一种无线传感器网络能耗均衡的自适应拓扑博弈算法
|
摘要
针对无线传感器网络节点能量有限与能耗不均衡导致网络生命周期提前结束的问题,运用势博弈理论将节点的平均寿命、节点最短寿命、网络的连通性以及覆盖性应用到效益函数的设计中,建立一种基于序数势博弈的能耗均衡的拓扑控制模型,以证明博弈模型是序数势博弈.基于该势博弈模型,提出一种能耗均衡的自适应拓扑博弈算法.该算法根据节点平均寿命调整自身的功率,帮助最短寿命节点降低功率,延长整个网络的生存时间.仿真实验及对比分析表明,所提出的算法相比于其他基于博弈论的拓扑控制算法,能够改善网络能量的均衡性,提高网络能量效率,保证网络拓扑的健壮性,增强网络拓扑的自适应性.
In order to solve the problems in wireless sensor network that the energy of node is limited and the energy consumption is unbalanced which leads to the premature termination of the network lifetime, an energy-balanced topology control model based on the potential game is constructed in this paper. The average lifespan and the shortest lifespan of nodes, the connectivity and coverage of the networks are used in the design of the utilization function in the model.The game model is proved to be an ordinal potential game. An energy-balanced and self-adaptation topology control game(ATCG) algorithm in wireless sensor networks is proposed based on this topology control model. According to the average life of nodes, the nodes adjust their own power to help nodes with the shortest life to reduce transmitting power,which can prolong the entire network life. By simulation and comparative analysis, compared with other game-based topology control algorithms, the energy balance and energy efficiency of the network are improved, the robustness of the network topology is guaranteed and the adaptability of the network topology is enhanced in ATCG.
In order to solve the problems in wireless sensor network that the energy of node is limited and the energy consumption is unbalanced which leads to the premature termination of the network lifetime, an energy-balanced topology control model based on the potential game is constructed in this paper. The average lifespan and the shortest lifespan of nodes, the connectivity and coverage of the networks are used in the design of the utilization function in the model.The game model is proved to be an ordinal potential game. An energy-balanced and self-adaptation topology control game(ATCG) algorithm in wireless sensor networks is proposed based on this topology control model. According to the average life of nodes, the nodes adjust their own power to help nodes with the shortest life to reduce transmitting power,which can prolong the entire network life. By simulation and comparative analysis, compared with other game-based topology control algorithms, the energy balance and energy efficiency of the network are improved, the robustness of the network topology is guaranteed and the adaptability of the network topology is enhanced in ATCG.
引文
[1] Farruh Ishmanov, Malik A S, Kim S W. Energy consumption balancing(ECB)issues and mechanisms in wireless sensor networks(WSNs):A comprehensive overview[J]. European Trans on Telecommunications,2011, 22(4):151-167.
[2]张学,陆桑璐,陈贵海,等.无线传感器网络的拓扑控制[J].软件学报, 2007, 18(4):943-954.(Zhang X, Lu S L, Chen G H, et al. Topology control for wireless sensor networks[J]. J of Software, 2007, 18(4):943-954.)
[3]李晓鸿,王文艳,王东.一种最大化Ad-Hoc网络生存期的拓扑控制算法[J].计算机研究与发展, 2013, 50(3):461-471.(Li X H, Wang W Y, Wang D. Extending the network lifetime using topology control in Ad Hoc networks[J].J of Computer Research and Development, 2013, 50(3):461-471.)
[4] Kubisch M, Karl H, Wolisz A, et al. Distributed algorithms for transmission power control in wireless sensor networks[C]. Proc of the IEEE Wireless Communications and Networking Conf. New York:IEEE Press, 2003:558-563.
[5] Heinzelman W R, Chandrakasan A, Balakrishnan H.Anapplication specific protocol architecture for wireless microsensor networks[J]. IEEE Trans on Wireless Communications, 2002, 1(4):660-670.
[6]沈士根,马绚,蒋华,等.基于演化博弈论的WSNs信任决策模型与动力学分析[J].控制与决策, 2012, 27(8):1133-1138.(Shen S G, Ma X, Jiang H, et al. Evolutionary game theory based trust strategy model and dynamics analysis in wireless sensor networks[J]. Control and Decision,2012, 27(8):1133-1138.)
[7] Lin D, Wang Q. A game theory based energy efficient clustering routing protocol for WSNs[J]. Wireless Networks, 2016, 23(4):1101–1111.
[8] Yang L, Lu Y Z, Zhong Y C, et al. A hybrid, game theory based, and distributed clustering protocol for wireless sensor networks[J]. Wireless Networks, 2016, 22(3):1007-1021.
[9] Komali R S, Mackenzie A B, Gilles R P. Effect of selfish node behavior on efficient topology design[J]. IEEE Trans on Mobile Computing, 2008, 7(9):1057-1070.
[10]李小龙,冯东磊,彭鹏程.一种基于势博弈的无线传感器网络拓扑控制算法[J].物理学报, 2016, 65(2):346-355.(Li X L, Feng D L, Peng P C. A topology control algorithm based on potential game for wireless sensor networks[J].Acta Physica Sinica, 2016, 65(2):346-355.)
[11]董荣胜,马争先,郭云川,等.一种基于马尔可夫博弈的能量均衡路由算法[J].计算机学报, 2013, 36(7):1500-1508.(Dong R S, Ma Z X, Guo Y C, et al. A markov game theory based energy balance routing algorithm[J]. Chinese J of Computers, 2013, 36(7):1500-1508.)
