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A Game-Theoretic and energy-efficient algorithm in an Improved Software-Defined Wireless Sensor Network

IEEE ACCESS 2017年 5卷 13430-13445页

作者： Li Peizhe Wu Muqing Liao Wenxing Zhao Min Beijing Univ Posts & Telecommun Sch Informat & Commun Engn Beijing 100876 Peoples R China

Because wireless sensor networks (WSNs) are becoming increasingly integrated into daily life, solving the energy efficiency problem of such networks is an urgent problem. Many energy-efficient algorithms have been proposed to reduce energy consumption in traditional WSNs. The emergence of software defined networks (SDNs) enables the transformation of WSNs. Some SDN-based WSNs architectures have been proposed and energy-efficient algorithms in SDN-based WSNs architectures have been studied. In this paper, we integrate an SDN into WSNs and an improved software-defined WSNs (SD-WSNs) architecture is presented. Based on the improved SD-WSNs architecture, we propose an energy-efficient algorithm. This energy-efficient algorithm is designed to match the SD-WSNs architecture, and is based on the residual energy and the transmission power, and the game theory is introduced to extend the network lifetime. Based on the SD-WSNs architecture and the energy-efficient algorithm, we provide a detailed introduction to the operating mechanism of the algorithm in the SD-WSNs. The simulation results show that our proposed algorithm performs better in terms of balancing energy consumption and extending the network lifetime compared with the typical energy-efficient algorithms in traditional WSNs.

关键词： SD-WSNs OPGEA WSNs game theory energy-efficient algorithm

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Design of multi-energy-space-based energy-efficient algorithm in novel software-defined wireless sensor networks

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INTERNATIONAL JOURNAL OF DISTRIBUTED SENSOR NETWORKS 2017年第7期13卷 1-1页

作者： Liao Wenxing Wu Muqing Wu Yuewei Beijing Univ Posts & Telecommun Beijing Lab Adv Informat Networks Beijing 100876 Peoples R China Beijing Univ Posts & Telecommun Beijing Key Lab Network Syst Architecture & Conve Beijing 100876 Peoples R China Beijing Univ Posts & Telecommun Sch Elect Engn Beijing Peoples R China

energy efficiency has always been a hot issue in wireless sensor networks. A lot of energy-efficient algorithms have been proposed to reduce energy consumption in traditional wireless sensor networks. With the emergence of software-defined networking, researchers have demonstrated the feasibility of software-defined networking over traditional wireless sensor networks. Thus, energy-efficient algorithms in software-defined wireless sensor networks have been studied. In this article, we propose an energy-efficient algorithm based on multi-energy-space in software-defined wireless sensor networks. First, we propose a novel architecture of software-defined wireless sensor networks according to current research on software-defined wireless sensor networks. Then, we introduce the concept of multi-energy-space which is based on the residual energy. Based on the novel architecture of software-defined wireless sensor networks and the concept of multi-energy-space, we give a detailed introduction of the main idea of our multi-energy-space-based energy-efficient algorithm. Simulation results show that our proposed algorithm performs better in energy consumption balance and network lifetime extension compared with the typical energy-efficient algorithms in traditional wireless sensor networks.

关键词： Software-defined wireless sensor networks network architecture design energy-efficient algorithm multi-energy-space energy consumption balance network lifetime

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An optimal energy-efficient clustering method in wireless sensor networks using multi-objective genetic algorithm

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INTERNATIONAL JOURNAL OF COMMUNICATION SYSTEMS 2013年第1期26卷 114-126页

作者： Peiravi, Ali Mashhadi, Habib Rajabi Javadi, S. Hamed Ferdowsi Univ Mashhad Dept Elect Engn Mashhad Iran

In this study, an optimal method of clustering homogeneous wireless sensor networks using a multi-objective two-nested genetic algorithm is presented. The top level algorithm is a multi-objective genetic algorithm (GA) whose goal is to obtain clustering schemes in which the network lifetime is optimized for different delay values. The low level GA is used in each cluster in order to get the most efficient topology for data transmission from sensor nodes to the cluster head. The presented clustering method is not restrictive, whereas existing intelligent clustering methods impose certain conditions such as performing two-tiered clustering. A random deployed model is used to demonstrate the efficiency of the proposed algorithm. In addition, a comparison is made between the presented algorithm other GA-based clustering methods and the Low energy Adaptive Clustering Hierarchy protocol. The results obtained indicate that using the proposed method, the network's lifetime would be extended much more than it would be when using the other methods. Copyright (C) 2011 John Wiley & Sons, Ltd.

