基于演化博弈的无线传感器网络分簇算法
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摘要
针对无线传感器网络中节点负载过重与能耗不均衡而出现网络能量空洞的问题,基于演化博弈理论建立一种簇头竞选的博弈模型,同时提出一种基于演化博弈的无线传感器网络最优成簇算法。运用节点的剩余能量、数据接收能耗和数据转发能耗设计簇头演化博弈的收益函数,并将最优发射功率控制机制应用于簇成员的选择,从而形成稳定连通的网络分簇结构。仿真实验表明该算法平衡了节点负载,从而均衡网络能量,有效改善网络中过早出现能量空洞的问题,进而延长了网络生存时间。
Aiming at the problem of energy hole arising from overloaded nodes and unbalanced energy consumption in wireless sensor network, evolutionary game theory is used to establish a game model of the cluster head race, and an optimal clustering algorithm based on evolutionary game for wireless sensor networks is proposed in this paper. The residual energy of nodes, data receiving energy consumption and data forwarding energy consumption are used to design the revenue function of cluster head in the evolutionary game model, and the optimal transmit power control mechanism is applied to the selection of cluster members, thereby forming a stable connected network clustering structure. The simulation results show that the algorithm balances the load of nodes and the energy of the network. It also effectively improves the premature emergence of energy holes in the network and extends the network lifetime.
Aiming at the problem of energy hole arising from overloaded nodes and unbalanced energy consumption in wireless sensor network, evolutionary game theory is used to establish a game model of the cluster head race, and an optimal clustering algorithm based on evolutionary game for wireless sensor networks is proposed in this paper. The residual energy of nodes, data receiving energy consumption and data forwarding energy consumption are used to design the revenue function of cluster head in the evolutionary game model, and the optimal transmit power control mechanism is applied to the selection of cluster members, thereby forming a stable connected network clustering structure. The simulation results show that the algorithm balances the load of nodes and the energy of the network. It also effectively improves the premature emergence of energy holes in the network and extends the network lifetime.
引文
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[2]钱志鸿,王义君.面向物联网的无线传感器网络综述[J].电子与信息学报,2013,35(1):215-227.
[3]Radi M,Dezfouli B,Abu B K,et al.Multipath routing in wireless sensor networks:survey and research challenges[J].Sensors,2012,12(1):650-685.
[4]Lohani D,Varma S.Energy efficient data aggregation in mobile agent based wireless sensor network[J].Wireless Personal Communications,2016,89(4):1165-1176.
[5]李方敏,刘新华,旷海兰,等.基于最优连通功率的无线传感器网络稳定成簇算法[J].通信学报,2009,30(3):75-83.
[6]黄利晓,王晖,袁利永,等.基于能量均衡高效WSN的LEACH协议改进算法[J].通信学报,2017,38(S2):164-169.
[7]王磊,谢弯弯,刘志中,等.非均匀分簇路由协议改进算法[J].计算机科学,2017,44(2):152-156.
[8]Lin D,Wang Q.A game theory based energy efficient clustering routing protocol for WSNs[J].Wireless Networks,2017,23(4):1-11.
[9]Tembine H,Altman E,Azouzi R,et al.Evolutionary games in wireless networks[J].IEEE Transactions on Systems Man&Cybernetics Part B Cybernetics A Publication of the IEEE Systems Man&Cybernetics Society,2010,40(3):634-646.
[10]Chen X,Yin Y,Xu Z.A game-theoretic approach for efficient clustering in wireless sensor networks[C]//International Conference on Computational&Information Sciences,2013:1663-1666.
[11]Xie D,Sun Q,Zhou Q,et al.An efficient clustering protocol for wireless sensor networks based on localized game theoretical approach[J].International Journal of Distributed Sensor Networks,2013:264-273.
[12]董荣胜,孙栋栋,郭云川,等.基于演化博弈论的功率控制和垂直切换研究[J].计算机研究与发展,2014,51(6):1185-1198.
[13]Chen Z,Qiao C,Qiu Y,et al.Dynamics stability in wireless sensor networks active defense model[J].Journal of Computer&System Sciences,2014,80(8):1534-1548.
[14]Koltsidas G,Pavlidou F N.A game theoretical approach to clustering of ad-hoc and sensor networks[J].Telecommunication Systems,2011,47(1/2):81-93.
[15]Purvis M,Deng J D,Aderohunmu F A.Enhancing clustering in wireless sensor networks with energy heterogeneity[J].International Journal of Business Data Communications&Networking,2013,7(4):18-31.2500 30002500 30002500 30002500 3000