recent papers about the solutions for MA itinerary problem abstract the wireless sensor networks ( WSNs) as completely connected graphs. Such one-hop networks are not proper for the real applications in WSNs. Hence, a novel itinerary solution model for MA through combining ant colony algorithm (AC A) with simulated annealing algorithm (SAA) in multi-hop WSNs is proposed. Sections 1 and 2 of the full paper explain our itinerary analysis mentioned in the title; we believe that our analysis is novel and better. Section 2 is entitled " ACA-SAA Based Itinerary Analysis for MA". Section 2. 1 is entitled "Itinerary Analysis Model for MA". Section 2. 2 is entitled "Formal Analysis". Section 2. 3 is entitled "Sub-Itinerary-Analysis for MA". Section 2. 4 is entitled "ACA-SAA Based Itinerary Analysis for MA" ; it contains a detailed 7-step procedure for implementing our itinerary analysis. The core of our itinerary analysis can be summed up in the following sentence; the model makes the local network nodes' relationships table (LNNRT) available at the sink node and divides the whole MA path into three sub paths in order to use the ACA-SAA to process the evolutionary computation to obtain the optimal itinerary. With the expansion of the network scale, simulation results in section 3 and their analysis show preliminarily that the model and ACA-SAA have indeed better performance than ACA and SAA algorithms.%关于无线传感器网络( WSNs)中移动Agent (MA)路由规划问题的解决方法,基本都以把它抽象成为一个无向全连通图(Completely Connected Graph)作为分析的前提,但一跳网络在实际的WSNs应用中并不合理.文章提出一种适用于多跳WSNs的基于蚁群模拟退火算法(ACA-SAA)的移动Agent访问路径规划模型.在Sink节点建立包含源节点在内的本地网络节点关系表LNNRT,将MA访问路径分解为定向子路径、数据融合子路径和返回子路径,利用ACA-SAA算法分别对子路径的解进行进化计算以求得最优解路径.仿真结果表明,随着网络规模的扩大,该优化模型优势明显,ACASAA表现出比SAA和ACA算法更好的性能.
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