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Allocation of multi-objective cross-layer wireless sensor network resource based on chaotic parallel genetic algorithm

Zhou Jie Liu Yuan-An Wu Fan Zhang Hong-Guang Zu Yun-Xiao

Allocation of multi-objective cross-layer wireless sensor network resource based on chaotic parallel genetic algorithm

Zhou Jie, Liu Yuan-An, Wu Fan, Zhang Hong-Guang, Zu Yun-Xiao
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Publishing process
  • Received Date:  16 November 2010
  • Accepted Date:  13 December 2010
  • Published Online:  15 September 2011

Allocation of multi-objective cross-layer wireless sensor network resource based on chaotic parallel genetic algorithm

  • 1. School of Electronic Engineering, Beijng University of Posts and Telecommunications, Beijing 100876, China

Abstract: A chaotic parallel genetic algorithm for the allocation of a multi-objective cross-layer wireless sensor network resource is provided, in which chaotic sequence and parallel genetic algorithm are used to dynamically adjust target selection, communication time slots and other parameters for optimizing the global cross-layer resource allocation. Simulations are conducted to compare the chaotic parallel genetic algorithm method with random allocation algorithm, dynamic programming algorithm, T-MAC protocol and the S-MAC protocol separalely. The simulation results show that the chaotic parallel genetic algorithm has a small communication delay and high success rate of target detection, which reduces the power consumption and improves the real-time characteristic of wireless sensor network.

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