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基于生命期模型的无线传感器网络信道分配博弈算法

郝晓辰 姚宁 汝小月 刘伟静 辛敏洁

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基于生命期模型的无线传感器网络信道分配博弈算法

郝晓辰, 姚宁, 汝小月, 刘伟静, 辛敏洁

Channel allocation game algorithm based on lifetime model in wireless sensor network

Hao Xiao-Chen, Yao Ning, Ru Xiao-Yue, Liu Wei-Jing, Xin Min-Jie
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  • 针对无线传感器网络中节点因干扰过大导致重传能耗增加, 进而节点过早失效、网络生命期缩短的问题, 根据网络拓扑信息和路由信息设计节点的负载模型, 从而构建了节点的生命期模型. 然后利用博弈论将路径增益、交叉干扰和节点生命期等性能参数融入到效益函数中, 构建信道分配博弈模型. 理论分析证明该博弈模型存在纳什均衡. 进而运用最佳回应策略, 在所构建的信道分配博弈模型的基础上, 设计了一种优化网络生命期的抗干扰信道分配算法. 该算法使节点在选择信道时避免与网络中交叉干扰较大的节点和生命期较小的节点使用相同信道, 实现干扰小、能耗低且均衡的信道选择. 理论分析与仿真结果证明该算法最终能够快速地收敛到纳什均衡, 且具有较小的信息复杂度, 从而减小算法本身的通信能耗. 同时, 该算法具有良好的抗干扰性和信道均衡性, 能够有效地延长网络生命期.
    In wireless sensor network, the lager interference makes the data transmission failed, thus leading to data retransmission of nodes. This situation exacerbates the energy consumption of retransmission. As a result, some nodes will prematurely fail to work, thus reducing the network lifetime. In order to deal with the above issue, this paper takes full advantage of the topology and route information to design a novel load model of nodes. Then, a lifetime model of each node is constructed based on the load model. Subsequently, the path gain, intersecting interference and node lifetime are integrated into a utility function to construct a channel allocation game model called channel allocation based-game (CABG) by taking advantage of the game theory. The theoretical analysis proves the existence of the Nash Equilibrium of CABG. And then, using the best response dynamics, a channel allocation game algorithm for anti-interference and lifetime optimization (CAGLO) is established based on CABG. This algorithm CAGLO makes nodes avoid selecting the same channel as the large intersecting interference nodes and shorter-lifetime nodes in the process of channel selection, thus realizing the channel selection with less interference, less and balanced energy consumption. The theoretical analysis and simulation results show that the algorithm CAGLO could converge to the Nash Equilibrium with a good convergence speed finally. And the algorithm CAGLO has less message complexity. As a result, the algorithm itself has less energy consumption of communication. At the same time, it has good characteristics of anti-interference, energy consumption equilibrium and channel equalization. The algorithm CAGLO proved in this paper prolongs the network lifetime effectively.
    • 基金项目: 国家自然科学基金(批准号: 61403336)和燕山大学青年教师自主研究计划课题A类(编号: 13LGA008)资助的课题.
    • Funds: Project supported by the National Natural Science Foundation of China (Grant No. 61403336) and the Independent Research Project Topics A Category for Young Teacher of Yanshan University of China (Grant No. 13LGA008).
    [1]

    Qian Z H, Wang Y J 2013 J. Electron. Inform. Technol. 35 215 (in Chinese) [钱志鸿, 王义君 2013 电子与信息学报 35 215]

    [2]

    Tong X J, Zuo K, Wang Z 2012 Acta Phys. Sin. 61 030502 (in Chinese) [佟晓筠, 左科, 王翥 2012 物理学报 61 030502]

    [3]

    Zhou J P, Liu L W, Deng Y H, Huang S Q 2014 Wireless Personal Commun. 75 273

    [4]

    Karaoglu B, Heinzelman W 2014 IEEE Trans. Mobile Comput. 15 951

    [5]

    Amini R M, Dziong Z 2014 IEEE Trans. Network and Service Management 11 188

    [6]

    Zhou G, Huang C D, Yan T, He T, Stankovic J A, Abdelzaher T F 2006 Proceedings of the 25th IEEE International Conference on Computer Communications Barcelona, Spain, April 23-29, 2006 p1

    [7]

    Wu Y F, Stankovic J A, He T, Lin S 2008 Proceedings of the 27th IEEE Communications Society Conference on Computer Communications Phoenix, AZ, United States, April 13-18, 2008 p1867

    [8]

    Chen J M, Yu Q, Cheng P, Sun Y X, Fan Y F, Shen X M 2011 IEEE Trans. Automat. Control 56 2332

    [9]

    Wang H, Roman H E, Yuan L Y, Huang Y F, Wang R L 2014 Computer Networks 75 212

    [10]

