Coverage control algorithm for wireless sensor networks based on non-cooperative game

Haoran LIU; Heyao ZHAO; Yujing DENG; Xingqi WANG; Rongrong YIN

doi:10.11959/j.issn.1000-436x.2019006

您当前的位置：

首页 >

文章列表页 >

Coverage control algorithm for wireless sensor networks based on non-cooperative game

Papers | 更新时间：2024-06-05

- Coverage control algorithm for wireless sensor networks based on non-cooperative game
- Journal on Communications Vol. 40, Issue 1, Pages: 71-78(2019)
- 作者机构：
  
  1. 燕山大学信息科学与工程学院，河北秦皇岛 066004
  2. 河北省特种光纤与光纤传感重点实验室，河北秦皇岛 066004
- 作者简介：
- 基金信息：
  
  The Natural Science Foundation of Hebei Province(F2015203091);The Science and Technology Research Project of Hebei Province(QN2018029)
- DOI：10.11959/j.issn.1000-436x.2019006
  CLC： TP393; TP212
- Online First：2019-01，
  
  Published：25 January 2019
- 稿件说明：
移动端阅览
Haoran LIU, Heyao ZHAO, Yujing DENG, et al. Coverage control algorithm for wireless sensor networks based on non-cooperative game[J]. Journal on Communications, 2019, 40(1): 71-78.
DOI：

Haoran LIU, Heyao ZHAO, Yujing DENG, et al. Coverage control algorithm for wireless sensor networks based on non-cooperative game[J]. Journal on Communications, 2019, 40(1): 71-78. DOI： 10.11959/j.issn.1000-436x.2019006.

摘要

针对节点覆盖冗余造成能量效率低的问题，基于非合作博弈理论，考虑节点覆盖率和剩余能量这2个关键因素构建收益函数，将节点生命周期和网络路径增益等性能参数融入收益函数中，使每个节点选择合适的工作策略来构建网络拓扑，提出一种基于非合作博弈理论的无线传感器网络覆盖控制算法。理论证明节点覆盖率和剩余能量之间存在纳什均衡，且收益函数收敛于帕累托最优。仿真结果表明，该算法能够提供合理的网络节点覆盖率并保证能量效率。

Abstract

For the redundancy coverage of nodes leads to the phenomenon of low energy efficiency

Non-cooperative game theory was used to solve it.A revenue function was proposed

which considering the coverage of nodes and the residual energy.The lifetime of the node and network path gain were applied to revenue function.The network topology was built by nodes with the appropriate work strategy.Control algorithm coverage in wireless sensor network was proposed based on Non-cooperative game theory.A Nash equilibrium between the coverage rate and the residual energy was proved

and the return function converged to the Pareto optimal.Experiments show that the algorithm can provide reasonable coverage of network nodes and ensure energy efficiency.

关键词

Keywords

references

NARANJO P G , SHOJAFAR M , MOSTAFAEI H , et al . P-SEP:a prolong stable election routing algorithm for energy-limited heterogeneous fog-supported wireless sensor networks [J ] . Journal of Supercomputing , 2017 , 73 ( 2 ): 733 - 755 .

SHAMSHIRBAND S , PATEL A , ANUAR N B , et al . Cooperative game theoretic approach using fuzzy Q-learning for detecting and preventing intrusions in wireless sensor networks [J ] . Engineering Applications of Artificial Intelligence , 2014 , 32 ( 2 ): 228 - 241 .

闫驰 . 基于交叉变异的WSN节点蒙特卡罗定位算法研究 [D ] . 兰州:兰州交通大学 , 2016 .

YAN C . Monte Carlo localization for WSN based on Crossover and mutation [D ] . Lanzhou:Lanzhou Jiaotong University , 2016 .

AMIN U.Cooperative ＆ cost-effective network selection . a novel approach to support location-dependent ＆ context-aware service migration in VANET [D ] . Glasgow:University of Glasgow , 2015 .

陈继光 . 基于流体动力学模型的无线传感器网络部署技术研究 [D ] . 南京:南京理工大学 , 2015 .

CHEN J G . Fluid dynamics model based deployment technology research for wireless wensor networks [D ] . Nanjing:Nanjing University of Science ＆ Technology , 2015 .

CHEN W , CHEN L , CHEN Z , et al . WITS:A wireless sensor network for intelligent transportation system [C ] // International Multi- Symposiums on Computer and Computational Sciences . IEEE Computer Society , 2006 : 635 - 641 .

张晓玲 , 梁炜 , 于海斌 . 无线传感器网络传输调度方法综述 [J ] . 通信学报 , 2012 , 33 ( 5 ): 143 - 157 .

ZHANG X L , LIANG W , YU H B . Survey of transmission scheduling methods in wireless sensor networks [J ] . Journal on Communications , 2012 , 33 ( 5 ): 143 - 157 .

SIVAKUMAR M , SADAGOPAN C , BASKARAN M . Wireless sensor network to cyber physical systems:addressing mobility challenges for energy efficient data aggregation using dynamic nodes [J ] . Sensor Letters , 2016 , 14 ( 8 ): 852 - 857 .