[12] Chu X, Sethu H. Cooperative topology control with adaptation for improved lifetime in wireless ad hoc networks[C]. IEEE INFOCOM. Orlando:Proc IEEE,2012:262-270.
[13]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.(Dong R S, Sun D D, Guo Y C, et al. Power control and vertical handoff based on evolutionary game theory[J].J of Computer Research and Development, 2014, 51(6):1185-1198.)
[14] Charilas D E, Panagopoulos A D. A survey on game theory applications in wireless networks[J]. Computer Networks, 2010, 54(18):3421-3430.
[15] Rasmusen E. Games and information:An introduction to game theory[M]. 4th ed. Oxford:Blackwell Publishing,2006:26-33.
[16] Hao X C, Zhang Y X, Jia N, et al. Virtual game based energy balanced topology control algorithm for wireless sensor networks[J]. Wireless Personal Communications,2013, 69(4):1289-1308.
[17] Chen X M, Cai Y M, Yu Z, et al. Topology control algorithm based on game theory in wireless sensor networks[J]. J of PLA University of Science and Technology, 2011, 12(5):414-418.
[18] Chu X, Sethu H. Cooperative topology control with adaptation for improved lifetime in wireless sensor networks[J]. Ad Hoc Networks, 2015, 30(C):99-114.
[2]张学,陆桑璐,陈贵海,等.无线传感器网络的拓扑控制[J].软件学报, 2007, 18(4):943-954.(Zhang X, Lu S L, Chen G H, et al. Topology control for wireless sensor networks[J]. J of Software, 2007, 18(4):943-954.)
[3]李晓鸿,王文艳,王东.一种最大化Ad-Hoc网络生存期的拓扑控制算法[J].计算机研究与发展, 2013, 50(3):461-471.(Li X H, Wang W Y, Wang D. Extending the network lifetime using topology control in Ad Hoc networks[J].J of Computer Research and Development, 2013, 50(3):461-471.)
[4] Kubisch M, Karl H, Wolisz A, et al. Distributed algorithms for transmission power control in wireless sensor networks[C]. Proc of the IEEE Wireless Communications and Networking Conf. New York:IEEE Press, 2003:558-563.
[5] Heinzelman W R, Chandrakasan A, Balakrishnan H.Anapplication specific protocol architecture for wireless microsensor networks[J]. IEEE Trans on Wireless Communications, 2002, 1(4):660-670.
[6]沈士根,马绚,蒋华,等.基于演化博弈论的WSNs信任决策模型与动力学分析[J].控制与决策, 2012, 27(8):1133-1138.(Shen S G, Ma X, Jiang H, et al. Evolutionary game theory based trust strategy model and dynamics analysis in wireless sensor networks[J]. Control and Decision,2012, 27(8):1133-1138.)
[7] Lin D, Wang Q. A game theory based energy efficient clustering routing protocol for WSNs[J]. Wireless Networks, 2016, 23(4):1101–1111.
[8] Yang L, Lu Y Z, Zhong Y C, et al. A hybrid, game theory based, and distributed clustering protocol for wireless sensor networks[J]. Wireless Networks, 2016, 22(3):1007-1021.
[9] Komali R S, Mackenzie A B, Gilles R P. Effect of selfish node behavior on efficient topology design[J]. IEEE Trans on Mobile Computing, 2008, 7(9):1057-1070.
[10]李小龙,冯东磊,彭鹏程.一种基于势博弈的无线传感器网络拓扑控制算法[J].物理学报, 2016, 65(2):346-355.(Li X L, Feng D L, Peng P C. A topology control algorithm based on potential game for wireless sensor networks[J].Acta Physica Sinica, 2016, 65(2):346-355.)
[11]董荣胜,马争先,郭云川,等.一种基于马尔可夫博弈的能量均衡路由算法[J].计算机学报, 2013, 36(7):1500-1508.(Dong R S, Ma Z X, Guo Y C, et al. A markov game theory based energy balance routing algorithm[J]. Chinese J of Computers, 2013, 36(7):1500-1508.)
[12] Chu X, Sethu H. Cooperative topology control with adaptation for improved lifetime in wireless ad hoc networks[C]. IEEE INFOCOM. Orlando:Proc IEEE,2012:262-270.
[13]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.(Dong R S, Sun D D, Guo Y C, et al. Power control and vertical handoff based on evolutionary game theory[J].J of Computer Research and Development, 2014, 51(6):1185-1198.)
[14] Charilas D E, Panagopoulos A D. A survey on game theory applications in wireless networks[J]. Computer Networks, 2010, 54(18):3421-3430.
[15] Rasmusen E. Games and information:An introduction to game theory[M]. 4th ed. Oxford:Blackwell Publishing,2006:26-33.
[16] Hao X C, Zhang Y X, Jia N, et al. Virtual game based energy balanced topology control algorithm for wireless sensor networks[J]. Wireless Personal Communications,2013, 69(4):1289-1308.
[17] Chen X M, Cai Y M, Yu Z, et al. Topology control algorithm based on game theory in wireless sensor networks[J]. J of PLA University of Science and Technology, 2011, 12(5):414-418.
[18] Chu X, Sethu H. Cooperative topology control with adaptation for improved lifetime in wireless sensor networks[J]. Ad Hoc Networks, 2015, 30(C):99-114.