基于量子遗传算法的无线传感器网络路由研究

Research on wireless sensor networks routing based on quantum genetic algorithm

对于无线传感器网络(WSNs)中的两大关键性问题路由搜寻和能量优化,引入量子遗传算法进行路径的搜寻,并改进算法编解码思路,降低由于网络规模扩大而导致编码长度急速增加,即减少算法的计算复杂度,从而解决传统编码方式下的量子遗传算法难以适用于大规模的WSNs的缺点。通过实验表明:该方法能够得到更加优越和稳定的路径搜索结果,与粒子群优化算法进行1000次重复路径搜寻试验比较,其平均最优解提高了18.9%,稳定性提升了38.9%。

There are two key problems in wireless sensor networks（WSNs） which are routing search and energy optimization. The improved quantum genetic algorithm （QGA） is used to search optimal route and proposed an energy-saving strategy to improve energy consumption. In traditional encoding, while network scale spread, the algorithm encoding length increased quickly. Meanwhile, the algorithm＇ s computational complexity will be much higher. So the encoding is improved to solve these problems, and made the routing algorithm available for large- scale WSNs. Simulation shows that the improved QGA can get more superior and stable routing path. Comparing to particle swarm optimization,this method increased by 18.9 % in average optimal solution and improved by 38.9 % in stability after 1000 repeated simulation.