Balance Particle Swarm Optimization and gravitational search algorithm for energy efficient in heterogeneous wireless sensor networks

T. Huynh, Anh-Vu Dinh-Duc, C. Tran, T. Le
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引用次数: 6

Abstract

In this paper, we propose a Balanced PSOGSA algorithm by combining the ability for social thinking in Particle Swarm Optimization with the local search capability of Gravitational Search Algorithm for reducing the probability of trapping in local optimum and prolonging time period before the death of the first node in wireless sensor network. Besides, we also improve the objective function to shorten the convergence time of the algorithm. The simulation results show that our proposed protocol has lower energy consumption and longer lifetime compared to other protocols.
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基于平衡粒子群优化和引力搜索算法的异构无线传感器网络节能研究
本文将粒子群优化中的社会思维能力与引力搜索算法的局部搜索能力相结合,提出了一种平衡的PSOGSA算法,以减少无线传感器网络中陷入局部最优的概率,延长首个节点死亡前的时间。此外,我们还对目标函数进行了改进,缩短了算法的收敛时间。仿真结果表明,与其他协议相比,我们提出的协议具有更低的能耗和更长的生存期。
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