Coverage of communication-based sensor nodes deployed location and energy efficient clustering algorithm in WSN  

作　　者：Xiang Gao Yintang Yang Duan Zhou 

机构地区：[1]College of Microelectronics, Xidian University, Xi' an 710071, P. R. China [2]College of Computer Science and Technology, Xidian University, Xi'an 710071, E R. China

出　　处：《Journal of Systems Engineering and Electronics》2010年第4期698-704,共7页系统工程与电子技术（英文版）

基　　金：supported by the Major State Basic Research Program of China(B1420080204);National Science Fund for Distinguished Young Scholars(60725415);the National Natural Science Foundation of China(60606006)

摘　　要：An effective algorithm based on signal coverage of effective communication and local energy-consumption saving strategy is proposed for the application in wireless sensor networks.This algorithm consists of two sub-algorithms.One is the multi-hop partition subspaces clustering algorithm for ensuring local energybalanced consumption ascribed to the deployment from another algorithm of distributed locating deployment based on efficient communication coverage probability（DLD-ECCP）.DLD-ECCP makes use of the characteristics of Markov chain and probabilistic optimization to obtain the optimum topology and number of sensor nodes.Through simulation,the relative data demonstrate the advantages of the proposed approaches on saving hardware resources and energy consumption of networks.An effective algorithm based on signal coverage of effective communication and local energy-consumption saving strategy is proposed for the application in wireless sensor networks.This algorithm consists of two sub-algorithms.One is the multi-hop partition subspaces clustering algorithm for ensuring local energybalanced consumption ascribed to the deployment from another algorithm of distributed locating deployment based on efficient communication coverage probability（DLD-ECCP）.DLD-ECCP makes use of the characteristics of Markov chain and probabilistic optimization to obtain the optimum topology and number of sensor nodes.Through simulation,the relative data demonstrate the advantages of the proposed approaches on saving hardware resources and energy consumption of networks.

关 键 词：wireless sensor network probability distribution function Markov chain received signal strength indicator Gaussian distribution. 

分 类 号：TP212[自动化与计算机技术—检测技术与自动化装置] TP391.41[自动化与计算机技术—控制科学与工程]