of energy intensities as aggregates of lower-level energy efficiency. It is suggested that the insufficiency of energy intensity indicators can be compensated with the introduction of thermodynamic indicators describing energy efficiency at the physical, technological, enterprise, sub-sector, sectoral and national levels without references to any economic or financial parameters. Structured statistical data on thermodynamic efficiency is offered as a better option for identifying break-through technologies and technological bottle-necks that constrain efficiency advancements. It is also suggested that macro-level thermodynamic indicators should be based on the thermodynamic first law efficiency and the energy

China Energy Group - Sustainable Growth Through EnergyEfficiency

Energy Technology Data Exchange (ETDEWEB)

Levine, Mark; Fridley, David; Lin, Jiang; Sinton, Jonathan; Zhou,Nan; Aden, Nathaniel; Huang, Joe; Price, Lynn; McKane, Aimee T.

2006-03-20

China is fueling its phenomenal economic growth with huge quantities of coal. The environmental consequences reach far beyond its borders--China is second only to the United States in greenhouse gas emissions. Expanding its supply of other energy sources, like nuclear power and imported oil, raises trade and security issues. Soaring electricity demand necessitates the construction of 40-70 GW of new capacity per year, creating sustained financing challenges. While daunting, the challenge of meeting China's energy needs presents a wealth of opportunities, particularly in meeting demand through improved energy efficiency and other clean energy technologies. The China Energy Group at the Lawrence Berkeley National Laboratory (LBNL) is committed to understanding these opportunities, and to exploring their implications for policy and business. We work collaboratively with energy researchers, suppliers, regulators, and consumers in China and elsewhere to: better understand the dynamics of energy use in China. Our Research Focus Encompasses Three Major Areas: Buildings, Industry, and Cross-Cutting Activities. Buildings--working to promote energy-efficient buildings and energy-efficient equipment used in buildings. Current work includes promoting the design and use of minimum energy efficiency standards and energy labeling for appliances, and assisting in the development and implementation of building codes for energy-efficient residential and commercial/public buildings. Past work has included a China Residential Energy Consumption Survey and a study of the health impacts of rural household energy use. Industry--understanding China's industrial sector, responsible for the majority of energy consumption in China. Current work includes benchmarking China's major energy-consuming industries to world best practice, examining energy efficiency trends in China's steel and cement industries, implementing voluntary energy efficiency agreements in various

Optimal Energy Management, Location and Size for Stationary Energy Storage System in a Metro Line Based on Genetic Algorithm

Directory of Open Access Journals (Sweden)

Huan Xia

2015-10-01

Full Text Available The installation of stationary super-capacitor energy storage system (ESS in metro systems can recycle the vehicle braking energy and improve the pantograph voltage profile. This paper aims to optimize the energy management, location, and size of stationary super-capacitor ESSes simultaneously and obtain the best economic efficiency and voltage profile of metro systems. Firstly, the simulation platform of an urban rail power supply system, which includes trains and super-capacitor energy storage systems, is established. Then, two evaluation functions from the perspectives of economic efficiency and voltage drop compensation are put forward. Ultimately, a novel optimization method that combines genetic algorithms and a simulation platform of urban rail power supply system is proposed, which can obtain the best energy management strategy, location, and size for ESSes simultaneously. With actual parameters of a Chinese metro line applied in the simulation comparison, certain optimal scheme of ESSes’ energy management strategy, location, and size obtained by a novel optimization method can achieve much better performance of metro systems from the perspectives of two evaluation functions. The simulation result shows that with the increase of weight coefficient, the optimal energy management strategy, locations and size of ESSes appear certain regularities, and the best compromise between economic efficiency and voltage drop compensation can be obtained by a novel optimization method, which can provide a valuable reference to subway company.

Energy Efficient Mobile Operating Systems

OpenAIRE

Muhammad Waseem

2013-01-01

Energy is an important resource in mobile computers now days. It is important to manage energy in efficient manner so that energy consumption will be reduced. Developers of operating system decided to increase the battery life time of mobile phones at operating system level. So, design of energy efficient mobile operating system is the best way to reduce the energy consumption in mobile devices. In this paper, currently used energy efficient mobile operating system is discussed and compared. ...

Cross-layer cluster-based energy-efficient protocol for wireless sensor networks.

Science.gov (United States)

Mammu, Aboobeker Sidhik Koyamparambil; Hernandez-Jayo, Unai; Sainz, Nekane; de la Iglesia, Idoia

2015-04-09

Recent developments in electronics and wireless communications have enabled the improvement of low-power and low-cost wireless sensors networks (WSNs). One of the most important challenges in WSNs is to increase the network lifetime due to the limited energy capacity of the network nodes. Another major challenge in WSNs is the hot spots that emerge as locations under heavy traffic load. Nodes in such areas quickly drain energy resources, leading to disconnection in network services. In such an environment, cross-layer cluster-based energy-efficient algorithms (CCBE) can prolong the network lifetime and energy efficiency. CCBE is based on clustering the nodes to different hexagonal structures. A hexagonal cluster consists of cluster members (CMs) and a cluster head (CH). The CHs are selected from the CMs based on nodes near the optimal CH distance and the residual energy of the nodes. Additionally, the optimal CH distance that links to optimal energy consumption is derived. To balance the energy consumption and the traffic load in the network, the CHs are rotated among all CMs. In WSNs, energy is mostly consumed during transmission and reception. Transmission collisions can further decrease the energy efficiency. These collisions can be avoided by using a contention-free protocol during the transmission period. Additionally, the CH allocates slots to the CMs based on their residual energy to increase sleep time. Furthermore, the energy consumption of CH can be further reduced by data aggregation. In this paper, we propose a data aggregation level based on the residual energy of CH and a cost-aware decision scheme for the fusion of data. Performance results show that the CCBE scheme performs better in terms of network lifetime, energy consumption and throughput compared to low-energy adaptive clustering hierarchy (LEACH) and hybrid energy-efficient distributed clustering (HEED).

Cross-Layer Cluster-Based Energy-Efficient Protocol for Wireless Sensor Networks

Directory of Open Access Journals (Sweden)

Aboobeker Sidhik Koyamparambil Mammu

2015-04-01

Full Text Available Recent developments in electronics and wireless communications have enabled the improvement of low-power and low-cost wireless sensors networks (WSNs. One of the most important challenges in WSNs is to increase the network lifetime due to the limited energy capacity of the network nodes. Another major challenge in WSNs is the hot spots that emerge as locations under heavy traffic load. Nodes in such areas quickly drain energy resources, leading to disconnection in network services. In such an environment, cross-layer cluster-based energy-efficient algorithms (CCBE can prolong the network lifetime and energy efficiency. CCBE is based on clustering the nodes to different hexagonal structures. A hexagonal cluster consists of cluster members (CMs and a cluster head (CH. The CHs are selected from the CMs based on nodes near the optimal CH distance and the residual energy of the nodes. Additionally, the optimal CH distance that links to optimal energy consumption is derived. To balance the energy consumption and the traffic load in the network, the CHs are rotated among all CMs. In WSNs, energy is mostly consumed during transmission and reception. Transmission collisions can further decrease the energy efficiency. These collisions can be avoided by using a contention-free protocol during the transmission period. Additionally, the CH allocates slots to the CMs based on their residual energy to increase sleep time. Furthermore, the energy consumption of CH can be further reduced by data aggregation. In this paper, we propose a data aggregation level based on the residual energy of CH and a cost-aware decision scheme for the fusion of data. Performance results show that the CCBE scheme performs better in terms of network lifetime, energy consumption and throughput compared to low-energy adaptive clustering hierarchy (LEACH and hybrid energy-efficient distributed clustering (HEED.

Efficient Parallel Algorithm For Direct Numerical Simulation of Turbulent Flows

Science.gov (United States)

Moitra, Stuti; Gatski, Thomas B.

1997-01-01

A distributed algorithm for a high-order-accurate finite-difference approach to the direct numerical simulation (DNS) of transition and turbulence in compressible flows is described. This work has two major objectives. The first objective is to demonstrate that parallel and distributed-memory machines can be successfully and efficiently used to solve computationally intensive and input/output intensive algorithms of the DNS class. The second objective is to show that the computational complexity involved in solving the tridiagonal systems inherent in the DNS algorithm can be reduced by algorithm innovations that obviate the need to use a parallelized tridiagonal solver.

Efficiency Evaluation of Energy Systems

CERN Document Server

Kanoğlu, Mehmet; Dinçer, İbrahim

2012-01-01

Efficiency is one of the most frequently used terms in thermodynamics, and it indicates how well an energy conversion or process is accomplished. Efficiency is also one of the most frequently misused terms in thermodynamics and is often a source of misunderstanding. This is because efficiency is often used without being properly defined first. This book intends to provide a comprehensive evaluation of various efficiencies used for energy transfer and conversion systems including steady-flow energy devices (turbines, compressors, pumps, nozzles, heat exchangers, etc.), various power plants, cogeneration plants, and refrigeration systems. The book will cover first-law (energy based) and second-law (exergy based) efficiencies and provide a comprehensive understanding of their implications. It will help minimize the widespread misuse of efficiencies among students and researchers in energy field by using an intuitive and unified approach for defining efficiencies. The book will be particularly useful for a clear ...

