基于增强蚁群算法的传感网移动sink路径规划

Path Planning for Mobile Sink Based on Enhanced Ant Colony Optimization Algorithm in Wireless Sensor Networks

为同时降低移动sink无线传感器网络的能耗与sink移动距离,提出了一种基于增强蚁群算法的传感网络移动sink路径规划算法。为人工蚁群算法引入了遗传算子,避免人工蚁群算法早熟收敛。将数据量不均匀作为网络的约束条件,将网络生命期与sink的移动距离作为问题的2个优化目标,采用增强的人工蚁群算法选择汇集点的帕累托次优集。多组仿真实验的结果表明,该算法有效地降低了网络平均能耗,提高了网络能耗的均衡性。

To reduce the energy consumption and sink mobile distance of mobile sink wireless sensor networks simultaneously, a path planning algorithm for mobile sink based on enhanced ant colony optimization algorithm in wireless sensor networks is proposed. Genetic operators are introduced to ant colony optimization algorithm in order to prevent ant colony optimization premature. The non-uniform of data distribution is considered as the constraint condition, the network lifetime and sink mobile distance are considered as a multi-objective problem, and the enhanced ant colony optimization is adopted to search the Pareto sub-optimal sets of rendezvous points. The simulation results show that the proposed algorithm reduces the network average energy consumption effectively and improves the energy consumption balance.