A Subproblem-dependent Heuristic in MOEA/D for the deployment and power assignment problem in wireless sensor networks

Authors:
Andreas Konstantinidis;Qingfu Zhang;Kun Yang
Affiliations:
The School of Computer Science and Electronic Engineering, University of Essex, Colchester, UK;The School of Computer Science and Electronic Engineering, University of Essex, Colchester, UK;The School of Computer Science and Electronic Engineering, University of Essex, Colchester, UK
Venue:
CEC'09 Proceedings of the Eleventh conference on Congress on Evolutionary Computation
Year:
2009

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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.