Efficient Algorithms for a Family of Matroid Intersection Problems

National Research Council Canada - National Science Library

Gabow, Harold N; Tarjan, Robert E

1982-01-01

.... its efficiency is demonstrated by implementations on specific matroids. In all cases but one, the running time matches the best-known algorithm for the problem without the red element constraint...

Energy efficiency of mobile soft robots.

Science.gov (United States)

Shui, Langquan; Zhu, Liangliang; Yang, Zhe; Liu, Yilun; Chen, Xi

2017-11-15

The performance of mobile soft robots is usually characterized by their locomotion/velocity efficiency, whereas the energy efficiency is a more intrinsic and fundamental criterion for the performance evaluation of independent or integrated soft robots. In this work, a general framework is established to evaluate the energy efficiency of mobile soft robots by considering the efficiency of the energy source, actuator and locomotion, and some insights for improving the efficiency of soft robotic systems are presented. Proposed as the ratio of the desired locomotion kinetic energy to the input mechanical energy, the energy efficiency of locomotion is found to play a critical role in determining the overall energy efficiency of soft robots. Four key factors related to the locomotion energy efficiency are identified, that is, the locomotion modes, material properties, geometric sizes, and actuation states. It is found that the energy efficiency of most mobile soft robots reported in the literature is surprisingly low (mostly below 0.1%), due to the inefficient mechanical energy that essentially does not contribute to the desired locomotion. A comparison of the locomotion energy efficiency for several representative locomotion modes in the literature is presented, showing a descending ranking as: jumping ≫ fish-like swimming > snake-like slithering > rolling > rising/turning over > inchworm-like inching > quadruped gait > earthworm-like squirming. Besides, considering the same locomotion mode, soft robots with lower stiffness, higher density and larger size tend to have higher locomotion energy efficiency. Moreover, a periodic pulse actuation instead of a continuous actuation mode may significantly reduce the input mechanical energy, thus improving the locomotion energy efficiency, especially when the pulse actuation matches the resonant states of the soft robots. The results presented herein indicate a large and necessary space for improving the locomotion energy

Improving energy efficiency in handheld biometric applications

Science.gov (United States)

Hoyle, David C.; Gale, John W.; Schultz, Robert C.; Rakvic, Ryan N.; Ives, Robert W.

2012-06-01

With improved smartphone and tablet technology, it is becoming increasingly feasible to implement powerful biometric recognition algorithms on portable devices. Typical iris recognition algorithms, such as Ridge Energy Direction (RED), utilize two-dimensional convolution in their implementation. This paper explores the energy consumption implications of 12 different methods of implementing two-dimensional convolution on a portable device. Typically, convolution is implemented using floating point operations. If a given algorithm implemented integer convolution vice floating point convolution, it could drastically reduce the energy consumed by the processor. The 12 methods compared include 4 major categories: Integer C, Integer Java, Floating Point C, and Floating Point Java. Each major category is further divided into 3 implementations: variable size looped convolution, static size looped convolution, and unrolled looped convolution. All testing was performed using the HTC Thunderbolt with energy measured directly using a Tektronix TDS5104B Digital Phosphor oscilloscope. Results indicate that energy savings as high as 75% are possible by using Integer C versus Floating Point C. Considering the relative proportion of processing time that convolution is responsible for in a typical algorithm, the savings in energy would likely result in significantly greater time between battery charges.

State-level benefits of energy efficiency

International Nuclear Information System (INIS)

Tonn, Bruce; Peretz, Jean H.

2007-01-01

This paper describes benefits attributable to state-level energy efficiency programs. Nationwide, state-level energy efficiency programs have targeted all sectors of the economy and have employed a wide range of methods to promote energy efficiency. Standard residential and industrial programs typically identify between 20% and 30% energy savings in homes and plants, respectively. Over a 20-year period of time, an average state that aggressively pursues even a limited array of energy efficiency programs can potentially reduce total state energy use by as much as 20%. Well-designed energy efficiency programs can be expected to help overcome numerous barriers to the market penetration of energy efficient technologies and accelerate the market penetration of the technologies. Energy efficiency programs are cost-effective; typical benefit-cost ratios exceed 3:1 and are much higher when non-energy and macroeconomic benefits are included. Indeed, energy efficiency and associated programs and investments can create significant numbers of new jobs and enhance state tax revenues. Several states have incorporated energy efficiency into their economic development programs. It should also be noted that increasing amounts of venture capital are being invested in the energy sector in general and in specific technologies like solar power in particular. (author)

State-Level Benefits of Energy Efficiency

Energy Technology Data Exchange (ETDEWEB)

Tonn, Bruce Edward [ORNL

2007-02-01

This report describes benefits attributable to state-level energy efficiency programs. Nationwide, state-level energy efficiency programs have targeted all sectors of the economy and have employed a wide range of methods to promote energy efficiency. Standard residential and industrial programs typically identify between 20 to 30% energy savings in homes and plants, respectively. Over a 20 year period of time, an average state that aggressively pursues even a limited array of energy efficiency programs can potentially reduce total state energy use by as much as 20%. Benefit-cost ratios of effective energy efficiency programs typically exceed 3 to 1 and are much higher when non-energy and macroeconomic benefits are included. Indeed, energy efficiency and associated programs and investments can create significant numbers of new jobs and enhance state tax revenues. Several states have incorporated energy efficiency into their economic development programs. It should also be noted that increasing amounts of venture capital are being invested in the energy sector in general and in specific technologies like solar power in particular. Well-designed energy efficiency programs can be expected to help overcome numerous barriers to the market penetration of energy efficient technologies and accelerate the market penetration of the technologies.

An Energy Aware Adaptive Sampling Algorithm for Energy Harvesting WSN with Energy Hungry Sensors

Science.gov (United States)

Srbinovski, Bruno; Magno, Michele; Edwards-Murphy, Fiona; Pakrashi, Vikram; Popovici, Emanuel

2016-01-01

Wireless sensor nodes have a limited power budget, though they are often expected to be functional in the field once deployed for extended periods of time. Therefore, minimization of energy consumption and energy harvesting technology in Wireless Sensor Networks (WSN) are key tools for maximizing network lifetime, and achieving self-sustainability. This paper proposes an energy aware Adaptive Sampling Algorithm (ASA) for WSN with power hungry sensors and harvesting capabilities, an energy management technique that can be implemented on any WSN platform with enough processing power to execute the proposed algorithm. An existing state-of-the-art ASA developed for wireless sensor networks with power hungry sensors is optimized and enhanced to adapt the sampling frequency according to the available energy of the node. The proposed algorithm is evaluated using two in-field testbeds that are supplied by two different energy harvesting sources (solar and wind). Simulation and comparison between the state-of-the-art ASA and the proposed energy aware ASA (EASA) in terms of energy durability are carried out using in-field measured harvested energy (using both wind and solar sources) and power hungry sensors (ultrasonic wind sensor and gas sensors). The simulation results demonstrate that using ASA in combination with an energy aware function on the nodes can drastically increase the lifetime of a WSN node and enable self-sustainability. In fact, the proposed EASA in conjunction with energy harvesting capability can lead towards perpetual WSN operation and significantly outperform the state-of-the-art ASA. PMID:27043559

An Energy Aware Adaptive Sampling Algorithm for Energy Harvesting WSN with Energy Hungry Sensors

Directory of Open Access Journals (Sweden)

Bruno Srbinovski

2016-03-01

Full Text Available Wireless sensor nodes have a limited power budget, though they are often expected to be functional in the field once deployed for extended periods of time. Therefore, minimization of energy consumption and energy harvesting technology in Wireless Sensor Networks (WSN are key tools for maximizing network lifetime, and achieving self-sustainability. This paper proposes an energy aware Adaptive Sampling Algorithm (ASA for WSN with power hungry sensors and harvesting capabilities, an energy management technique that can be implemented on any WSN platform with enough processing power to execute the proposed algorithm. An existing state-of-the-art ASA developed for wireless sensor networks with power hungry sensors is optimized and enhanced to adapt the sampling frequency according to the available energy of the node. The proposed algorithm is evaluated using two in-field testbeds that are supplied by two different energy harvesting sources (solar and wind. Simulation and comparison between the state-of-the-art ASA and the proposed energy aware ASA (EASA in terms of energy durability are carried out using in-field measured harvested energy (using both wind and solar sources and power hungry sensors (ultrasonic wind sensor and gas sensors. The simulation results demonstrate that using ASA in combination with an energy aware function on the nodes can drastically increase the lifetime of a WSN node and enable self-sustainability. In fact, the proposed EASA in conjunction with energy harvesting capability can lead towards perpetual WSN operation and significantly outperform the state-of-the-art ASA.

Market conditions affecting energy efficiency investments

International Nuclear Information System (INIS)

Seabright, J.

