基于量子遗传算法的WSNs能量均衡路由优化

Optimization of Energy Balancing Routing Based on Quantum Genetic Algorithm in WSNs

针对无线传感器网络(WSNs)中传感器节点能量有限,以及单一的传输路径所带来的能量消耗不均衡的问题,引入量子遗传算法对其进行优化。充分利用量子遗传算法高效搜索和全局优化的能力,在综合考虑网络耗能和路径延迟的基础上全局优化路由;并对算法的一些环节如量子比特编码、适应度函数的设计以及量子变异进行了详细的分析与设计。仿真表明:与传统遗传算法相比,量子遗传算法在降低网络能耗,延长网络生命期方面有着优越性.

In order to solve the problem that sensor node energy is limited and energy-consuming of sensor nodes in wireless sensor network is unbalanced, a quantum genetic algorithm is proposed. On the basis of considering the network energy consumption and path delay, the algorithm makes full use of efficient searching and global optimization ability of quantum genetic algorithm to optimize routing. Moreover, quantum genetic algorithm is analyzed in detail, including the quantum encoding, fitness function design and quantum variations, The simulation result shows that quantum genetic algorithm is better than traditional genetic algorithm in inducing energy consumption and prolonging network life cycle.