| Q学习和蚁群优化混合的无线传感器网络移动代理路由算法 |
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| 引用本文： | 党小超,姚浩浩,郝占军.Q学习和蚁群优化混合的无线传感器网络移动代理路由算法[J].计算机应用,2013,33(9):2440-2443. |
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| 作者姓名： | 党小超 姚浩浩 郝占军 |
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| 作者单位： | 1. 甘肃省物联网工程研究中心, 兰州 730070
2. 西北师范大学 计算机科学与工程学院, 兰州 730070;
3. 甘肃省物联网工程研究中心, 兰州 730070 |
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| 基金项目： | 甘肃省发展和改革委员会项目 |
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| 摘 要： | 针对无线传感器网络移动代理路由问题,提出了Q学习和蚁群优化混合的无线传感器网络移动代理路由算法。该算法综合了Q学习和蚁群优化算法思想,引入了新的路径选择概率模型,并对最优路径进行了有效的维护。仿真实验结果表明:该算法有效地提高移动代理选路效率,满足不同任务对时延的要求,增强了最优路径的可靠性,进一步降低了网络能耗。
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| 关 键 词： | 无线传感器网络 Q学习 蚁群优化 移动代理 路由算法 路径维护 |
| 收稿时间： | 2013-04-01 |
| 修稿时间： | 2013-05-07 |
Mobile Agent routing algorithm for WSN based on Q learning hybrid with ant colony optimization |
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| DANG Xiaochao
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YAO Haohao
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HAO Zhanjun.Mobile Agent routing algorithm for WSN based on Q learning hybrid with ant colony optimization[J].journal of Computer Applications,2013,33(9):2440-2443. |
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| Authors: | DANG Xiaochao YAO Haohao HAO Zhanjun |
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| Affiliation: | 1. College of Computer Science and Engineering, Northwest Normal University, Lanzhou Gansu 730070, China;
2. Gansu Province Internet of Things Engineering Research Center, Lanzhou Gansu 730070, China |
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| Abstract: | In view of mobile Agent routing problem in Wireless Sensor Networks (WSN), a mobile Agent routing algorithm for WSN based on Q learning hybrid with ant colony optimization was proposed. A new path choosing probability model was introduced and the optimal path was efficiently maintained in the algorithm. The simulation results show that the mobile Agent routing efficiency is highly improved and delay requirements in multiple tasks are fulfilled, the reliability of the optimal path is enhanced, and network energy consumption is reduced. |
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| Keywords: | Wireless Sensor Network (WSN) Q learning ant colony optimization mobile Agent routing algorithm path repair |
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