DocumentCode :
1642293
Title :
A Subproblem-dependent Heuristic in MOEA/D for the Deployment and Power Assignment Problem in Wireless Sensor Networks
Author :
Konstantinidis, Andreas ; Zhang, Qingfu ; Yang, Kun
Author_Institution :
Sch. of Comput. Sci. & Electron. Eng., Univ. of Essex, Colchester
fYear :
2009
Firstpage :
2740
Lastpage :
2747
Abstract :
In this paper, we propose a Subproblem-dependent Heuristic (SH) for MOEA/D to deal with the Deployment and Power Assignment Problem (DPAP) in Wireless Sensor Networks (WSNs). The goal of the DPAP is to assign locations and transmit power levels to sensor nodes for maximizing the network coverage and lifetime objectives. In our method, the DPAP is decomposed into a number of scalar subproblems. The subproblems are optimized in parallel, by using neighborhood information and problem-specific knowledge. The proposed SH probabilistically alternates between two DPAP-specific strategies based on the subproblems objective preferences. Simulation results have shown that MOEA/D performs better than NSGA-II in several WSN instances.
Keywords :
genetic algorithms; wireless sensor networks; lifetime objectives; neighborhood information; network coverage; power assignment problem; problem-specific knowledge; subproblem-dependent heuristic; wireless sensor networks; Computer science; Constraint optimization; Evolutionary computation; Genetics; Monitoring; Network topology; Power engineering and energy; Sensor systems; Sorting; Wireless sensor networks;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Evolutionary Computation, 2009. CEC '09. IEEE Congress on
Conference_Location :
Trondheim
Print_ISBN :
978-1-4244-2958-5
Electronic_ISBN :
978-1-4244-2959-2
Type :
conf
DOI :
10.1109/CEC.2009.4983286
Filename :
4983286
Link To Document :
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