1996-01-01

The global energy efficiency market is growing, due in part to energy sector and macroeconomic reforms and increased awareness of the environmental benefits of energy efficiency. Many countries have promoted open, competitive markets, thereby stimulating economic growth. They have reduced or removed subsidies on energy prices, and governments have initiated energy conservation programs that have spurred the wider adoption of energy efficiency technologies. The market outlook for energy efficiency is quite positive. The global market for end-use energy efficiency in the industrial, residential and commercial sectors is now estimated to total more than $34 billion per year. There is still enormous technical potential to implement energy conservation measures and to upgrade to the best available technologies for new investments. For many technologies, energy-efficient designs now represent less than 10--20% of new product sales. Thus, creating favorable market conditions should be a priority. There are a number of actions that can be taken to create favorable market conditions for investing in energy efficiency. Fostering a market-oriented energy sector will lead to energy prices that reflect the true cost of supply. Policy initiatives should address known market failures and should support energy efficiency initiatives. And market transformation for energy efficiency products and services can be facilitated by creating an institutional and legal structure that favors commercially-oriented entities

Promotion of Efficient Use of Energy

Energy Technology Data Exchange (ETDEWEB)

Harry Misuriello; DOE Project Officer - Keith Bennett

2006-01-25

The Department of Energy funded the Alliance to Save Energy to promote the efficient use of energy under a multiyear cooperative agreement. This funding allowed the Alliance to be innovative and flexible in its program development, and to initiate and enhance projects it would otherwise not have been able to pursue. The program period was 1999 through 2004. The mission of the Alliance to Save Energy is to promote energy efficiency domestically and worldwide. The Alliance followed this mission by working closely with consumers, government, policy makers, and energy efficient product and service providers. The projects that were initiated by the Alliance included communication and consumer education, policy analysis and research, the promotion of interaction among the energy efficiency industry, and international energy efficiency programs. The funding from the Department of Energy allowed the Alliance to study new issues in energy efficiency, draw public attention to those issues, and create targeted programs, such as the Efficient Windows Collaborative or the Green Schools program, which now function on their own to promote energy efficiency in important areas.

Building occupancy diversity and HVAC (heating, ventilation, and air conditioning) system energy efficiency

International Nuclear Information System (INIS)

Yang, Zheng; Ghahramani, Ali; Becerik-Gerber, Burcin

2016-01-01

Approximately forty percent of total building energy consumption is attributed to HVAC (heating, ventilation, and air conditioning) systems that aim to maintain healthy and comfortable indoor environments. An HVAC system is a network with several subsystems, and there exist heat transfer and balance among the zones of a building, as well as heat gains and losses through a building's envelope. Diverse occupancy (diversity in terms of when and how occupants occupy a building) in spaces could result in increase of loads that are not actual demands for an HVAC system, leading into inefficiencies. This paper introduces a framework to quantitatively evaluate the energy implications of occupancy diversity at the building level, where building information modeling is integrated to provide building geometries, HVAC system layouts, and spatial information as inputs for computing potential energy implications if occupancy diversity were to be eliminated. An agglomerate hierarchical clustering-based iterative evaluation algorithm is designed for iteratively eliminating occupancy diversity. Whole building energy simulations for a real-world building, as well as virtual reference buildings demonstrate that the proposed framework could effectively quantify the HVAC system energy efficiency affected by occupancy diversity and the framework is generalizable to different building geometries, layouts, and occupancy diversities. - Highlights: • Analyze relationships between occupancy diversity and HVAC energy efficiency. • Integrate BIM for quantifying energy implications of occupancy diversity. • Demonstrate the effectiveness and generalizability of iterative evaluation algorithm. • Improve agglomerative hierarchical clustering process using heap data structure.

75 FR 69655 - Energy Efficiency and Renewable Energy Advisory Committee (ERAC)

Science.gov (United States)

2010-11-15

... DEPARTMENT OF ENERGY Office of Energy Efficiency and Renewable Energy Energy Efficiency and Renewable Energy Advisory Committee (ERAC) AGENCY: Department of Energy, Office of Energy Efficiency and... Energy Efficiency and Renewable Energy Advisory [[Page 69656

EH-GC: An Efficient and Secure Architecture of Energy Harvesting Green Cloud Infrastructure

Directory of Open Access Journals (Sweden)

Saurabh Singh

2017-04-01

Full Text Available Nowadays, the high power consumption of data centers is the biggest challenge to making cloud computing greener. Many researchers are still seeking effective solutions to reduce or harvest the energy produced at data centers. To address this challenge, we propose a green cloud infrastructure which provides security and efficiency based on energy harvesting (EH-GC. The EH-GC is basically focused on harvesting the heat energy produced by data centers in the Infrastructure-as-a-Service (IaaS infrastructure. A pyroelectric material is used to generate the electric current from heat using the Olsen cycle. In order to achieve efficient green cloud computing, the architecture utilizes a genetic algorithm for proper virtual machine allocation, taking into consideration less Service Level Agreement (SLA violations. The architecture utilizes Multivariate Correlation Analysis (MCA correlation analysis based on a triangular map area generation to detect Denial of Service (DoS attacks in the data center layer of the IaaS. Finally, the experimental analysis is explained based on the energy parameter, which proves that our model is efficient and secure, and that it efficiently reuses the energy emitted from the data center.

78 FR 20896 - Renewable Energy and Energy Efficiency Advisory Committee

Science.gov (United States)

2013-04-08

... DEPARTMENT OF COMMERCE International Trade Administration Renewable Energy and Energy Efficiency... of an Open Meeting. SUMMARY: The Renewable Energy and Energy Efficiency Advisory Committee (RE&EEAC... industry-specific teams--renewable energy, energy efficiency, energy storage and transmission, and biofuels...

78 FR 48855 - Renewable Energy and Energy Efficiency Advisory Committee

Science.gov (United States)

2013-08-12

... Administration Renewable Energy and Energy Efficiency Advisory Committee AGENCY: International Trade... the international competitiveness of the U.S. renewable energy and energy efficiency industries. The... Renewable Energy and Energy Efficiency Advisory Committee, Attention: Ryan Mulholland, Office of Energy and...

Is energy efficiency environmentally friendly?

Energy Technology Data Exchange (ETDEWEB)

Herring, H. [Open University, Milton Keynes (United Kingdom). Energy and Environment Research Unit

2000-07-01

The paper challenges the view that improving the efficiency of energy use will lead to a reduction in national energy consumption, and hence is an effective policy for reducing CO{sub 2} emissions. It argues that improving energy efficiency lowers the implicit price of energy and hence makes its use more affordable, thus leading to greater use. The paper presents the views of economists, as well as green critics of 'efficiency' and the 'dematerialization' thesis. It argues that a more effective CO{sub 2} policy is to concentrate on shifting to non-fossil fuel, like renewables, subsidized through a carbon tax. Ultimately what is needed, to limit energy consumption is energy conservation not energy efficiency. 44 refs.

77 FR 50489 - Office of Energy Efficiency and Renewable Energy

Science.gov (United States)

2012-08-21

... DEPARTMENT OF ENERGY Office of Energy Efficiency and Renewable Energy Wind and Water Power Program AGENCY: Office of Energy Efficiency and Renewable Energy, Department of Energy. ACTION: Notice of public... FURTHER INFORMATION CONTACT: Mr. Hoyt Battey, Office of Energy Efficiency and Renewable Energy, U.S...

75 FR 70214 - Renewable Energy and Energy Efficiency Advisory Committee

Science.gov (United States)

2010-11-17

... DEPARTMENT OF COMMERCE International Trade Administration Renewable Energy and Energy Efficiency... of an open meeting. SUMMARY: The Renewable Energy and Energy Efficiency Advisory Committee (RE&EEAC... submitted to the Renewable Energy and Energy Efficiency Advisory Committee, Office of Energy and...

Mobile Energy Laboratory energy-efficiency testing programs

International Nuclear Information System (INIS)

Parker, G.B.; Currie, J.W.

