基于被动测量的IP网络性能与故障管理技术研究
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摘要
IP网络的性能评估和故障诊断是网络管理的核心部分,也是网络管理领域多年以来的研究热点。为了获取网络性能指标、采集网络故障信息,人们在网络测量方面开展了大量的研究工作,并设计了多种网络测量方法。然而,目前仍然存在部分问题尚未解决。如:在大规模网络中,难以对大量端到端路径的性能进行并行评估;在故障告警事件缺失或虚假告警的情况下,难以保证故障诊断结果的准确性。
本文提出一种基于被动测量的网络性能和故障管理机制,以试图解决网络管理中的两个关键问题:(1)IP网络性能状态的在线评估;(2)IP网络故障事件的实时关联分析。本文通过被动测量手段获取大量端到端路径性能指标采样,并在此基础上通过基于路由模型的推理方法RMBR(Routing Model Based Reasoning)实现网络故障诊断。上述机制涉及大规模并发流跟踪算法、被动模式测量方法、网络故障推理等一系列技术内容。本文的主要成果包括:
(1)提出一种高速网络流跟踪算法。本文基于网络流的本地性特征,提出了可扩展哈希树算法SHT(Scalable Hash Tree)。与现有IPSX算法相比,SHT算法能够有效缩短流的查找时间,提高流跟踪效率。
(2)提出了若干网络性能指标的被动测量方法和QoE(Quality of Experience)指标的客观评价方法。在丢包率、时延、带宽等传统性能指标基础上,定义“半路径”性能指标作为测量对象,提出相应的被动模式测量方法,并通过QoE评价模型对不同性能指标的测量结果进行综合评价。
(3)提出基于性能测量的网络故障诊断方法。本文借鉴了基于模型的故障推理(Model-Based Reasoning, MBR)思想,提出了网络路由抽象模型RM(Routing Model)和相应的网络故障诊断方法RMBR,并结合网络断层扫描理论,对故障诊断过程中的关键算法进行设计,包括RPS(Routing Path Simulation)路由推演算法和LMT(Link Metrics Tomography)链路质量推断算法。
(4)通过原型系统对技术路线进行验证。本文的相关理论和方法均通过原型系统IDCFlow加以实现和验证。通过RPPM、FaultMan、NetView等子系统的设计,实现了本文工作思路中各个技术层次的内容。原型系统在CERNET网络和其他商用网络中获得应用。
As central aspects of IP network management, performance evaluation and fault diagnosis have been hot-spots of network management area for years. To estimate network performance metrics and collect fault events, a lot of research work has been carried out in network measurement area, and many measurement techniques have been developed. However, there are still some issues remain to be resolved. For example, the parallel performance evaluation of end-to-end paths in large-scale network is difficult, and the result of network fault diagnosis is imprecise under the circumstances of alarm loss and spuriousness alarms.
In this thesis, a new network performance and fault management mechanism based on passive measurement is proposed in order to solve two key issues: (1) the online evaluation of network performance status, (2) the real-time correlation and analysis of fault events. With this mechanism, end-to-end performance metrics are obtained through passive measurement, and a model-based reasoning system is developed to diagnose network faults on the basis of performance evaluation. This mechanism contains several technical issues including the tracking of large-scale IP flows, the passive measurement techniques, the reasoning model for fault diagnosis. The above issues are discussed in this thesis which results in following achievements:
(1) Proposing a high speed flow tracking algorithm. Based on the locality of IP traffic, a scalable hash tree (SHT) algorithm is proposed for tracking the IP flows in large-scale network. SHT algorithm shortens the period of IP flow seeking and performs better than IPSX algorithm in efficiency.
(2) Proposing measurement methods for QoS/QoE metrics estimation. Based on three basic QoS metrics, some“half-path”metrics are proposed and the according passive measurement techniques are developed. Also a QoE evaluation model is proposed to combine different performance metrics into a single rating score.
(3) Proposing a fault diagnosis method based on performance measurement. Taking the advantage of current model-based reasoning (MBR) method, a network routing mode (RM) is proposed, and a fault reasoning model called RMBR is designed to locate network faults on the basis of performance evaluation. Two key algorithms of RMBR - the routing path simulation algorithm (RPS) and the link metrics tomography algorithm (LMT) - are also proposed.