KERAMATPOUR A , NIKANJAM A , GHAFFARIAN H . Deployment of wireless intrusion detection systems to provide the most possible coverage in wireless sensor networks without infrastructures [J ] . Wireless Personal Communications , 2017 , 96 ( 3 ): 1 - 14 .

YANG C , CHIN K W . On nodes placement in energy harvesting wireless sensor networks for coverage and connectivity [J ] . IEEE Transactions on Industrial Informatics , 2017 , 13 ( 1 ): 27 - 36 .

孙泽宇 , 伍卫国 , 王换招 , 等 . 概率模型下的一种优化覆盖算法 [J ] . 软件学报 , 2016 ( 5 ): 1285 - 1300 .

SUN Z Y , WU W G , WANG H Z , et al . Optimized coverage algorithm in probability model [J ] . Journal of Software , 2016 ( 5 ): 1285 - 1300 .

周霆 , 虞保忠 . 基于感知数据分析的传感器网络覆盖控制 [J ] . 电子测试 , 2017 ( 11 ): 49 - 50 .

ZHOU T , YU B Z . A data analysis based coverage control for wireless sensor networks [J ] . Electronic Test , 2017 ( 11 ): 49 - 50 .

贾杰 , 张桂园 , 陈剑 , 等 . 无线传感器网络中基于潜在博弈的分布式节点定位 [J ] . 电子学报 , 2014 , 42 ( 9 ): 1724 - 1730 .

JIA J , ZHANG G Y , CHEN J , et al . Distributed node localization based on potential game in wireless sensor networks [J ] . ACTA Electronica sinica , 2014 , 42 ( 9 ): 1724 - 1730 .

胡彪 . 智能算法在无线传感器网络覆盖优化中的应用研究 [D ] . 兰州:兰州大学 , 2016 .

HU B . Research of intelligent algorithm used in the wireless sensor network coverage optimization [D ] . Lanzhou:Lanzhou University , 2016 .

DUAN J , GAO D , YANG D , et al . An energy-aware trust derivation scheme with game theoretic approach in wireless sensor networks for IoT applications [J ] . Internet of Things Journal IEEE , 2014 , 1 ( 1 ): 58 - 69 .

曹傧 , 梁裕丞 , 罗雷 , 等 . Ad hoc 云环境中分布式博弈卸载策略 [J ] . 通信学报 , 2017 , 38 ( 11 ): 24 - 34 .

CAO B , LIANG Y C , LUO L . Distributed game theoretic approach for offloading in ad hoc cloud [J ] . Journal on Communications , 2017 , 38 ( 11 ): 24 - 34 .

XU M , YANG Q , KWAK K S . Distributed topology control with lifetime extension based on non-cooperative game for wireless sensor networks [J ] . IEEE Sensors Journal , 2016 , 16 ( 9 ): 3332 - 3342 .

WU X , ZENG X , FANG B , et al . An energy-balance and game-theory-based cluster formation method for wireless sensor networks [J ] . International Journal of Distributed Sensor Networks , 2017 , 13 ( 8 ): 1 - 15 .

BINMORE K . Game theory and the social contract [J ] . Journal Des Économistes Et Des Études Humaines , 1994 , 5 ( 2-3 ): 429 - 436 .

QUANG D , CHEW Y H , SOONG B H . An Interoduction to game theory [M ] . Oxford : Oxford University Press , 2005 .

MAMUN Q . A Coverage-based scheduling algorihm for WSN [J ] . International Journal of Wireless Information Networks , 2014 , 21 ( 1 ): 48 - 57 .

RITZBERGER K . Foundations of non-cooperative game theory [M ] . Oxford : Oxford University Press , 2002 : 601 - 602 .

ZHU H , LUO H , PENG H , et al . Complex networks-based energy-efficient evolution model for wireless sensor networks [J ] . Chaos,Solitons and Fractals , 2009 , 41 ( 4 ): 1828 - 1835 .

Views

1510

下载量

CSCD

Alert me when the article has been cited

提交

Tools

Publicity Resources

State-of-the-art survey of privacy-preserving data aggregation in wireless sensor networks

New minimum exposure path problem and its solving algorithm in wireless sensor networks

Fault diagnosis and restoration strategy based on Voronoi diagram and resolving set

CS-based data collection method for airborne clustering WSN

Adaptive node scheduling algorithm for target tracking in wireless sensor networks

Related Author

Xiaoying ZHANG

Hui PENG

Hong CHEN

Miao YE

ping WANGYu

Cai DAI

li WANGXiao

Xiao-ding WANG

Related Institution

School of Information,Renmin University of China

Key Laboratory Data Engineering and Knowledge Engineering of Ministry of Education,Renmin University of China

The Fifth Electronic Research Institute of MIIT

School of Computer Science and Technology, Xidian U iversity

College of Information Science and Engineering, Guilin University of Technology

AI问答

⁰