1992-03-01

This report summarizes energy-efficiency testing activities applying the Mobile Energy Laboratory (MEL) testing capabilities during the third and fourth quarters of fiscal year (FY) 1991. The MELs, developed by the US Department of Energy (DOE) Federal Energy Management Program (FEMP), are administered by Pacific Northwest Laboratory (PNL) and the Naval Energy and Environmental Support Activity (NEESA) for energy testing and energy conservation program support functions at federal facilities. The using agencies principally fund MEL applications, while DOE/FEMP funds program administration and capability enhancement activities. This report fulfills the requirements established in Section 8 of the MEL Use Plan (PNL-6861) for semi-annual reporting on energy-efficiency testing activities using the MEL capabilities. The MEL Use Committee, formally established in 1989, developed the MEL Use Plan and meets semi-annually to establish priorities for energy-efficient testing applications using the MEL capabilities. The MEL Use Committee is composed of one representative each of the US Department of Energy, US Army, US Air Force, US Navy, and other federal agencies

Mobile Energy Laboratory energy-efficiency testing programs

Energy Technology Data Exchange (ETDEWEB)

Parker, G B; Currie, J W

1992-03-01

This report summarizes energy-efficiency testing activities applying the Mobile Energy Laboratory (MEL) testing capabilities during the third and fourth quarters of fiscal year (FY) 1991. The MELs, developed by the US Department of Energy (DOE) Federal Energy Management Program (FEMP), are administered by Pacific Northwest Laboratory (PNL) and the Naval Energy and Environmental Support Activity (NEESA) for energy testing and energy conservation program support functions at federal facilities. The using agencies principally fund MEL applications, while DOE/FEMP funds program administration and capability enhancement activities. This report fulfills the requirements established in Section 8 of the MEL Use Plan (PNL-6861) for semi-annual reporting on energy-efficiency testing activities using the MEL capabilities. The MEL Use Committee, formally established in 1989, developed the MEL Use Plan and meets semi-annually to establish priorities for energy-efficient testing applications using the MEL capabilities. The MEL Use Committee is composed of one representative each of the US Department of Energy, US Army, US Air Force, US Navy, and other federal agencies.

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.

Efficient Algorithms for gcd and Cubic Residuosity in the Ring of Eisenstein Integers

DEFF Research Database (Denmark)

Damgård, Ivan Bjerre; Frandsen, Gudmund Skovbjerg

2003-01-01

We present simple and efficient algorithms for computing gcd and cubic residuosity in the ring of Eisenstein integers, bf Z[ ]i.e. the integers extended with , a complex primitive third root of unity. The algorithms are similar and may be seen as generalisations of the binary integer gcd and deri......We present simple and efficient algorithms for computing gcd and cubic residuosity in the ring of Eisenstein integers, bf Z[ ]i.e. the integers extended with , a complex primitive third root of unity. The algorithms are similar and may be seen as generalisations of the binary integer gcd...

Management of efficient use of energy and energy efficiency markets in Europe

International Nuclear Information System (INIS)

Lutz, Wolfang F.

1999-01-01

The present paper is based on the study S ystematization of European Legal, regulatory, and Institutional Frameworks for the Efficient Use of Energy , conducted in the framework of the project entitled Building up the Institutional and Regulatory Design to Consolidate Modernization of Energy Policies in the Countries of Latin America: Efficient Use of energy, implemented by the United Nations Economic Commission for Latin America and the Caribbean, in cooperation with the Synergy Programme of the European Commission of the Directorate General of Energy. (The author)

Energy Efficiency: Finding Leadership Opportunities

Directory of Open Access Journals (Sweden)

William Rosehart

2014-01-01

Full Text Available Between 1995 and 2011, the population of Alberta increased by roughly 40 per cent, but energy use in the province grew much faster, with a 62 per cent increase over the same period. In the industrial sector, the province’s largest energy consumer, demands grew 110 per cent. In mining and oil-and-gas extraction specifically, energy use over that period soared, growing by 355 per cent. That remarkable growth in energy consumption creates a particular challenge for Alberta Premier Alison Redford, who in 2011 ordered her ministers to develop a plan that “would make Alberta the national leader in energy efficiency and sustainability.” The province is still waiting. The incentives to become more energy efficient are not particularly strong in Alberta. The province’s terrain and size favour larger and less-efficient vehicles. Energy in the province is abundant, so there is little cause for concern over energy security. And energy is relatively affordable, particularly for a population that is more affluent than the Canadian average. There is little pressure on Albertans to radically alter their energy consumption behaviour. Yet, improved energy efficiency could position businesses in Alberta to become even more globally competitive, in addition to leading to improved air quality and public health. And for a province racing to keep up with growing energy demand, effective measures that promote conservation will prove much cheaper than adding yet more expensive infrastructure to the energy network. Many other jurisdictions have already provided examples of methods Alberta could employ to effectively promote energy conservation. First, Alberta must set hard targets for its goals to save energy, and then monitor that progress through transparent accounting, measuring and reporting. The provincial government can also nurture a culture of energy conservation, by formally and publicly recognizing leadership in efficiency improvements in industry and

Energy efficiency in Finland

Energy Technology Data Exchange (ETDEWEB)

NONE

1997-12-31

In Finland a significant portion of energy originates from renewable sources and cogeneration, that is, combined production of electricity and heat. Combined heat and electricity production is typical in the Finnish industry and in the district heating sector. One third of all electricity and 15 % of district heating is produced by cogeneration. District heating schemes provide about 45 % of heat in buildings. Overall efficiency in industry exceeds 80 % and is even higher in the district heating sector. In 1996 25 % of Finland`s primary energy was produced from renewable energy sources which is a far higher proportion than the European Union average of 6 %. Finland is one of the leading users of bioenergy. Biomass including peat, provides approximately 50 % of fuel consumed by industry and is utilised in significant amounts in combined heat and electricity plants. For example, in the pulp and paper industry, by burning black liquor and bark during the production of chemical pulp, significant amounts of energy are generated and used in paper mills. Conservation and efficient use of energy are central to the Finnish Government`s Energy Strategy. The energy conservation programme aims to increase energy efficiency by 10-20 % by the year 2010. Energy saving technology plays a key role in making the production and use of energy more efficient. In 1996 of FIM 335 million (ECU 57 million) spent on funding research, FIM 120 million (ECU 20 million) was spent on research into energy conservation

76 FR 6605 - Energy Efficiency and Renewable Energy Advisory Committee (ERAC)

Science.gov (United States)

2011-02-07

... DEPARTMENT OF ENERGY Office of Energy Efficiency and Renewable Energy Energy Efficiency and Renewable Energy Advisory Committee (ERAC) AGENCY: Department of Energy, Office of Energy Efficiency and... within the field of energy efficiency and renewable energy. The Federal Advisory Committee Act, Public...

76 FR 7815 - Renewable Energy and Energy Efficiency Advisory Committee

Science.gov (United States)

2011-02-11

... DEPARTMENT OF COMMERCE International Trade Administration Renewable Energy and Energy Efficiency... of an open meeting. SUMMARY: The Renewable Energy and Energy Efficiency Advisory Committee (RE&EEAC... programs support the competitiveness of U.S. renewable energy and energy efficiency companies, to review...

76 FR 54431 - Renewable Energy and Energy Efficiency Advisory Committee

Science.gov (United States)

2011-09-01

... DEPARTMENT OF COMMERCE International Trade Administration Renewable Energy and Energy Efficiency... of an Open Meeting. SUMMARY: The Renewable Energy and Energy Efficiency Advisory Committee (RE&EEAC... competitiveness of the U.S. renewable energy and energy efficiency industries, including specific challenges...

78 FR 78340 - Renewable Energy and Energy Efficiency Advisory Committee

Science.gov (United States)

2013-12-26

... DEPARTMENT OF COMMERCE International Trade Administration Renewable Energy and Energy Efficiency... of an Open Meeting. SUMMARY: The Renewable Energy and Energy Efficiency Advisory Committee (RE&EEAC... affecting U.S. competitiveness in exporting renewable energy and energy efficiency (RE&EE) products and...

Simulation of a coal-fired power plant using mathematical programming algorithms in order to optimize its efficiency

International Nuclear Information System (INIS)

Tzolakis, G.; Papanikolaou, P.; Kolokotronis, D.; Samaras, N.; Tourlidakis, A.; Tomboulides, A.

2012-01-01

Since most of the world's electric energy production is mainly based on fossil fuels and need for better efficiency of the energy conversion systems is imminent, mathematical programming algorithms were applied for the simulation and optimization of a detailed model of an existing lignite-fired power plant in Kozani, Greece (KARDIA IV). The optimization of its overall thermal efficiency, using as control variables the mass flow rates of the steam turbine extractions and the fuel consumption, was performed with the use of the simulation and optimization software gPROMS. The power plant components' mathematical models were imported in software by the authors and the results showed that further increase to the overall thermal efficiency of the plant can be achieved (a 0.55% absolute increase) through reduction of the HP turbine's and increase of the LP turbine's extractions mass flow rates and the parallel reduction of the fuel consumption by 2.05% which also results to an equivalent reduction of the greenhouse gasses. The setup of the mathematical model and the flexibility of gPROMS, make this software applicable to various power plants. - Highlights: ► Modeling and simulation of the flue gases circuit of a specific plant. ► Designing of modules in gPROMS FO (Foreign Objects). ► Simulation of the complete detailed plant with gPROMS. ► Optimization using a non-linear optimization algorithm of the plant's efficiency.

Financing Energy Efficient Homes

Energy Technology Data Exchange (ETDEWEB)

NONE

2007-07-01

Existing buildings require over 40% of the world's total final energy consumption, and account for 24% of world CO2 emissions (IEA, 2006). Much of this consumption could be avoided through improved efficiency of building energy systems (IEA, 2006) using current, commercially-viable technology. In most cases, these technologies make economic sense on a life-cycle cost analysis (IEA, 2006b). Moreover, to the extent that they reduce dependence on risk-prone fossil energy sources, energy efficient technologies also address concerns of energy security.

