摘要
研究无线传感器(WSN)路由优化问题,传统路由过程传感器能量消耗过大,就会造成节点的早死亡。如不能提供很好的节点能量,使网络生存困难。为了减少WSN能量消耗,延长网络生存时间,提出一种利用混合计算智能优化算法。采用遗传算法全局快速收敛优点,并融入蚁群算法的每一次迭代中,加快蚁群算法收敛速度,达到具有很强的全局搜索能力,最后对WSN路由优化问题求解。仿真结果表明,混合智能算法提高了节点能量利用效率,延长了网络生存时间。
The traditional routing algorithms have some defects, such as large consumption of node energy, short survival time of the network. In order to reduce the WSN energy consumption, prolong the survival time of the net- work, the paper proposed a WSN routing optimization algorithm based on a hybrid intelligent computation. The genet- ic algorithm was integrated into the ant colony algorithm in each iteration to accelerate the convergence speed, so it has strong global search ability. Finally, the WSN routing optimization was applied to solve problem. The simulation results show that, the hybrid intelligent computation algorithm improves the utilization efficiency of node energy, and prolongs the survival time of the network.
出处
《计算机仿真》
CSCD
北大核心
2012年第7期188-191,共4页
Computer Simulation
关键词
路由优化
无线传感器网络
蚁群算法
遗传算法
Route optimization
WSN
Ant colony optimization algorithm
Genetic algorithm
