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论文:2012,Vol:30,Issue(5):629-635 |
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引用本文： |
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张亚明, 史浩山, 刘燕, 姜飞. WSNs中基于蚁群模拟退火算法的移动Agent访问路径规划[J]. 西北工业大学 |
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Zhang Yaming, Shi Haoshan, Liu Yan, Jiang Fei. A Better Itinerary Analysis for Mobile Agent(MA) through Using ACA-SAA Algorithm in Wireless Sensor Networks[J]. Northwestern polytechnical university |
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| WSNs中基于蚁群模拟退火算法的移动Agent访问路径规划 |
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| 张亚明1, 史浩山1, 刘燕2, 姜飞3 |
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1. 西北工业大学 电子信息学院, 陕西 西安 710072;
2. 空军工程大学 电讯工程学院, 陕西 西安 710077;
3. 解放军西安通信学院 通信指挥系, 陕西 西安 710106 |
| 摘要: |
| 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A-gent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,ACA-SAA表现出比SAA和ACA算法更好的性能。 |
| 关键词:
无线传感器网络
路由算法
移动Agent
蚁群算法
模拟退火算法
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| A Better Itinerary Analysis for Mobile Agent(MA) through Using ACA-SAA Algorithm in Wireless Sensor Networks |
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| Zhang Yaming1, Shi Haoshan1, Liu Yan2, Jiang Fei3 |
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1. Department of Electronics Engineering, Northwestern Polytechnic University, Xi'an 710072, China;
2. The Information and Navigation Institute, Air Force Engineering University, Xi'an 710077, China;
3. Department of Communication & Command, Xi'an Communication College of the PLA, Xi'an 710106, China |
| Abstract: |
| 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(ACA) with simulated annealing al-gorithm(SAA) in multi-hop WSNs is proposed.Sections 1 and 2 of the full paper explain our itinerary analysismentioned in the title; we believe that our analysis is novel and better.Section 2 is entitled"ACA-SAA Based Itin-erary Analysis for MA".Section 2.1 is entitled"Itinerary Analysis Model for MA".Section 2.2 is entitled"For-mal Analysis".Section 2.3 is entitled"Sub-Itinerary-Analysis for MA".Section 2.4 is entitled"ACA-SAA BasedItinerary Analysis for MA" ; it contains a detailed 7-step procedure for implementing our itinerary analysis.The coreof our itinerary analysis can be summed up in the following sentence: the model makes the local network nodes're-lationships table (LNNRT) available at the sink node and divides the whole MA path into three sub paths in orderto use the ACA-SAA to process the evolutionary computation to obtain the optimal itinerary.With the expansion ofthe network scale, simulation results in section 3 and their analysis show preliminarily that the model and ACA-SAAhave indeed better performance than ACA and SAA algorithms. |
| Key words:
algorithms
computer simulation
mathematical models
mobile agents
optimization
routing algo-rithms
simulated annealing
wireless sensor networks;ant colony algorithm(ACA)
simulated an-nealing algorithm(SAA)
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| 收稿日期: 2011-10-28
修回日期:
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| DOI: |
| 通讯作者:
Email： |
| 作者简介: 张亚明(1980-)，西北工业大学博士研究生，主要从事无线传感器网络关键技术研究。
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| 作者相关文章 |
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| 张亚明 在本刊中的所有文章 |
| 史浩山 在本刊中的所有文章 |
| 刘燕 在本刊中的所有文章 |
| 姜飞 在本刊中的所有文章 |
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相关文献: |
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1．李虎雄, 张克旺.基于蚁群优化的无线传感器网络路由优化算法[J]. 西北工业大学, 2012,30(3): 356-360 |
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