基于分布式计算的地下无线网络任务调度优化算法研究

Dian-xu Ruan, Xiao-guang Zhang, Hui Li, Yin Liu
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引用次数: 3

摘要

为解决无线传感器网络实时诊断和矿井煤矿井下设备健康记录监测中特征提取、模式分类等实时性高、计算复杂的问题,提出了一种基于分布式计算的井下无线监测网络任务调度优化算法,该算法利用遗传算法的快速收敛特性,将具有生存机制的鱼群算法与遗传算法相结合。提高全局搜索能力和收敛速度,借鉴分布式计算模型的进步,将分布式计算引入无线网络任务调度中,利用鱼群遗传算法实现资源负载均衡。仿真结果表明,该算法不仅具有很强的全局搜索能力和收敛性,而且提高了网络的生存期。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The Research of Optimal Algorithm for Task Scheduling Underground Wireless Network Based on Distributed Computing
To solve high real-time and complexity calculation problems such as feature extraction and pattern classification when wireless sensor network real-time diagnosis and equipment health record of the mine coal underground equipments monitoring, this paper purpose a optimal algorithm for task scheduling underground wireless monitoring network based on distributed computing, this method use the fast convergence feature of GA, combine the fish swarm algorithm with survival mechanism and GA, improves the global search capability and convergence rate, referring the advance of distributed computing model, introducing the distributed computing to wireless network task scheduling, with fish swarm genetic algorithm, it can balance resource loads. The simulation results show that this algorithm not only has very strong global search capability and convergence, but also improve the network lifetime.
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