无线通信网络非等间距节点负载部署研究仿真

Research and Simulation of Non-Equal Distance Node Load Deployment in Wireless Communication Networks

随着无线通信技术的发展,网络节点的部署问题成为无线网络中亟待解决的难题之一。由于网络负载配备不合理,严重影响了无线网络的工作计算效率。针对不等间距节点间存在负载不均衡和工作效率低等问题,提出采用分数阶达尔文粒子群算法,对无线通信网络中非等间距节点进行能量均衡和动态调节,根据网络节点的链路结构和相邻性的特点计算节点间的能量和距离,通过节点接收与传输距离对非等间距节点的能量进行计算,并将无线通信网络的信息流量与数据请求所需能量消耗采取提前估算处理,进而实现对各节点载荷的合理配置。搭建仿真平台,验证了提出的新型非等间距节点负载部署方法能够有效改善负载部署问题,节约更多的时间成本和功耗成本,有利于提高无线通信网络的效率,改善非等间距节点的覆盖率。

With the development of wireless technology,the deployment of wireless communication network nodes has become one of the most important problems in wireless networks.Due to the unreasonable network load,the working efficiency of the wireless network is seriously affected.In order to solve the problem of unbalanced load and low efficiency between nodes with unequal spacing,this paper used the fractional Darwin particle swarm optimization algorithm to perform energy balance and dynamic adjustment on non-equal nodes in wireless communication networks,according to the link structure of network nodes.The characteristics of the adjacency were used to calculate the energy and distance between the nodes.The energy of the non-equal-spacing nodes was calculated by the node receiving and transmitting distance,and the load deployment prediction was performed on the traffic and the number of requests of the wireless network,thereby performing a series of load on the network.The experimental results show that the Darwin particle swarm optimization algorithm can effectively improve the load deployment problem,and save more time cost and power consumption cost,which is beneficial to improve the efficiency of the wireless communication network and improves the coverage of non-equal spacing nodes.