基于GA-PSO算法的ZigBee自组网最佳路由选择

发布时间：2018-05-14 01:16

本文选题：ZigBee自组网 + 物联网　；参考：《计算机工程》2017年07期

【摘要】：为进一步提高ZigBee自组网的网络性能,对ZigBee自组网和路由算法两方面进行研究。利用ZigBee技术构建网络,在路由路径更新时综合考虑网络节点能量均衡和收敛速度,采用改进遗传算法搜索到全局较优解,并利用粒子群优化算法从中快速找到最优解的最佳路由路径。基于NS2的仿真结果表明,与经典AODVjr路由算法和基于遗传算法的路由算法相比,混合遗传粒子群优化算法可延长网络的生命周期,减小网络延时,提高ZigBee网络的整体性能,更适合规模较大的复杂网络。
[Abstract]:In order to further improve the performance of ZigBee ad hoc network, two aspects of ZigBee ad hoc network and routing algorithm are studied. The ZigBee technology is used to construct the network. The energy balance and convergence speed of the network nodes are considered when the routing path is updated, and the improved genetic algorithm is used to search the global optimal solution. Particle swarm optimization (PSO) algorithm is used to quickly find the optimal routing path. Simulation results based on NS2 show that compared with classical AODVjr routing algorithm and genetic algorithm, hybrid genetic particle swarm optimization algorithm can prolong the network life cycle, reduce network delay and improve the overall performance of ZigBee network. More suitable for larger complex networks.
【作者单位】：华中师范大学物理科学与技术学院电信系;国网湖北省电力公司经济技术研究院;
【基金】：国家自然科学基金(61074046) 中央高校探索创新基金(CCNU15A02060) 中国-乌克兰国际合作基金(CU01-11)
【分类号】：TN92;TP18;TP391.44

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