基于改进量子遗传算法的WSNs多路径路由研究

最优路径搜寻和能量优化是无线传感器网络(wireless sensor networks,WSNs)研究的两大关键性问题，基于簇结构的无线传感器网络模型，将改进的量子遗传算法引入WSNs网络层节能路由算法研究中，选取多条较优染色体代替一条最优染色体指导群体的进化；采用动态的量子旋转门调整策略，避免算法收敛于局部最优解；利用球面坐标角度对量子遗传算法编码，降低算法的复杂度；以路由所耗能量为优化目标，构造适应度函数。与基于传统遗传算法（genetic algorithm, GA）、标准量子遗传算法(quantum genetic algorithms, QGA)的多路径路由进行比较，实验表明，该算法比基于GA，QGA算法的多路径路由具有更低的网络能量消耗，更长的网络生存周期。

Multipath routing protocol for wireless sensor networks based on improved quantum genetic algorithm

The best routing search and energy optimization are two key problems in wireless sensor networks (WSNs). Based on the clustering network model, the improved quantum genetic algorithm (Improved-QGA) is used to achieve the energy-efficient routing protocol for WSNs network layer. More excellent chromosomes instead of the most excellent one are selected, which can guide the evolution of the populations. The dynamic quantum gate strategy has been adopted to remedy the defect of poor local search ability. The algorithm encoding uses the spherical coordinate to reduce the complexity and take the energy consumption as the objective function. Compared to the genetic algorithm (GA) and quantum genetic algorithms (QGA) which multipath routing protocol is based on,the Improved-QGA has lower energy consumption and longer network lifetime.