【摘要】 在诸如森林火灾监测等对时间敏感的无线传感器网络(WSN)应用系统中,所允许的最大消息传递延迟必须限制在可接受的范围内.通过使用多个sink节点不但能降低消息传递延迟,而且能有效降低通信中的能量消耗.首先为WSN中的多sink节点放置问题建立了优化模型,进而设计一个两阶段的混合智能优化算法:第1阶段使用蚂蚁算法解决给定多sink节点部署方案下的普通节点与sink节点间的关联问题;第2阶段使用遗传算法解决部署方案的寻优.最后,通过与随机优化算法的仿真对比,表明本文方法具有一定的可行性.更多还原

【Abstract】 In those time-sensitive wireless sensor network(WSN) applications such as forest fire monitoring,etc.,the maximal delay on message transportation must be restricted within an acceptable range.By using multiple sink nodes,the distance between sensors and sinks can be effectively reduced and this leads to the decrease of the delay as well as the energy consuming.This paper at first builds an optimization model for WSN multiple sink deployment problem,and then designs a hybrid intelligent optimization algorithm that is divided into two stages.The first stage employs an ant algorithm to solve the association problem for a given deployment strategy,i.e.,determining the associated sink for each sensor;The second stage uses a genetic algorithm to solve the optimization problem on deployment strategy,i.e.,determining where the sink nodes are deployed.Finally,the simulation and the comparisons with the randomized optimization algorithm manifest that our method is practical.更多还原