基于细菌觅食优化算法的WSNs节点部署策略

为了提高传感器节点的有效覆盖率,提出了一种基于细菌觅食优化(BFO)算法的节点部署策略。以网络覆盖率为目标函数,在细菌觅食算法的趋向操作过程中,引入碰壁策略,对细菌初始位置进行优化,从而提高算法的收敛速度。算法中的每个细菌都代表一只传感器,多个细菌组成的一个菌落代表一种传感器的部署方案。算法以菌落为单位做复制操作和迁徙操作,按照菌落适应度值大小选出较为优越的部署方案。通过仿真实验,分析了参数对算法性能的影响,并与其他方法的优化结果进行比较,结果表明:该算法有效地提高了传感器节点覆盖率。

Node deployment strategy of WSNs based on BFO algorithm

In order to improve effective coverage rate of sensor nodes, a node deployment strategy based on bacterial foraging optimization（BFO） algorithm is proposed. The ratio of network coverage is taken as objective function, the rebound strategy is applied to ehemotaxis-operating process of BFO algorithm to optimize the initial position of bacteria, so as to increase speed of algorithm convergence. Each of the bacteria represents a sensor, and each colony that is constituted by a series of bacteria represents a type of deployment scheme. The algorithm that in unit of the colony did the operation of reproduction and elimination. The relative superior deployment scheme is chosen through comparing the fitness values of colonies. Through simulation experiments, the influence of parameters on the algorithm performance is analyzed, and the optimal results is compared with those of other methods, and experimental results show that this algorithm can effectively improve the ratio of sensor node coverage.