关键词： clustering energy-efficient algorithm multi-objective genetic algorithm wireless sensor network

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On Power Management Policies for Data Centers

On Power Management Policies for Data Centers

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IEEE International Conference on Data Science and Data Intensive Systems

作者： Haas, Zygmunt J. Gu, Shuyang Cornell Univ Sch Elect & Comp Engn Ithaca NY 14850 USA Univ Texas Dallas Erik Jonsson Sch Engn & Comp Sci Richardson TX 75083 USA

ISBN: (纸本)9781509002146

One of the most important practical and timely operational problem associated with the performance of data centers for cloud computing is energy consumption. The fundamental approach for saving energy in a data center is right-sizing the number of servers;i.e., the determination of the minimum required number of servers to meet the load demand, allowing unnecessary servers to be turned off, so that energy usage can be minimized. The main challenge in designing such right-sizing algorithms is the fact that servers cannot be turned on instantaneously, so typically some estimation of the futuristic load is needed. Of course, the more uncorrelated the load arrival, the less accurate is such estimation. As the problem of right-sizing is NP-complete, a heuristic algorithm is required for practical deployment. In this paper, we first develop an efficient offline right-sizing heuristic, and we demonstrate that its performance is close to optimal. Rather than classifying jobs into a fixed number of types as prior works do, every arriving job is characterized with its own latency tolerance profile. Our offline heuristic, taking advantage of this latency tolerance, attempts to rearranges the jobs' processing times, so that the overall servers' demand is "smoothed". Then, based on the offline algorithm, we design an online algorithm that computes the real-time servers' right-sizing according to the arriving workload. As the key result of this paper, we show that the performance of the online algorithm closely approximates the performance of the offline algorithm, and that both closely approximate the optimal solution. We also demonstrate that the use of our algorithm corresponds to an over 50% operational cost reduction of a data center.

关键词： data centers right-sizing job profiling energy-efficient algorithm

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energy-efficient Admission of Delay-Sensitive Tasks for multi-Mobile Edge Computing Servers 25

Energy-Efficient Admission of Delay-Sensitive Tasks for mult...

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25th IEEE International Conference on Parallel and Distributed Systems (IEEE ICPADS)

作者： Wang, Jianrong Yue, Yuanzhi Wang, Ru Yu, Mei Yu, Jian Liu, Hongwei Ying, Xiang Yu, Ruiguo Tianjin Univ Tianjin Int Engn Inst Tianjin Peoples R China Tianjin Univ Coll Intelligence & Comp Tianjin Peoples R China Tianjin Key Lab Adv Networking TANK Lab Tianjin Peoples R China Tianjin Key Lab Cognit Comp & Applicat Tianjin Peoples R China Tianjin Foreign Studies Univ Foreign Language Literature & Culture Studies Ctr Tianjin Peoples R China

ISBN: (纸本)9781728125831

For delay-sensitive applications in mobile edge computing (MEC), task admission approach is of vital importance, and there has been a lot of researches in this field. But previous works focus on the situation with only one MEC server that is a simplification of the real world. In multi-servers situation, some devices may be within the service range of multiple MEC servers, so that they could choose which MEC server to offload. We formulate this problem to a multiple-choice integer program (MCIP) and utilize Ben's genetic algorithm to solve it. The simulation results show that our approach can significantly reduce energy consumption and every task can catch its deadline under almost all experiments.

关键词： Mobile Edge Computing Multiple-Choice Integer Program energy-efficient algorithm

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Routing, Modulation Level and Spectrum Assignment Considering energy Consumption in C+L-Bands Optical Network 22

Routing, Modulation Level and Spectrum Assignment Considerin...

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22nd International Conference on Optical Communications and Networks, ICOCN 2024

作者： Liu, Kaiwen You, Chenyu Yin, Shan Liu, Xiaodong Cai, Mengru Huang, Shanguo Beijing University of Posts and Telecommunications Beijing China

We establish network energy consumption model, propose routing, modulation level, spectrum assignment algorithm considering energy consumption based on DDPG. Simulation results show that this algorithm can effectively... 详细信息

ISBN: (纸本)9798350367652

关键词： C+L-bands EONs DDPG energy consumption model energy-efficient algorithm RMLSA

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efficient Data Collection by Mobile Sink to Detect Phenomena in Internet of Things

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INFORMATION 2017年第4期8卷 123页

作者： Abu Safia, Amany Al Aghbari, Zaher Kamel, Ibrahim Univ Sharjah Dept Comp Sci POB 27272 Sharjah U Arab Emirates Univ Sharjah Dept Elect & Comp Engn POB 27272 Sharjah U Arab Emirates