(4) Developing a network measurement and diagnosis system. Algorithms and models in this thesis are implemented as a prototyping system called IDCFlow, which is consisted of several sub-systems (RPPM, FaultMan, and NetView). IDCFlow has been deployed in CERNET and some commercial networks.
本文提出一种基于被动测量的网络性能和故障管理机制,以试图解决网络管理中的两个关键问题:(1)IP网络性能状态的在线评估;(2)IP网络故障事件的实时关联分析。本文通过被动测量手段获取大量端到端路径性能指标采样,并在此基础上通过基于路由模型的推理方法RMBR(Routing Model Based Reasoning)实现网络故障诊断。上述机制涉及大规模并发流跟踪算法、被动模式测量方法、网络故障推理等一系列技术内容。本文的主要成果包括:
(1)提出一种高速网络流跟踪算法。本文基于网络流的本地性特征,提出了可扩展哈希树算法SHT(Scalable Hash Tree)。与现有IPSX算法相比,SHT算法能够有效缩短流的查找时间,提高流跟踪效率。
(2)提出了若干网络性能指标的被动测量方法和QoE(Quality of Experience)指标的客观评价方法。在丢包率、时延、带宽等传统性能指标基础上,定义“半路径”性能指标作为测量对象,提出相应的被动模式测量方法,并通过QoE评价模型对不同性能指标的测量结果进行综合评价。
(3)提出基于性能测量的网络故障诊断方法。本文借鉴了基于模型的故障推理(Model-Based Reasoning, MBR)思想,提出了网络路由抽象模型RM(Routing Model)和相应的网络故障诊断方法RMBR,并结合网络断层扫描理论,对故障诊断过程中的关键算法进行设计,包括RPS(Routing Path Simulation)路由推演算法和LMT(Link Metrics Tomography)链路质量推断算法。
(4)通过原型系统对技术路线进行验证。本文的相关理论和方法均通过原型系统IDCFlow加以实现和验证。通过RPPM、FaultMan、NetView等子系统的设计,实现了本文工作思路中各个技术层次的内容。原型系统在CERNET网络和其他商用网络中获得应用。
As central aspects of IP network management, performance evaluation and fault diagnosis have been hot-spots of network management area for years. To estimate network performance metrics and collect fault events, a lot of research work has been carried out in network measurement area, and many measurement techniques have been developed. However, there are still some issues remain to be resolved. For example, the parallel performance evaluation of end-to-end paths in large-scale network is difficult, and the result of network fault diagnosis is imprecise under the circumstances of alarm loss and spuriousness alarms.
In this thesis, a new network performance and fault management mechanism based on passive measurement is proposed in order to solve two key issues: (1) the online evaluation of network performance status, (2) the real-time correlation and analysis of fault events. With this mechanism, end-to-end performance metrics are obtained through passive measurement, and a model-based reasoning system is developed to diagnose network faults on the basis of performance evaluation. This mechanism contains several technical issues including the tracking of large-scale IP flows, the passive measurement techniques, the reasoning model for fault diagnosis. The above issues are discussed in this thesis which results in following achievements:
(1) Proposing a high speed flow tracking algorithm. Based on the locality of IP traffic, a scalable hash tree (SHT) algorithm is proposed for tracking the IP flows in large-scale network. SHT algorithm shortens the period of IP flow seeking and performs better than IPSX algorithm in efficiency.
(2) Proposing measurement methods for QoS/QoE metrics estimation. Based on three basic QoS metrics, some“half-path”metrics are proposed and the according passive measurement techniques are developed. Also a QoE evaluation model is proposed to combine different performance metrics into a single rating score.
(3) Proposing a fault diagnosis method based on performance measurement. Taking the advantage of current model-based reasoning (MBR) method, a network routing mode (RM) is proposed, and a fault reasoning model called RMBR is designed to locate network faults on the basis of performance evaluation. Two key algorithms of RMBR - the routing path simulation algorithm (RPS) and the link metrics tomography algorithm (LMT) - are also proposed.
(4) Developing a network measurement and diagnosis system. Algorithms and models in this thesis are implemented as a prototyping system called IDCFlow, which is consisted of several sub-systems (RPPM, FaultMan, and NetView). IDCFlow has been deployed in CERNET and some commercial networks.
引文
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