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The multi-criteria degree-constrained minimum spanning tree problem (mcd-MST) is an important issue in wireless sensor networks (WSNs) topology control. However, the multi-criteria MST (mc-MST) is NP-hard problem and mcd-MST is a typical mc-MST. In this paper, we present an improved discrete particle swarm optimization (PSO) approach for mcd-MST which gives a good compromise between many key objectives in WSNs such as energy consumption, reliability, QoS provisioning and so on. The principles of mutation and crossover operator in the genetic algorithm (GA) are incorporated into the proposed PSO algorithm to achieve a better diversity and break away from local optima. The proposed algorithm is compared with an enumeration method. The simulation results show that this algorithm is efficient and finds high quality solutions for mcd-MST.
Machine Learning and Cybernetics, 2009 International Conference on (Volume:3 )
Date of Conference: 12-15 July 2009