With the rapid development of Internet of Things (IoT), more and more static and mobile sensors are being deployed for sensing and tracking environmental phenomena, such as fire, oil spills and air pollution. As these sensors are usually battery-powered, energy-efficient algorithms are required to extend the sensors' lifetime. Moreover, forwarding sensed data towards a static sink causes quick battery depletion of the sinks' nearby sensors. Therefore, in this paper, we propose a distributed energy-efficient algorithm, called the Hilbert-order Collection Strategy (HCS), which uses a mobile sink (e.g., drone) to collect data from a mobile wireless sensor network (mWSN) and detect environmental phenomena. The mWSN consists of mobile sensors that sense environmental data. These mobile sensors self-organize themselves into groups. The sensors of each group elect a group head (GH), which collects data from the mobile sensors in its group. Periodically, a mobile sink passes by the locations of the GHs (data collection path) to collect their data. The collected data are aggregated to discover a global phenomenon. To shorten the data collection path, which results in reducing the energy cost, the mobile sink establishes the path based on the order of Hilbert values of the GHs' locations. Furthermore, the paper proposes two optimization techniques for data collection to further reduce the energy cost of mWSN and reduce the data loss.

关键词： mobile wireless sensor networks phenomena detection mobile sink energy-efficient algorithm IoT

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energy-efficient Admission of Delay-Sensitive Tasks for Multi-Mobile Edge Computing Servers

Energy-Efficient Admission of Delay-Sensitive Tasks for Mult...

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International Conference on Parallel and Distributed Systems (ICPADS)

作者： Jianrong Wang Yuanzhi Yue Ru Wang Mei Yu Jian Yu Hongwei Liu Xiang Ying Ruiguo Yu Tianjin International Engineering Institute Tianjin University Tianjin China College of Intelligence and Computing Tianjin University Tianjin China Tianjin Key Laboratory of Advanced Networking (TANK Lab) Tianjin China Tianjin Key Laboratory of Cognitive Computing and Application Tianjin China Foreign Language Tianjin Foreign Studies University Tianjin China

ISBN: (纸本)9781728125848

关键词： Mobile edge computing Multiple-Choice integer program energy-efficient algorithm Servers most economic control CCL28 gene Simulation results simplification energy efficiency UNLOADING

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Sleeping is efficient: MIS in O(1)-rounds Node-averaged Awake Complexity 20

Sleeping is Efficient: MIS in O(1)-rounds Node-averaged Awak...

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39th Symposium on Principles of Distributed Computing

作者： Chatterjee, Soumyottam Gmyr, Robert Pandurangan, Gopal Georgetown Univ Washington DC 20057 USA Microsoft Redmond WA USA Univ Houston Houston TX USA

ISBN: (纸本)9781450375825

Maximal Independent Set (MIS) is one of the fundamental problems in distributed computing. The round (time) complexity of distributed MIS has traditionally focused on the worst-case time for all nodes to finish. The best-known (randomized) MIS algorithms take O(log n) worst-case rounds on general graphs (where.. is the number of nodes). Breaking the O(log n) worst-case bound has been a longstanding open problem, while currently the best-known lower bound is Omega(root log n/log log n) rounds. Motivated by the goal to reduce total energy consumption in energy-constrained networks such as sensor and ad hoc wireless networks, we take an alternative approach to measuring performance. We focus on minimizing the total (or equivalently, the average) time for all nodes to finish. It is not clear whether the currently best-known algorithms yield constant-round (or even o(log n)) node-averaged round complexity for MIS in general graphs. We posit the sleeping model, a generalization of the traditional model, that allows nodes to enter either "sleep" or "waking" states at any round. While waking state corresponds to the default state in the traditional model, in sleeping state a node is "offline", i.e., it does not send or receive messages (and messages sent to it are dropped as well) and does not incur any time, communication, or local computation cost. Hence, in this model, only rounds in which a node is awake are counted and we are interested in minimizing the average as well as the worst-case number of rounds a node spends in the awake state, besides the traditional worst-case round complexity (i.e., the rounds for all nodes to finish including both the awake and sleeping rounds). Our main result is that we show that MIS can be solved in (expected) O(1) rounds under node-averaged awake complexity measure in the sleeping model. In particular, we present a randomized distributed algorithm for MIS that has expected O(1)-rounds node-averaged awake complexity and, with high prob

关键词： Maximal Independent Set sleeping model node-averaged round complexity awake complexity resource-efficient algorithm MIS energy-efficient algorithm energy-efficiency

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