Financing Energy Efficient Homes

Energy Technology Data Exchange (ETDEWEB)

NONE

2007-07-01

Existing buildings require over 40% of the world's total final energy consumption, and account for 24% of world CO2 emissions (IEA, 2006). Much of this consumption could be avoided through improved efficiency of building energy systems (IEA, 2006) using current, commercially-viable technology. In most cases, these technologies make economic sense on a life-cycle cost analysis (IEA, 2006b). Moreover, to the extent that they reduce dependence on risk-prone fossil energy sources, energy efficient technologies also address concerns of energy security.

Energy Efficiency Project Development

Energy Technology Data Exchange (ETDEWEB)

IUEP

2004-03-01

The International Utility Efficiency Partnerships, Inc. (IUEP) has been a leader among the industry groups that have supported voluntary initiatives to promote international energy efficiency projects and address global climate change. The IUEP maintains its leadership by both supporting international greenhouse gas (GHG) reduction projects under the auspices of the U.S. Department of Energy (DOE) and by partnering with U.S. and international organizations to develop and implement strategies and specific energy efficiency projects. The goals of the IUEP program are to (1) provide a way for U.S. industry to maintain a leadership role in international energy efficiency infrastructure projects; (2) identify international energy project development opportunities to continue its leadership in supporting voluntary market-based mechanisms to reduce GHG emissions; and (3) demonstrate private sector commitment to voluntary approaches to global climate issues. The IUEP is dedicated to identifying, promoting, managing, and assisting in the registration of international energy efficiency projects that result in demonstrated voluntary reductions of GHG emissions. This Final Technical Report summarizes the IUEP's work in identifying, promoting, managing, and assisting in development of these projects and IUEP's effort in creating international cooperative partnerships to support project development activities that develop and deploy technologies that (1) increase efficiency in the production, delivery and use of energy; (2) increase the use of cleaner, low-carbon fuels in processing products; and (3) capture/sequester carbon gases from energy systems. Through international cooperative efforts, the IUEP intends to strengthen partnerships for energy technology innovation and demonstration projects capable of providing cleaner energy in a cost-effective manner. As detailed in this report, the IUEP met program objectives and goals during the reporting period January 1

Efficient Energy Consumption Scheduling: Towards Effective Load Leveling

Directory of Open Access Journals (Sweden)

Yuan Hong

2017-01-01

Full Text Available Different agents in the smart grid infrastructure (e.g., households, buildings, communities consume energy with their own appliances, which may have adjustable usage schedules over a day, a month, a season or even a year. One of the major objectives of the smart grid is to flatten the demand load of numerous agents (viz. consumers, such that the peak load can be avoided and power supply can feed the demand load at anytime on the grid. To this end, we propose two Energy Consumption Scheduling (ECS problems for the appliances held by different agents at the demand side to effectively facilitate load leveling. Specifically, we mathematically model the ECS problems as Mixed-Integer Programming (MIP problems using the data collected from different agents (e.g., their appliances’ energy consumption in every time slot and the total number of required in-use time slots, specific preferences of the in-use time slots for their appliances. Furthermore, we propose a novel algorithm to efficiently and effectively solve the ECS problems with large-scale inputs (which are NP-hard. The experimental results demonstrate that our approach is significantly more efficient than standard benchmarks, such as CPLEX, while guaranteeing near-optimal outputs.

An optimization method of VON mapping for energy efficiency and routing in elastic optical networks

Science.gov (United States)

Liu, Huanlin; Xiong, Cuilian; Chen, Yong; Li, Changping; Chen, Derun

2018-03-01

To improve resources utilization efficiency, network virtualization in elastic optical networks has been developed by sharing the same physical network for difference users and applications. In the process of virtual nodes mapping, longer paths between physical nodes will consume more spectrum resources and energy. To address the problem, we propose a virtual optical network mapping algorithm called genetic multi-objective optimize virtual optical network mapping algorithm (GM-OVONM-AL), which jointly optimizes the energy consumption and spectrum resources consumption in the process of virtual optical network mapping. Firstly, a vector function is proposed to balance the energy consumption and spectrum resources by optimizing population classification and crowding distance sorting. Then, an adaptive crossover operator based on hierarchical comparison is proposed to improve search ability and convergence speed. In addition, the principle of the survival of the fittest is introduced to select better individual according to the relationship of domination rank. Compared with the spectrum consecutiveness-opaque virtual optical network mapping-algorithm and baseline-opaque virtual optical network mapping algorithm, simulation results show the proposed GM-OVONM-AL can achieve the lowest bandwidth blocking probability and save the energy consumption.

77 FR 23224 - Renewable Energy and Energy Efficiency Advisory Committee

Science.gov (United States)

2012-04-18

... DEPARTMENT OF COMMERCE International Trade Administration Renewable Energy and Energy Efficiency... of an open meeting. SUMMARY: The Renewable Energy and Energy Efficiency Advisory Committee (RE&EEAC.... competitiveness in exporting renewable energy and energy efficiency (RE&EE) products and services, such as access...

78 FR 69370 - Renewable Energy and Energy Efficiency Advisory Committee

Science.gov (United States)

2013-11-19

... DEPARTMENT OF COMMERCE International Trade Administration Renewable Energy and Energy Efficiency... of an open meeting. SUMMARY: The Renewable Energy and Energy Efficiency Advisory Committee (RE&EEAC....S. renewable energy and energy efficiency industries. The December 3, 2013 meeting of the RE&EEAC...

77 FR 32531 - Renewable Energy and Energy Efficiency Advisory Committee

Science.gov (United States)

2012-06-01

... DEPARTMENT OF COMMERCE International Trade Administration Renewable Energy and Energy Efficiency... of an Open Meeting. SUMMARY: The Renewable Energy and Energy Efficiency Advisory Committee (RE&EEAC... new capital for investment in the U.S. renewable energy and energy efficiency sectors, increasing the...

76 FR 44576 - Renewable Energy and Energy Efficiency Advisory Committee

Science.gov (United States)

2011-07-26

... DEPARTMENT OF COMMERCE International Trade Administration Renewable Energy and Energy Efficiency... of an Open Meeting. SUMMARY: The Renewable Energy and Energy Efficiency Advisory Committee (RE&EEAC.... renewable energy and energy efficiency industries. The RE&EEAC held its first meeting on December 7, 2010...

78 FR 2952 - Renewable Energy and Energy Efficiency Advisory Committee

Science.gov (United States)

2013-01-15

... DEPARTMENT OF COMMERCE International Trade Administration Renewable Energy and Energy Efficiency... of an open meeting. SUMMARY: The Renewable Energy and Energy Efficiency Advisory Committee (RE&EEAC... competitiveness of U.S. renewable energy and energy efficiency exports. The meeting is open to the public and the...

Improving energy efficiency of an Olefin plant – A new approach

International Nuclear Information System (INIS)

Tahouni, Nassim; Bagheri, Narges; Towfighi, Jafar; Hassan Panjeshahi, M.

2013-01-01

Highlights: • The retrofit of an Olefin plant is studied to improve the overall energy efficiency. • Three levels of retrofit and optimization of this process are suggested. • A simultaneous method is presented to optimize low-temperature separation processes. - Abstract: Low-temperature gas separation processes are the most important gas separation routes. There is a complex interaction between core process (separation columns), associated heat exchanger network and refrigeration cycles in sub ambient processes. The aim of this paper is performing a comprehensive retrofit study of an Olefin plant (as an industrial example) to improve the overall energy efficiency. In this regard, the effect of improving column operating parameters and refrigeration cycles are first evaluated separately. Then, column operating parameters and refrigeration cycles as well as heat exchanger network are optimized simultaneously using genetic algorithm or simulated annealing. Having compared all results, one can conclude that simultaneous optimization leads to higher efficiency of the overall system

Productivity and energy efficiency

Energy Technology Data Exchange (ETDEWEB)

Lovins, H. [Rocky Mountain Inst., Snowmass, CO (United States)

1995-12-31

Energy efficient building and office design offers the possibility of significantly increased worker productivity. By improving lighting, heating and cooling, workers can be made more comfortable and productive. An increase of 1 percent in productivity can provide savings to a company that exceed its entire energy bill. Efficient design practices are cost effective just from their energy savings. The resulting productivity gains make them indispensable. This paper documents eight cases in which efficient lighting, heating, and cooling have measurably increased worker productivity, decreased absenteeism, and/or improved the quality of work performed. They also show that efficient lighting can measurably increase work quality by removing errors and manufacturing defects. The case studies presented include retrofit of existing buildings and the design of new facilities, and cover a variety of commercial and industrial settings. Each case study identifies the design changes that were most responsible for increased productivity. As the eight case studies illustrate, energy efficient design may be one of the least expensive ways for a business to improve the productivity of its workers and the quality of its product. (author). 15 refs.

