外推人工蜂群算法在WSN部署优化中的应用研究

Extrapolation Artificial Bee Colony Algorithm Research on Deployment Optimization in Wireless Sensor Network

为解决无线传感器网络(WSN)覆盖部署优化的问题,提出了一种基于外推人工蜂群算法的节点部署优化方法。首先,设定网络系统基本假设,并以使网络覆盖率最大化为目标建立网络覆盖优化基本模型,再者,利用外推人工蜂群算法代入模型进行求解,获得覆盖最优的节点部署位置。仿真实验结果表明:外推人工蜂群算法能够很好地解决无线传感网络覆盖优化问题,相比于传统的遗传算法、人工鱼群算法、粒子群算法和人工蜂群算法,表现出更快的寻优速度和更高的覆盖率。

Aiming at the coverage deployment optimization problem in Wireless Sensor Network, a method for nodes deployment optimization based on Extrapolation Artificial Bee Colony （EABC） algorithm was proposed. Firstly, the basic hypothesis of network system was set up, and the network coverage optimization model was established with the objective of maximizing the network coverage rate, and then EABC was used to solve the model,and the optimal nodes deployment for coverage optimization was obtained. Simulation experiments show that EABC algorithm can efficiently solve the coverage deployment optimization problem, comparing with traditional Genetic Algorithm, Artificial Fish Swarm Algorithm, Particle Swarm Optimization Algorithm and Artificial Bee Colony Algorithm, and EABC achieves faster optimization speed and high coverage rate.