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| 一种IP网络拥塞链路丢包率范围推断算法 |
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陈宇1,2, 周巍1, 段哲民1, 钱叶魁3, 赵鑫3,4
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1.西北工业大学 电子信息学院, 陕西 西安 710072;2.郑州航空工业管理学院, 河南 郑州 450015;3.解放军防空兵学院, 河南 郑州 450052;4.中国电子科技集团公司 第五十四研究所 通信网信息传输与分发技术重点实验室, 河北 石家庄 050081
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| 摘要: |
| 针对大规模IP网络拥塞链路丢包率范围推断算法中存在的不足，提出一种贪婪启发式拥塞链路丢包率范围推断算法.借助多时隙路径探测，避开单时隙探测对时钟同步的强依赖；通过学习各链路拥塞先验概率，借助贝叶斯最大后验定位拥塞链路；提出了聚类拥塞链路相关、性能相近路径集合的策略，通过对聚类路径集合中性能相似系数求解，循环推断拥塞链路丢包率范围.实验验证了算法的准确性及鲁棒性. |
| 关键词: IP网络 拥塞链路推断 丢包率范围 贝叶斯最大后验概率 贪婪启发算法 |
| DOI：10.13328/j.cnki.jos.005148 |
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| 基金项目:国家重点基础研究发展计划（973）（2013CB329104）；国家自然科学基金（61103225）；通信网信息传输与分发技术重点实验室基金 |
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| Congested Link Loss Rate Range Inference Algorithm in IP Network |
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CHEN Yu1,2, ZHOU Wei1, DUAN Zhe-Min1, QIAN Ye-Kui3, ZHAO Xin3,4
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1.Institute of Electronic Information, Northwestern Polytechnical University, Xi’an 710072, China;2.Zhengzhou University of Aeronautics, Zhengzhou 450015, China;3.Air Defence Forces Academy of PLA, Zhengzhou 450052, China;4.Science and Technology on Information Transmission and Dissemination in Communication Networks Laboratory, No.54 Research Institute, China Electronics Technology Group Corporation, Shijiazhuang 050081, China
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| Abstract: |
| Addressing the shortcomings of existing link congestion loss rate range inference algorithms in large scale IP network, a new link congestion loss rate range inference algorithm based on greedy heuristic method is proposed. The strong dependency on the clock synchronization of single slot E2E path measurements is avoided through using multiple slots E2E path measurements. Each congested link can be located through adopting the link congestion Bayesian maximum a-posterior (BMAP) after learning prior probabilities of the link congestion. The set consisting of paths with related congested links and similar performance is constructed. Through solving the performance similarity coefficient dynamically, loss rate range of each congested link can be recurrently inferred. The accuracy and robustness of the algorithm proposed in this paper is verified by experiments. |
| Key words: IP network congested link inference loss rate range Bayesian maximum a-posteriori (BMAP) greed heuristic algorithm |