77 FR 64112 - Office of Energy Efficiency and Renewable Energy

Science.gov (United States)

2012-10-18

... DEPARTMENT OF ENERGY Office of Energy Efficiency and Renewable Energy Nationwide Categorical Waivers of the American Recovery and Reinvestment Act AGENCY: Office of Energy Efficiency and Renewable... Efficiency and Renewable Energy, U.S. Department of Energy. [FR Doc. 2012-25636 Filed 10-17-12; 8:45 am...

Optimization of photovoltaic energy production through an efficient switching matrix

Directory of Open Access Journals (Sweden)

Pietro Romano

2013-09-01

Full Text Available This work presents a preliminary study on the implementation of a new system for power output maximization of photovoltaic generators under non-homogeneous conditions. The study evaluates the performance of an efficient switching matrix and the relevant automatic reconfiguration control algorithms. The switching matrix is installed between the PV generator and the inverter, allowing a large number of possible module configurations. PV generator, switching matrix and the intelligent controller have been simulated in Simulink. The proposed reconfiguration system improved the energy extracted by the PV generator under non-uniform solar irradiation conditions. Short calculation times of the proposed control algorithms allow its use in real time applications even where a higher number of PV modules is required.

An Efficient Meta Heuristic Algorithm to Solve Economic Load Dispatch Problems

Directory of Open Access Journals (Sweden)

R Subramanian

2013-12-01

Full Text Available The Economic Load Dispatch (ELD problems in power generation systems are to reduce the fuel cost by reducing the total cost for the generation of electric power. This paper presents an efficient Modified Firefly Algorithm (MFA, for solving ELD Problem. The main objective of the problems is to minimize the total fuel cost of the generating units having quadratic cost functions subjected to limits on generator true power output and transmission losses. The MFA is a stochastic, Meta heuristic approach based on the idealized behaviour of the flashing characteristics of fireflies. This paper presents an application of MFA to ELD for six generator test case system. MFA is applied to ELD problem and compared its solution quality and computation efficiency to Genetic algorithm (GA, Differential Evolution (DE, Particle swarm optimization (PSO, Artificial Bee Colony optimization (ABC, Biogeography-Based Optimization (BBO, Bacterial Foraging optimization (BFO, Firefly Algorithm (FA techniques. The simulation result shows that the proposed algorithm outperforms previous optimization methods.

Energy efficiency benchmarking of energy-intensive industries in Taiwan

International Nuclear Information System (INIS)

Chan, David Yih-Liang; Huang, Chi-Feng; Lin, Wei-Chun; Hong, Gui-Bing

2014-01-01

Highlights: • Analytical tool was applied to estimate the energy efficiency indicator of energy intensive industries in Taiwan. • The carbon dioxide emission intensity in selected energy-intensive industries is also evaluated in this study. • The obtained energy efficiency indicator can serve as a base case for comparison to the other regions in the world. • This analysis results can serve as a benchmark for selected energy-intensive industries. - Abstract: Taiwan imports approximately 97.9% of its primary energy as rapid economic development has significantly increased energy and electricity demands. Increased energy efficiency is necessary for industry to comply with energy-efficiency indicators and benchmarking. Benchmarking is applied in this work as an analytical tool to estimate the energy-efficiency indicators of major energy-intensive industries in Taiwan and then compare them to other regions of the world. In addition, the carbon dioxide emission intensity in the iron and steel, chemical, cement, textile and pulp and paper industries are evaluated in this study. In the iron and steel industry, the energy improvement potential of blast furnace–basic oxygen furnace (BF–BOF) based on BPT (best practice technology) is about 28%. Between 2007 and 2011, the average specific energy consumption (SEC) of styrene monomer (SM), purified terephthalic acid (PTA) and low-density polyethylene (LDPE) was 9.6 GJ/ton, 5.3 GJ/ton and 9.1 GJ/ton, respectively. The energy efficiency of pulping would be improved by 33% if BAT (best available technology) were applied. The analysis results can serve as a benchmark for these industries and as a base case for stimulating changes aimed at more efficient energy utilization

Role of executive agencies for energy efficiency with a view on activities of Serbian Energy Efficiency Agency

Directory of Open Access Journals (Sweden)

Kovačić Bojan J.

2012-01-01

Full Text Available Many countries, particularly in Europe, have executive energy efficiency agencies at national, regional and local levels that are organized in different ways. For all of them, it is common that there are existing strategic needs in their countries for enhancement of conditions and measures for rational use of energy and fuels. Serbian Energy Efficiency Agency was established in 2002 within the reform of the energy sector in Serbia and its current status was defined in 2004 by the Energy Law. It contributes to the improvement of social responsibility towards energy in all structures of the state and society, by proposing energy efficiency incentives, promoting importance of energy efficiency, as well as by managing energy efficiency and renewable energy programs and projects.

Energy planning and energy efficiency assistance

Energy Technology Data Exchange (ETDEWEB)

Markel, L. [Electrotek Concepts, Inc., Knoxville, TN (United States)

1995-12-31

Electrotek is an engineering services company specializing in energy-related programs. Clients are most utilities, large energy users, and the U.S. Electric Power Research Institute. Electrotek has directed energy projects for the U.S. Agency for International Development and the U.S. Department of Energy in Poland and other countries of Central Europe. The objective is to assist the host country organizations to identify and implement appropriate energy efficiency and pollution reduction technologies, to transfer technical and organizational knowledge, so that further implementations are market-driven, without needed continuing foreign investment. Electrotek has worked with the Silesian Power Distribution Company to design an energy efficiency program for industrial customers that has proven to be profitable for the company and for its customers. The program has both saved energy and costs, and reduced pollution. The program is expanding to include additional customers, without needing more funding from the U.S. government.

A simple and efficient algorithm to estimate daily global solar radiation from geostationary satellite data

International Nuclear Information System (INIS)

Lu, Ning; Qin, Jun; Yang, Kun; Sun, Jiulin

2011-01-01

Surface global solar radiation (GSR) is the primary renewable energy in nature. Geostationary satellite data are used to map GSR in many inversion algorithms in which ground GSR measurements merely serve to validate the satellite retrievals. In this study, a simple algorithm with artificial neural network (ANN) modeling is proposed to explore the non-linear physical relationship between ground daily GSR measurements and Multi-functional Transport Satellite (MTSAT) all-channel observations in an effort to fully exploit information contained in both data sets. Singular value decomposition is implemented to extract the principal signals from satellite data and a novel method is applied to enhance ANN performance at high altitude. A three-layer feed-forward ANN model is trained with one year of daily GSR measurements at ten ground sites. This trained ANN is then used to map continuous daily GSR for two years, and its performance is validated at all 83 ground sites in China. The evaluation result demonstrates that this algorithm can quickly and efficiently build the ANN model that estimates daily GSR from geostationary satellite data with good accuracy in both space and time. -- Highlights: → A simple and efficient algorithm to estimate GSR from geostationary satellite data. → ANN model fully exploits both the information from satellite and ground measurements. → Good performance of the ANN model is comparable to that of the classical models. → Surface elevation and infrared information enhance GSR inversion.

Efficient Dual Domain Decoding of Linear Block Codes Using Genetic Algorithms

Directory of Open Access Journals (Sweden)

Ahmed Azouaoui

2012-01-01

Full Text Available A computationally efficient algorithm for decoding block codes is developed using a genetic algorithm (GA. The proposed algorithm uses the dual code in contrast to the existing genetic decoders in the literature that use the code itself. Hence, this new approach reduces the complexity of decoding the codes of high rates. We simulated our algorithm in various transmission channels. The performance of this algorithm is investigated and compared with competitor decoding algorithms including Maini and Shakeel ones. The results show that the proposed algorithm gives large gains over the Chase-2 decoding algorithm and reach the performance of the OSD-3 for some quadratic residue (QR codes. Further, we define a new crossover operator that exploits the domain specific information and compare it with uniform and two point crossover. The complexity of this algorithm is also discussed and compared to other algorithms.

Fast Ss-Ilm a Computationally Efficient Algorithm to Discover Socially Important Locations

Science.gov (United States)

Dokuz, A. S.; Celik, M.

2017-11-01

Socially important locations are places which are frequently visited by social media users in their social media lifetime. Discovering socially important locations provide several valuable information about user behaviours on social media networking sites. However, discovering socially important locations are challenging due to data volume and dimensions, spatial and temporal calculations, location sparseness in social media datasets, and inefficiency of current algorithms. In the literature, several studies are conducted to discover important locations, however, the proposed approaches do not work in computationally efficient manner. In this study, we propose Fast SS-ILM algorithm by modifying the algorithm of SS-ILM to mine socially important locations efficiently. Experimental results show that proposed Fast SS-ILM algorithm decreases execution time of socially important locations discovery process up to 20 %.

