基于改进粒子群优化的井下WMSN覆盖增强算法  

A coverage-enhancing algorithm based on improved particle swarm optimization for WMSN of underground coal mine

作　　者：韩睿松 杨维[1] 

机构地区：[1]北京交通大学电子信息工程学院,北京100044

出　　处：《中国矿业大学学报》2016年第1期170-175,共6页Journal of China University of Mining & Technology

基　　金：国家自然科学基金项目(51474015);国家"十二五"科技支撑计划项目(2013BAK06B03)

摘　　要：针对煤矿井下无线多媒体传感器网络(WMSN)覆盖问题,提出了一种基于改进粒子群优化的覆盖增强算法.结合煤矿巷道场景特点,构建了井下无线多媒体传感器网络多用感知模型.为提高网络覆盖率,采用带压缩因子的粒子群优化算法确定传感器节点的感知方向,同时引入模拟退火操作,克服了粒子群优化后期陷入局部最优造成网络覆盖率收敛于次优值的缺点,显著提高了网络的覆盖增强效果.算法通过寻优速度控制及概率突跳机制,在保证搜索精度的同时提高全局搜索能力,提升网络覆盖率的优化效果.仿真结果表明:基于改进粒子群优化的覆盖增强算法可有效消除感知重叠区和盲区,实现高效的覆盖增强,相比于其他典型井下WMSN覆盖增强算法具有更好的覆盖增强效果.A coverage-enhancing algorithm based on improved particle swarm optimization was proposed for wireless multimedia sensor network（WMSN）of underground coal mine.According to the characteristics of underground mine tunnels scene,a multipurpose sensing model for wireless multimedia sensor network of underground coal mine was introduced.To optimize the coverage rate of networks,particle swarm optimization algorithm with constriction coefficient was adopted in determining the sensing directions of sensor nodes.At the same time,the simulated annealing algorithm was brought in and combined with particle swarm optimization to overcome the deficiency of local optimum which could reduce the optimizing effect of coverage and lead to sub-optimal convergence.The mechanisms of search speed control and probabilistic leap are employed to ensure the search accuracy and get better global search ability,which will enhance the optimizing effect of coverage rate.The simulation results show that,compared with the existing coverage-enhancing algorithms for underground mines,the proposed algorithm enhances the coverage performance of the wireless multimedia sensor network of underground coal mine significantly by eliminating the sensing overlapping regions and coverage holes.

关 键 词：无线多媒体传感器网络 煤矿井下 覆盖增强 粒子群优化 模拟退火 

分 类 号：TP393[自动化与计算机技术—计算机应用技术]