Optimization of PWSN transmission performance on coal mining face
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摘要: 针对煤矿工作面定位无线传感器网络(PWSN)端到端时间较长、丢包率较大等问题，提出采用保障贪婪调度（GGS）算法来优化网络传输性能。GGS算法结合了粒子群优化(PSO)算法和贪婪算法，使用PSO算法对信道中的报文种群进行有序化处理，实现对种群的保障；使用贪婪算法对网络传输过程中的具体服务请求形成一种多层次、反复迭代的处理机制，以优化报文种群质量；利用PSO变异算法对种群进行检查和更新，以确保得到的是最优解。仿真结果表明，与现有文化基因算法(MA)、差分进化人工蜂群(DE-ABC)算法相比，GGS算法可在控制丢包率的前提下缩短传输时间，提升网络整体性能。Abstract: In view of problems of long end-to-end time and high packet loss rate of positioning wireless sensor network (PWSN) on coal mining face, a guaranteed greedy scheduling (GGS) algorithm was proposed to optimize network transmission performance. The GGS algorithm combines the particle swarm optimization (PSO) algorithm and the greedy algorithm. The PSO algorithm is used to orderly process the message population in the channel to ensure the population. The greedy algorithm is used to form a multi-level, iterative processing mechanism for specific service requests during network transmission, so as to optimize the quality of the message population. The PSO mutation algorithm is used to check and update the population to ensure that the optimal solution is obtained. The simulation results show that compared with the existing MA and DE-ABC algorithms, the GGS algorithm can shorten the transmission time and improve the overall network performance while controlling the packet loss rate.
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期刊类型引用(3)
1. 侯瑞丽. 基于EMMD-RVM的煤矿采矿机械设备异常检测系统. 能源与环保. 2022(05): 149-155 . 
百度学术
2. 李敬兆，叶桐舟，欧阳其春，王翼宁，陆正兴. 基于TCN的散装物料精准装车系统研究. 煤矿机械. 2021(03): 63-65 . 百度学术
3. 吴炬华. 基于雾计算的煤矿安全监测系统研究. 煤炭技术. 2021(12): 193-195 . 百度学术
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