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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.
In order to solve the problem of wireless multimedia sensor network (WMSN) coverage in coal mine, a coverage enhancement algorithm based on improved particle swarm optimization is proposed. Based on the characteristics of coal mine tunnel scene, a multi-sensing model of underground wireless multimedia sensor network is constructed. Particle swarm optimization algorithm with compression factor is used to determine the sensing direction of sensor nodes, and the simulated annealing is introduced to overcome the shortcoming that the network coverage converges to the sub-optimal value in the latter part of particle swarm optimization, Which can improve the global search ability and improve the network coverage optimization effect by optimizing the speed control and the probability of sudden jump mechanism.The simulation results show that the coverage enhancement algorithm based on improved particle swarm optimization can effectively eliminate Sensing overlap area and blind area to achieve efficient coverage enhancement, which has better coverage enhancement effect than other typical WMSN coverage enhancement algorithms.