Wireless Sensor Nodes Redeployment using a Multiobjective Optimization Evolutionary Algorithm

       IEEE TENCON 2013——This talk proposes to apply a multiobjective optimization evolutionary algorithm in wireless sensor node redeployment process to improve network lifetime and sensing coverage. The multiobjective optimization uses a population of individuals, each of which represents a set of wireless sensor node positions, and evolves them via the genetic operations for seeking optimal sensing coverage and network lifetime. The data transmission success rate and the total moving cost are also added as constraints. Simulation results show that the proposed multiobjective optimization evolutionary algorithm outperforms a well-known existing evolutionary algorithm for multiobjective optimization.