FAST SS-ILM: A COMPUTATIONALLY EFFICIENT ALGORITHM TO DISCOVER SOCIALLY IMPORTANT LOCATIONS

Directory of Open Access Journals (Sweden)

A. S. Dokuz

2017-11-01

Full Text Available Socially important locations are places which are frequently visited by social media users in their social media lifetime. Discovering socially important locations provide several valuable information about user behaviours on social media networking sites. However, discovering socially important locations are challenging due to data volume and dimensions, spatial and temporal calculations, location sparseness in social media datasets, and inefficiency of current algorithms. In the literature, several studies are conducted to discover important locations, however, the proposed approaches do not work in computationally efficient manner. In this study, we propose Fast SS-ILM algorithm by modifying the algorithm of SS-ILM to mine socially important locations efficiently. Experimental results show that proposed Fast SS-ILM algorithm decreases execution time of socially important locations discovery process up to 20 %.

Energy efficiency. Lever for the German energy transition

International Nuclear Information System (INIS)

Persem, Melanie; Roesner, Sven

2014-05-01

This document provides some key data on energy consumption in housing and public buildings, indicates the national German objectives in terms of reduction of energy consumption, of reduction of electricity consumption, of energy efficiency, and of evolution of energy consumption in housing and public buildings and in the transport sector. It gives some data related to energy saving and achievements: energy efficiency of the German economy, improvements in housing energy efficiency and insulation, financial support for low income households, reduction of energy consumption within small-medium enterprises, the public sector, the data processing sector and public lighting, and energy saving potential by renewal of public buildings. It indicates the main measures and arrangements: information, support programs for enterprises, local communities and individuals. A graph illustrates a comparison of shares of household power consumption in France and in Germany

Promotion of energy efficiency in enterprises

International Nuclear Information System (INIS)

Beltrani, G.; Schelske, O.; Peter, D.; Oettli, B.

2003-01-01

This comprehensive report for the Swiss Federal Office of Energy (SFOE) presents the results of a study made within the framework of the research programme on energy-economics fundamentals on how the energy efficiency of enterprises can be improved. The report first examines the present state of affairs in Swiss enterprises and looks into the interaction of energy efficiency and environmental management systems. ISO 14001 certification is discussed and examples are given of the responses of various enterprises to a survey concerning the role of energy efficiency in environmental management. Both hindrances and success factors for the embedding of energy-efficiency measures in environmental management activities are discussed and examples are given. Instruments available in Switzerland and from abroad that can be used to promote energy efficiency in enterprises are discussed. Four particular instruments are presented; guidelines and computer-based tools that help in the making of energy-relevant investment decisions, incentives to take part in an energy-benchmark system for small and medium-sized enterprises (SME), low-interest loans for investments in energy-efficiency for SMEs and the closer definition of 'continuous improvement' of energy efficiency within the framework of ISO 14001. The results of a survey amongst those involved are discussed. The report is concluded with recommendations for the implementation of the guidelines and for improvements in the integration of energy efficiency in environmental management systems

ECOWAS renewable energy and energy efficiency status report - 2014

International Nuclear Information System (INIS)

Auth, Katie; Musolino, Evan; Thomas, Tristram; Adebiyi, Adeola; Reiss, Karin; Semedo, Eder; Williamson, Laura E.; Chawla, Kanika; Diarra, Charles

2014-01-01

In recent years, the Economic Community of West African States (ECOWAS), comprising 15 Member States, it has emerged as one of the most active and dynamic regional economic communities on the African continent. Expanding access to modern, reliable, and affordable energy services is a key priority, prompting inter-state cooperation in crucial areas including capacity building, policy development and implementation, and investment. Recognising the critical role that sustainable energy plays in catalysing social, economic, and industrial development across the region, ECOWAS Member States formally inaugurated the ECOWAS Centre for Renewable Energy and Energy Efficiency (ECREEE) in 2010 to 'contribute to the sustainable economic, social and environmental development of West Africa by improving access to modern, reliable and affordable energy services, energy security and reduction of energy related externalities'. Drawing on data from the ECOWAS Observatory for Renewable Energy and Energy Efficiency (ECOWREX) and a network of contributors and researchers across the region, the ECOWAS Renewable Energy and Energy Efficiency Status Report supports ECREEE's efforts to increase the deployment of renewable energy and energy efficiency in West Africa by providing a comprehensive regional review of renewable energy and energy efficiency developments, evolving policy landscapes, market trends and related activities, investments in renewable energy and off-grid energy solutions, and the crucial nexus between energy access and gender

Industrial energy efficiency: A policy perspective

International Nuclear Information System (INIS)

Chandler, W.U.

1990-01-01

Policies that promote energy efficiency can work; but potential energy savings are unlikely to be realized without effective policy leadership. This article discusses the opportunities in several countries for increasing energy efficiency. Both ''open'' and centrally planned economies could be much more energy efficient. In the United States, for example, the government needs to stimulate energy efficiency. This could be done by sponsoring research to develop new processes, creating favourable financial conditions for investment in efficiency, and making the advantages of energy efficiency technologies better known. International collaboration in sponsoring research and transfer technologies could be of the greatest importance in improving energy efficiency in countries with centrally planned economies, including the Soviet Union, as well as in developing countries. Favourable conditions for achieving both economic development and environmental protection can be created through cooperation on the international level. (author). 24 refs, 4 tabs

Spin-neurons: A possible path to energy-efficient neuromorphic computers

Energy Technology Data Exchange (ETDEWEB)

Sharad, Mrigank; Fan, Deliang; Roy, Kaushik [School of Electrical and Computer Engineering, Purdue University, West Lafayette, Indiana 47907 (United States)

2013-12-21

Recent years have witnessed growing interest in the field of brain-inspired computing based on neural-network architectures. In order to translate the related algorithmic models into powerful, yet energy-efficient cognitive-computing hardware, computing-devices beyond CMOS may need to be explored. The suitability of such devices to this field of computing would strongly depend upon how closely their physical characteristics match with the essential computing primitives employed in such models. In this work, we discuss the rationale of applying emerging spin-torque devices for bio-inspired computing. Recent spin-torque experiments have shown the path to low-current, low-voltage, and high-speed magnetization switching in nano-scale magnetic devices. Such magneto-metallic, current-mode spin-torque switches can mimic the analog summing and “thresholding” operation of an artificial neuron with high energy-efficiency. Comparison with CMOS-based analog circuit-model of a neuron shows that “spin-neurons” (spin based circuit model of neurons) can achieve more than two orders of magnitude lower energy and beyond three orders of magnitude reduction in energy-delay product. The application of spin-neurons can therefore be an attractive option for neuromorphic computers of future.

CSA: An efficient algorithm to improve circular DNA multiple alignment

Directory of Open Access Journals (Sweden)

Pereira Luísa

2009-07-01

Full Text Available Abstract Background The comparison of homologous sequences from different species is an essential approach to reconstruct the evolutionary history of species and of the genes they harbour in their genomes. Several complete mitochondrial and nuclear genomes are now available, increasing the importance of using multiple sequence alignment algorithms in comparative genomics. MtDNA has long been used in phylogenetic analysis and errors in the alignments can lead to errors in the interpretation of evolutionary information. Although a large number of multiple sequence alignment algorithms have been proposed to date, they all deal with linear DNA and cannot handle directly circular DNA. Researchers interested in aligning circular DNA sequences must first rotate them to the "right" place using an essentially manual process, before they can use multiple sequence alignment tools. Results In this paper we propose an efficient algorithm that identifies the most interesting region to cut circular genomes in order to improve phylogenetic analysis when using standard multiple sequence alignment algorithms. This algorithm identifies the largest chain of non-repeated longest subsequences common to a set of circular mitochondrial DNA sequences. All the sequences are then rotated and made linear for multiple alignment purposes. To evaluate the effectiveness of this new tool, three different sets of mitochondrial DNA sequences were considered. Other tests considering randomly rotated sequences were also performed. The software package Arlequin was used to evaluate the standard genetic measures of the alignments obtained with and without the use of the CSA algorithm with two well known multiple alignment algorithms, the CLUSTALW and the MAVID tools, and also the visualization tool SinicView. Conclusion The results show that a circularization and rotation pre-processing step significantly improves the efficiency of public available multiple sequence alignment

Energy efficiency public service advertising campaign

Energy Technology Data Exchange (ETDEWEB)

Gibson-Grant, Amanda [Advertising Council, New York, NY (United States)

2015-06-12

The Advertising Council (“the Ad Council”) and The United States Department of Energy (DOE) created and launched a national public service advertising campaign designed to promote energy efficiency. The objective of the Energy Efficiency campaign was to redefine how consumers approach energy efficiency by showing that saving energy can save homeowners money.

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.

State Energy Efficiency Benefits and Opportunities

Science.gov (United States)

Describes the benefits of energy efficiency and how to assess its potential for your state. Also, find details on energy efficiency policies, programs, and resources available for furthering energy efficiency goals.

