DocumentCode :
2538330
Title :
Node Distribution Optimization in Mobile Sensor Network Based on Multi-Objective Differential Evolution Algorithm
Author :
Jin, Lizhong ; Jia, Jie ; Sun, Dawei
Author_Institution :
Sch. of Inf. Sci. & Eng., Northeastern Univ., Shenyang, China
fYear :
2010
fDate :
13-15 Dec. 2010
Firstpage :
51
Lastpage :
54
Abstract :
In the research on mobile sensor networks, coverage control is one of the most important challenges. For the sensor network constructed by random distribution, better network coverage can be achieved by topology adjustment utilizing mobility of sensor nodes. This paper investigates how to make use of sensor radius adjustment and the mobility of the sensor nodes to improve the sensor network coverage. A node distribution optimization scheme based on multi-objective differential evolution algorithm is proposed. Simulation results show that the proposed scheme can quickly achieve node distribution optimization of a mobile sensor network, increase the effective coverage rate, reduce network redundant coverage and network energy consumption, extend network lifetime, and achieve global optimization of the deployment of the mobile sensor network.
Keywords :
evolutionary computation; mobile communication; mobility management (mobile radio); wireless sensor networks; coverage control; mobile sensor network; multiobjective differential evolution algorithm; network energy consumption; node distribution optimization scheme; random distribution; sensor node mobility; Energy consumption; Mobile communication; Mobile computing; Network topology; Optimization; Sensors; Wireless sensor networks; mobile sensor network; multi-objective evolution algorithm; network coverage rate; network sensing consumption;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Genetic and Evolutionary Computing (ICGEC), 2010 Fourth International Conference on
Conference_Location :
Shenzhen
Print_ISBN :
978-1-4244-8891-9
Electronic_ISBN :
978-0-7695-4281-2
Type :
conf
DOI :
10.1109/ICGEC.2010.21
Filename :
5715368
Link To Document :
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