基于群体智能和遗传算法的WSNs能耗优化关键技术研究

Research on Key Technologies of WSNs Energy Consumption Optimization based on Swarm Intelligence and Genetic Algorithm

节点能耗是决定无线传感器网络(WSNs)生存期的重要参数,设计良好的网络通信协议可以很大程度上减少和平衡能量消耗。网络协议设计簇头和簇间路由的计算过程是多项式时间无法解答的NP问题,该文讨论了5种自然元启发算法,既4种群体智能算法和遗传算法应用于WSNs能耗优化的关键技术,给出了不同网络能量结构模型的簇间单跳和多跳场景的设计建议,旨在为搭建大规模WSNs网络提供参考和借鉴。

Node energy consumption is an important parameter to determine the lifetime of wireless sensor networks(WSNs).A good network communication protocol can greatly reduce and balance energy consumption.The calculation process of cluster head and inter cluster routing in network protocol design is a NP problem that cannot be solved by polynomial time.This paper discusses five kinds of natural element heuristic algorithms,namely four kinds of swarm intelligence algorithm and genetic algorithm,which are the key technologies of energy consumption optimization of WSNs,and gives the design suggestions of single hop and multi hop sce⁃narios between clusters with different network energy structure model.The purpose is to provide reference for building large-scale WSNs network.