A Hybrid Node Scheduling Approach Based on Energy Efficient Chain Routing for WSN

Directory of Open Access Journals (Sweden)

Yimei Kang

2014-04-01

Full Text Available Energy efficiency is usually a significant goal in wireless sensor networks (WSNs. In this work, an energy efficient chain (EEC data routing approach is first presented. The coverage and connectivity of WSNs are discussed based on EEC. A hybrid node scheduling approach is then proposed. It includes sleep scheduling for cyclically monitoring regions of interest in time-driven modes and wakeup scheduling for tracking emergency events in event-driven modes. A failure rate is introduced to the sleep scheduling to improve the reliability of the system. A wakeup sensor threshold and a sleep time threshold are introduced in the wakeup scheduling to reduce the consumption of energy to the possible extent. The results of the simulation show that the proposed algorithm can extend the effective lifetime of the network to twice that of PEAS. In addition, the proposed methods are computing efficient because they are very simple to implement.

MODA: an efficient algorithm for network motif discovery in biological networks.

Science.gov (United States)

Omidi, Saeed; Schreiber, Falk; Masoudi-Nejad, Ali

2009-10-01

In recent years, interest has been growing in the study of complex networks. Since Erdös and Rényi (1960) proposed their random graph model about 50 years ago, many researchers have investigated and shaped this field. Many indicators have been proposed to assess the global features of networks. Recently, an active research area has developed in studying local features named motifs as the building blocks of networks. Unfortunately, network motif discovery is a computationally hard problem and finding rather large motifs (larger than 8 nodes) by means of current algorithms is impractical as it demands too much computational effort. In this paper, we present a new algorithm (MODA) that incorporates techniques such as a pattern growth approach for extracting larger motifs efficiently. We have tested our algorithm and found it able to identify larger motifs with more than 8 nodes more efficiently than most of the current state-of-the-art motif discovery algorithms. While most of the algorithms rely on induced subgraphs as motifs of the networks, MODA is able to extract both induced and non-induced subgraphs simultaneously. The MODA source code is freely available at: http://LBB.ut.ac.ir/Download/LBBsoft/MODA/

Applying a supervised ANN (artificial neural network) approach to the prognostication of driven wheel energy efficiency indices

International Nuclear Information System (INIS)

Taghavifar, Hamid; Mardani, Aref

2014-01-01

This paper examines the prediction of energy efficiency indices of driven wheels (i.e. traction coefficient and tractive power efficiency) as affected by wheel load, slippage and forward velocity at three different levels with three replicates to form a total of 162 data points. The pertinent experiments were carried out in the soil bin testing facility. A feed-forward ANN (artificial neural network) with standard BP (back propagation) algorithm was practiced to construct a supervised representation to predict the energy efficiency indices of driven wheels. It was deduced, in view of the statistical performance criteria (i.e. MSE (mean squared error) and R 2 ), that a supervised ANN with 3-8-10-2 topology and Levenberg–Marquardt training algorithm represented the optimal model. Modeling implementations indicated that ANN is a powerful technique to prognosticate the stochastic energy efficiency indices as affected by soil-wheel interactions with MSE of 0.001194 and R 2 of 0.987 and 0.9772 for traction coefficient and tractive power efficiency. It was found that traction coefficient and tractive power efficiency increase with increased slippage. A similar trend is valid for the influence of wheel load on the objective parameters. Wherein increase of velocity led to an increment of tractive power efficiency, velocity had no significant effect on traction coefficient. - Highlights: • Energy efficiency indexes were assessed as affected by tire parameters. • ANN was applied for prognostication of the objective parameters. • A 3-8-10-2 ANN with MSE of 0.001194 and R 2 of 0.987 and 0.9772 was designated as optimal model. • Optimal values of learning rate and momentum were found 0.9 and 0.5, respectively

Scheduling algorithms for saving energy and balancing load

Energy Technology Data Exchange (ETDEWEB)

Antoniadis, Antonios

2012-08-03

In this thesis we study problems of scheduling tasks in computing environments. We consider both the modern objective function of minimizing energy consumption, and the classical objective of balancing load across machines. We first investigate offline deadline-based scheduling in the setting of a single variable-speed processor that is equipped with a sleep state. The objective is that of minimizing the total energy consumption. Apart from settling the complexity of the problem by showing its NP-hardness, we provide a lower bound of 2 for general convex power functions, and a particular natural class of schedules called s{sub crit}-schedules. We also present an algorithmic framework for designing good approximation algorithms. For general convex power functions our framework improves the best known approximation-factor from 2 to 4/3. This factor can be reduced even further to 137/117 for a specific well-motivated class of power functions. Furthermore, we give tight bounds to show that our framework returns optimal s{sub crit}-schedules for the two aforementioned power-function classes. We then focus on the multiprocessor setting where each processor has the ability to vary its speed. Job migration is allowed, and we again consider classical deadline-based scheduling with the objective of energy minimization. We first study the offline problem and show that optimal schedules can be computed efficiently in polynomial time for any convex and non-decreasing power function. Our algorithm relies on repeated maximum flow computations. Regarding the online problem and power functions P(s) = s{sup {alpha}}, where s is the processor speed and {alpha} > 1 a constant, we extend the two well-known single-processor algorithms Optimal Available and Average Rate. We prove that Optimal Available is {alpha}{sup {alpha}}-competitive as in the single-processor case. For Average Rate we show a competitive factor of (2{alpha}){sup {alpha}}/2 + 1, i.e., compared to the single

Promoting energy efficiency in Egyptian industry

International Nuclear Information System (INIS)

Selim, M.H.

1990-01-01

The energy situation in Egypt is characterized by a rather high energy demand, a high annual increase in energy consumption, inefficient utilization of energy, and heavily subsidized energy prices. Energy efficiency is therefore considered to be a matter of top priority, as it would lead to substantial savings. A national policy for efficient use of energy in industry has been outlined, including the establishment of an Industrial Energy Conservation Centre (IECC), the training and upgrading of energy management specialists, and the introduction of energy efficiency technologies in industrial plants. In this article the assistance that international organizations and donors can give to energy efficiency programmes is demonstrated. The results obtained so far are discussed and the lessons, findings and experience gained are outlined. (author). 1 tab

Energy Efficiency in Swimming Facilities

OpenAIRE

Kampel, Wolfgang

2015-01-01

High and increasing energy use is a worldwide issue that has been reported and documented in the literature. Various studies have been performed on renewable energy and energy efficiency to counteract this trend. Although using renewable energy sources reduces pollution, improvements in energy efficiency reduce total energy use and protect the environment from further damage. In Europe, 40 % of the total energy use is linked to buildings, making them a main objective concerning...

Energy Efficiency Indicators Methodology Booklet

Energy Technology Data Exchange (ETDEWEB)

Sathaye, Jayant; Price, Lynn; McNeil, Michael; de la rue du Can, Stephane

2010-05-01

This Methodology Booklet provides a comprehensive review and methodology guiding principles for constructing energy efficiency indicators, with illustrative examples of application to individual countries. It reviews work done by international agencies and national government in constructing meaningful energy efficiency indicators that help policy makers to assess changes in energy efficiency over time. Building on past OECD experience and best practices, and the knowledge of these countries' institutions, relevant sources of information to construct an energy indicator database are identified. A framework based on levels of hierarchy of indicators -- spanning from aggregate, macro level to disaggregated end-use level metrics -- is presented to help shape the understanding of assessing energy efficiency. In each sector of activity: industry, commercial, residential, agriculture and transport, indicators are presented and recommendations to distinguish the different factors affecting energy use are highlighted. The methodology booklet addresses specifically issues that are relevant to developing indicators where activity is a major factor driving energy demand. A companion spreadsheet tool is available upon request.

Interactions between Energy Efficiency Programs funded under the Recovery Act and Utility Customer-Funded Energy Efficiency Programs

Energy Technology Data Exchange (ETDEWEB)

Goldman, Charles A.; Stuart, Elizabeth; Hoffman, Ian; Fuller, Merrian C.; Billingsley, Megan A.

2011-02-25

Since the spring of 2009, billions of federal dollars have been allocated to state and local governments as grants for energy efficiency and renewable energy projects and programs. The scale of this American Reinvestment and Recovery Act (ARRA) funding, focused on 'shovel-ready' projects to create and retain jobs, is unprecedented. Thousands of newly funded players - cities, counties, states, and tribes - and thousands of programs and projects are entering the existing landscape of energy efficiency programs for the first time or expanding their reach. The nation's experience base with energy efficiency is growing enormously, fed by federal dollars and driven by broader objectives than saving energy alone. State and local officials made countless choices in developing portfolios of ARRA-funded energy efficiency programs and deciding how their programs would relate to existing efficiency programs funded by utility customers. Those choices are worth examining as bellwethers of a future world where there may be multiple program administrators and funding sources in many states. What are the opportunities and challenges of this new environment? What short- and long-term impacts will this large, infusion of funds have on utility customer-funded programs; for example, on infrastructure for delivering energy efficiency services or on customer willingness to invest in energy efficiency? To what extent has the attribution of energy savings been a critical issue, especially where administrators of utility customer-funded energy efficiency programs have performance or shareholder incentives? Do the new ARRA-funded energy efficiency programs provide insights on roles or activities that are particularly well-suited to state and local program administrators vs. administrators or implementers of utility customer-funded programs? The answers could have important implications for the future of U.S. energy efficiency. This report focuses on a selected set of ARRA