@techreport{TD:100260,
	att_abstract={{As IP networks have become the mainstay of an increasingly diverse set of applications ranging from Internet games and streaming videos, to e-commerce and online banking, and even to mission-critical 911 over VoIP, best effort service is no longer acceptable. This requires a transformation in network management, changing its focus from detecting and replacing individual faulty network elements, such as routers and line cards, to managing the service quality as a whole for end-users. 

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 includes network topological and cross-layer relationships, protocol interactions, and routing and control plane dependencies. G-RCA abstracts the RCA process 
into signature identification for symptom and diagnostic events, temporal and 
spatial event correlation, and reasoning and inference logic. G-RCA provides a simple yet flexible rule specification language that allows operators to quickly customize G-RCA into different RCA tools as new problems need to be investigated and understood. G-RCA is also integrated with the data trending, 
manual data exploration, and statistical correlation mining capabilities that are tailored for SQM. 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 drop in CDN service.}},
	att_authors={zg2325, jy1348, lb7179, dp8327},
	att_categories={C_NSS.9},
	att_copyright={{ACM}},
	att_copyright_notice={{(c) ACM, 2010. This is the author's version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version was published in ACM CoNEXT 2010 {{, 2010-10-30}}{{, http://conferences.sigcomm.org/co-next/2010/}}.}},
	att_donotupload={},
	att_private={false},
	att_projects={Darkstar},
	att_tags={root cause analysis,  service quality management,  network troubleshooting},
	att_techdoc={true},
	att_techdoc_key={TD:100260},
	att_url={http://web1.research.att.com:81/techdocs_downloads/TD:100260_DS1_2010-10-25T20:43:04.720Z.pdf},
	author={Zihui Ge and Jennifer Yates and Lee Breslau and Dan Pei and He Yan and Dan Massey},
	institution={{ACM CONEXT 2010}},
	month={October},
	title={{G-RCA: A Generic Root Cause Analysis Platform for Service Quality Management in Large ISP Networks}},
	year=2010,
}