Range expansion of mobile wireless system by cooperative transmission based on glowworm swarm optimization

Wenbin Zheng, Hongtao Yin, Jiafeng Fu, Ping Fu, Bing Liu, Wenlei Pan
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引用次数: 1

Abstract

We explore range expansion along an fixed direction with a wireless system consists of a fixed number of mobile robots which do cooperative transmission (CT). The emphasis is on optimal the clusters and locations of clusters to maximize the multi-hop range along a line based on the glowworm swarm optimization (GSO). We build the CT model which can't be solved by conventional method, and solve it by using GSO algorithm to get the optimal result. In GSO algorithm, every mobile node was considered as a glowworm, and the intensity of signs was the intensity of luciferin. Firstly, the initial deployment of nodes is set randomly. Then, after calculating the value of the movement probability, the direction of movement is determined as well as the direction of movement under the constraint of outage probability in CT model. Finally, the deployment of cluster nodes is finished by iterations. Simulation results show that our improve GSO (IGSO) algorithm has such characteristics as high precision and time saving by comparing with traditional GSO and ant colony system (ACS) algorithm.
基于萤火虫群优化的移动无线系统协同传输范围扩展
我们探索了一个由固定数量的移动机器人组成的无线系统沿固定方向进行范围扩展,这些移动机器人进行协同传输。重点研究了基于萤火虫群优化算法(GSO)对集群和集群的位置进行优化,使多跳范围沿直线最大化。建立了传统方法无法求解的CT模型,利用GSO算法求解得到最优解。在GSO算法中,将每个移动节点视为一只萤火虫,符号的强度即为荧光素的强度。首先,随机设置节点的初始部署。然后,计算出运动概率值后,确定运动方向,并在CT模型中确定停电概率约束下的运动方向。最后,通过迭代完成集群节点的部署。仿真结果表明,与传统的GSO算法和蚁群系统(ACS)算法相比,改进的IGSO算法具有精度高、节省时间等特点。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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