摘要
研究无线传感器网络路径优化问题,针对无线传感器网络(WSN)路径优化问题,在分析了遗传算法和蚁群算法各自优缺点的基础上,通过把蚁群算法作为WSN路径优化的主框架,采用遗传算的选择、交叉和变异算子提高蚁群算法搜索速度,提出一种改进蚁群算法的WSN路径优化方法。仿真结果表明,改进蚁群算法有效地克服了基本蚁群算法的缺陷,提高了WSN路径优化效率和成功率,减少了能理消耗,有效延长了网络生存时间。
This paper proposed a path optimization of wireless sensor network based on an improved ant colony al- gorithm by analysis of the respective advantages and disadvantages of genetic algorithm and ant colony algorithm. The ant colony algorithm was used as WSN path optimization main frame, and genetic algorithm selection, crossover and mutation operator were used to improve ant colony algorithm performance. Simulation experimental results show that the improved ant colony algorithm overcomes the defect of ant colony algorithm effectively, improves WSN routing ef- ficiency and success rate, reduces energy consumption, and prolongs the survival time of the network.
出处
《计算机仿真》
CSCD
北大核心
2012年第8期112-115,共4页
Computer Simulation
关键词
无线传感器网络
蚁群算法
遗传算法
路径寻优
Wireless sensor network (WSN)
Ant colony algorithm(ACA)
Genetic algorithm(GA)
Path optimi- zation