G-RCA: a generic root cause analysis platform for service quality management in large IP networks
Conference on Emerging Network Experiment and Technology(2012)
摘要
An increasingly diverse set of applications, such as Internet games, streaming videos, e-commerce, online banking, and even mission-critical emergency call services, all relies on IP networks. In such an environment, best-effort service is no longer acceptable. This requires a transformation in network management from detecting and replacing individual faulty network elements to managing the end-to-end service quality as a whole. In this paper, we describe the design and development of a Generic Root Cause Analysis platform (G-RCA) for service quality management (SQM) in large IP networks. G-RCA contains a comprehensive service dependency model that incorporates topological and cross-layer relationships, protocol interactions, and control plane dependencies. G-RCA abstracts the root cause analysis process into signature identification for symptom and diagnostic events, temporal and spatial event correlation, and reasoning and inference logic. G-RCA provides a flexible rule specification language that allows operators to quickly customize G-RCA and provide different root cause analysis tools as new problems need to be investigated. G-RCA is also integrated with data trending, manual data exploration, and statistical correlation mining capabilities. G-RCA has proven to be a highly effective SQM platform in several different applications, and we present results regarding BGP flaps, PIM flaps in Multicast VPN service, and end-to-end throughput degradation in content delivery network (CDN) service.
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关键词
Routing protocols,IP networks,Quality management,Routing,Correlation,Libraries
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