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Journal of Software:2021.32(2):475-495

网络断层扫描:理论与算法
李惠康,高艺,董玮,陈纯
(浙江大学 计算机科学与技术学院, 浙江 杭州 310027)
Network Tomography: Theory and Algorithm
LI Hui-Kang,GAO Yi,DONG Wei,CHEN Chun
(College of Computer Science and Technology, Zhejiang University, Hangzhou 310027, China)
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Received:May 30, 2020    Revised:July 22, 2020
> 中文摘要: 网络测量为网络设计者与管理者提供网络内部细粒度的运行状态信息,是对网络进行高效管理与优化的基础.网络断层扫描是网络测量领域的一个研究热点,是一种端到端的网络测量方法.与传统网络内部测量方法不同,网络断层扫描利用端到端的测量信息计算和推断网络内部性能和状态,从而实现与网络组成和协议无关的网络测量,具有较低的测量开销.对近年来国内外学者在网络断层扫描研究领域取得的成果进行了系统的总结.首先介绍了网络断层扫描的基本模型,并指出了影响网络断层扫描性能的3个重要因素:监测节点部署、测量路径构造和测量数据分析;接着,依次归纳了这3个方面的研究进展和研究成果;随后分析了已有网络断层扫描方法在实际应用中存在的缺陷,并给出了应对这些核心缺陷的理论和关键算法;最后,基于现有研究成果讨论了网络断层扫描的发展趋势和进一步的研究方向.
Abstract:Network measurement provides the network designers and managers with fine-grained information on the operational statuses of the network and is the basis for efficient network management and optimization. Network tomography is a hot topic in the field of network measurement and is an end-to-end approach for network measurement. Unlike the traditional internal approaches for network measurement, network tomography uses the end-to-end measurements to infer the internal network performance and network states, thereby incurring low overhead to achieve the network measurement that is independent of the network composition and the network protocols. This paper systematically summarizes the representative research works about network tomography in the past few years. First, the basic model of network tomography is given and three key factors that impact the performance of network tomography are identified: the monitoring node placement, the measurement path construction, and the measurement data analysis. Then, the related works are reviewed on these three factors separately. In particular, the major limitations of existing network tomography methods in practical applications are explored, and the efficient solutions proposed in recent years are introduced. Lastly, some challenges and future research directions are discussed in the field of network tomography based on existing research works.
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基金项目:国家自然科学基金(61872437,61772465);浙江省自然科学基金(LR19F020001) 国家自然科学基金(61872437,61772465);浙江省自然科学基金(LR19F020001)
Foundation items:National Natural Science Foundation of China (61872437, 61772465); Zhejiang Provincial Natural Science Foundation (LR19F020001)
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李惠康,高艺,董玮,陈纯.网络断层扫描:理论与算法.软件学报,2021,32(2):475-495

LI Hui-Kang,GAO Yi,DONG Wei,CHEN Chun.Network Tomography: Theory and Algorithm.Journal of Software,2021,32(2):475-495