    Chen B, Gong Q Q, Hou S, Li X D, Hao X C, Liu B 2014 J. Computat. Inform. Syst. 10 4385

    [11]

    Liu C, Rong B, Cui S 2015 IEEE Trans. Wireless Commun. 14 138

    [12]

    Marina M K, Das S R, Subramanian A P 2010 Comput. Networks 54 241

    [13]

    Hao X C, Gong Q Q, Hou S, Liu B 2014 Wireless Personal Commun. 78 1047

    [14]

    Wu C, Jiang H, You X J 2014 Acta Phys. Sin. 63 088801 (in Chinese) [伍春, 江虹, 尤晓健 2014 物理学报 63 088801]

    [15]

    Hao X C, Zhang Y X, Jia N, Liu B 2013 Wireless Personal Commun. 73 1169

    [16]

    Liu H R, Yin W X, Han T, Dong M R 2014 Acta Phys.Sin. 63 040509 (in Chinese) [刘浩然, 尹文晓, 韩涛, 董明如2014 物理学报63 040509]

    [17]

    Liu Y H, Ren A, Sun D Y, Wang A M 2013 Comput. Electr. Engineer. 39 1767

    [18]

    Beaude O, Lasaulce S, Hennebel M 2012 Proceedings of the 6th International Conference on Network Games, Control and Optimization Avignon, France, November 28-30, 2012 p96

    [19]

    Fanelli A, Moscardelli L, Skopalik A 2012 Proceedings of the 37th International Symposium on Mathematical Foundations of Computer Science Bratislava, Slovakia, August 27-31, 2012 p360

  • [1]

    Qian Z H, Wang Y J 2013 J. Electron. Inform. Technol. 35 215 (in Chinese) [钱志鸿, 王义君 2013 电子与信息学报 35 215]

    [2]

    Tong X J, Zuo K, Wang Z 2012 Acta Phys. Sin. 61 030502 (in Chinese) [佟晓筠, 左科, 王翥 2012 物理学报 61 030502]

    [3]

    Zhou J P, Liu L W, Deng Y H, Huang S Q 2014 Wireless Personal Commun. 75 273

    [4]

    Karaoglu B, Heinzelman W 2014 IEEE Trans. Mobile Comput. 15 951

    [5]

    Amini R M, Dziong Z 2014 IEEE Trans. Network and Service Management 11 188

    [6]

    Zhou G, Huang C D, Yan T, He T, Stankovic J A, Abdelzaher T F 2006 Proceedings of the 25th IEEE International Conference on Computer Communications Barcelona, Spain, April 23-29, 2006 p1

    [7]

    Wu Y F, Stankovic J A, He T, Lin S 2008 Proceedings of the 27th IEEE Communications Society Conference on Computer Communications Phoenix, AZ, United States, April 13-18, 2008 p1867

    [8]

    Chen J M, Yu Q, Cheng P, Sun Y X, Fan Y F, Shen X M 2011 IEEE Trans. Automat. Control 56 2332

    [9]

    Wang H, Roman H E, Yuan L Y, Huang Y F, Wang R L 2014 Computer Networks 75 212

    [10]

    Chen B, Gong Q Q, Hou S, Li X D, Hao X C, Liu B 2014 J. Computat. Inform. Syst. 10 4385

    [11]

    Liu C, Rong B, Cui S 2015 IEEE Trans. Wireless Commun. 14 138

    [12]

    Marina M K, Das S R, Subramanian A P 2010 Comput. Networks 54 241

    [13]

    Hao X C, Gong Q Q, Hou S, Liu B 2014 Wireless Personal Commun. 78 1047

    [14]

    Wu C, Jiang H, You X J 2014 Acta Phys. Sin. 63 088801 (in Chinese) [伍春, 江虹, 尤晓健 2014 物理学报 63 088801]

    [15]

    Hao X C, Zhang Y X, Jia N, Liu B 2013 Wireless Personal Commun. 73 1169

    [16]

    Liu H R, Yin W X, Han T, Dong M R 2014 Acta Phys.Sin. 63 040509 (in Chinese) [刘浩然, 尹文晓, 韩涛, 董明如2014 物理学报63 040509]

    [17]

    Liu Y H, Ren A, Sun D Y, Wang A M 2013 Comput. Electr. Engineer. 39 1767

    [18]

    Beaude O, Lasaulce S, Hennebel M 2012 Proceedings of the 6th International Conference on Network Games, Control and Optimization Avignon, France, November 28-30, 2012 p96

    [19]

    Fanelli A, Moscardelli L, Skopalik A 2012 Proceedings of the 37th International Symposium on Mathematical Foundations of Computer Science Bratislava, Slovakia, August 27-31, 2012 p360

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出版历程
  • 收稿日期:  2015-01-13
  • 修回日期:  2015-03-03
  • 刊出日期:  2015-07-05

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