改进蜂群算法在传感器网络覆盖增强中的应用

Application of Coverage Enhancement in Sensor Networks Based on Improved Bee Colony Algorithm

传感器网络的覆盖增强是传感器网络建设中的重要问题。为了最大程度地提升网络覆盖率,需要合理分配网络的空间资源。论文提出了一种应用于传感器网络覆盖增强的改进蜂群算法。首先,结合遗传算法全局优化能力强,以及蜂群算法收敛速度快的特点,构造了一种全局收敛性能更佳的混合优化算法;其次,为改善混合优化算法在迭代后期易于陷入局部最优的缺点,采用了正弦余弦因子以改善算法的全局收敛性能。其测试函数和传感器网络覆盖增强实际算例的仿真结果表明,论文提出的改进的蜂群算法具有更佳的优化性能。

Coverage enhancement in sensor networks is a significant problem need to be considered in sensor network construction. It is necessary to allocate the network space resources reasonably,in order to promote the network coverage as much as possible,an improved bee colony algorithm(IBC)for application of coverage enhancement in sensor networks is proposed. Firstly,a hybrid optimization algorithm with better global convergence performance has been constructed. The robust global optimization capacity of the genetic algorithm is combined with the fast convergence velocity of the bee colony algorithm. Secondly,aiming at improving the weakness easy to fall into local convergence for hybrid optimization algorithm,the global convergence performance of the hybrid optimization algorithm is ameliorated by integrating into sine-cosine operator. The specific simulation results of benchmark functions and coverage enhancement in sensor networks practical example show that the improved algorithm proposed in this paper has better optimization performance.