基于传感器网络节点配置优化仿真研究

研究无线传感网络节点配置覆盖优化问题。由于无线传感网络存在着热区问题,对网络的覆盖性能造成严重的影响,同时影响网络配置优化。为了有效的提高无线传感网络的覆盖率,提出了一种改进的粒子群算法优化无线网络节点覆盖。针对粒子群算法存在易陷入局部极值和早熟的缺陷,引入遗传算法中的交叉算子和变异算子,优化传感网络节点的混合粒子群算法,在严格确保无线传感器网络连通性的条件下,传感器节点配置数目达到要求的覆盖度,并进行仿真。仿真结果表明混合粒子群算法能快速收敛到更精确的解,使网络节点配置达到覆盖的优化要求。

Research on Sensor Deployment Based on Probabilistic Detection Model

The coverage of the wireless sensor network node configuration optimization was researched.Redundancy exists in wireless sensor networks,which seriously affects the network’s optimal performance.In order to effectively improve the coverage of wireless sensor network,an improved particle swarm algorithm was proposed for the optimization of wireless network node coverage.the crossover and mutation operators of genetic algorithm were introducted to optimize the hybrid particle swarm algorithm,to ensure that under the conditions of wireless sensor networks connectivity,the number of sensor nodes reached the required coverage.Simulation results show that the hybrid particle swarm algorithm can quickly converge to the accurate solution and better reduce the network redundancy to extend the network lifetime.