DocumentCode :
3028984
Title :
Optimize Multiple Mobile Elements Touring in Wireless Sensor Networks
Author :
He, Liang ; Xu, Jingdong ; Yu, Yuntao
Author_Institution :
Dept. of Comput. Sci., Nankai Univ. Tianjin, Tianjin, China
fYear :
2009
fDate :
10-12 Aug. 2009
Firstpage :
317
Lastpage :
323
Abstract :
Integrating mobility into WSNs can significantly reduce the energy consumption of sensor nodes. However, this may lead to unacceptable data collection latency at the same time. In our previous work, we alleviated the problem under the assumption of a mobile base station (BS). In this paper, we discuss how the problem can be solved when the BS itself is not capable of moving, but it can instead employ some mobile elements (MEs). The data collection latency is mainly determined by the longest tour of the MEs in this case. Each ME should be assigned a similar workload to reduce the latency. Furthermore, the total length of the tours should be minimized to decrease the working cost of MEs. We propose three methods to solve the problem with these two-fold objectives. In the first two methods, we cluster the network according to some criteria, and then construct the data collection tour for each ME. We apply a heuristic operator based on the genetic algorithm in the third method, whose fitness function is defined according to the two-fold objectives. These methods are evaluated by comprehensive experiments. The results show that the genetic method can provide us more steady solutions in term of data collection latency. We also compare the mobile BS model and the multiple MEs model, whose results show that the latter can get us better solutions when the number of MEs gets larger.
Keywords :
data acquisition; genetic algorithms; mobile communication; wireless sensor networks; data collection latency; energy consumption; fitness function; genetic algorithm; heuristic operator; mobile BS model; mobile base station; multiple ME model; multiple mobile elements touring; sensor nodes; wireless sensor networks; Application software; Base stations; Delay; Distributed processing; Energy consumption; Genetic algorithms; Helium; Mobile communication; Mobile computing; Wireless sensor networks; clustering; data collection latency; delay tolerant sensor networks; genetic algorithm; mobile elements;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Parallel and Distributed Processing with Applications, 2009 IEEE International Symposium on
Conference_Location :
Chengdu
Print_ISBN :
978-0-7695-3747-4
Type :
conf
DOI :
10.1109/ISPA.2009.16
Filename :
5207917
Link To Document :
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