| 基于环境感知的多路径路由算法 |
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| 引用本文： | 林沛,胡建军.基于环境感知的多路径路由算法[J].计算机应用,2013,33(10):2750-2752. |
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| 作者姓名： | 林沛 胡建军 |
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| 作者单位： | 甘肃联合大学 电子信息工程学院，兰州 730000 |
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| 基金项目： | 甘肃省高等学校研究生导师科研项目，甘肃联合大学科研能力提升计划骨干项目 |
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| 摘 要： | 认知网络能够提高网络端到端的性能，确保服务质量(QoS)要求。而目前普遍使用的路由算法不具备网络认知能力。针对这一问题，提出一种具有认知能力的负载均衡多路径路由算法，该算法结合了Q学习算法和蚁群算法各自的优点，通过蚁群算法完成路径的建立和维护，Q学习算法实现拥塞规避和负载均衡。使用OPNET仿真比较，表明该算法在时延、带宽利用方面均具有较好的性能。
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| 关 键 词： | 多路径路由 认知网络 Q学习算法 蚁群算法 拥塞避免 |
| 收稿时间： | 2013-04-25 |
| 修稿时间： | 2013-06-24 |
Environment-aware multiple-path routing algorithm |
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| LIN Pei
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HU Jianjun.Environment-aware multiple-path routing algorithm[J].journal of Computer Applications,2013,33(10):2750-2752. |
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| Authors: | LIN Pei HU Jianjun |
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| Affiliation: | School of Electronic and Information Engineering, University of Gansu Lianhe, Lanzhou Gansu 730000,China |
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| Abstract: | Cognitive network can improve the end-to-end performance of the network, and ensure QoS(Quality of Service) requirements. The existing routing algorithm does not have cognitive ability. To solve this problem, a multi-path routing algorithm of cognitiveload balancing was proposed, which combined the advantages of Q-learning algorithm and ant algorithm, to establish and maintain the route through ant algorithm, and to achieve congestion avoidance and load balancing by Q-learning algorithm. The simulation contrast with OPNET shows that the algorithm is valid and effective at controlling packet loss ratio, delay and bandwidth utilization. |
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| Keywords: | multiple-path routing cognitive networks Q-learning algorithm ant colony algorithm congestion avoidance |
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