DocumentCode
2414495
Title
Failure Recovery in Cooperative Data Stream Analysis
Author
Rong, Bin ; Douglis, Fred ; Liu, Zhen ; Xia, Cathy H.
Author_Institution
Sch. of Comput. Sci. & Inf. Technol., RMIT Univ., Melbourne, Vic.
fYear
2007
fDate
10-13 April 2007
Firstpage
77
Lastpage
84
Abstract
We present a failure recovery framework for System S, a large-scale stream data analysis environment. It is intended to support multiple sites, which have their own local administration and goals. However, it is beneficial for these sites to cooperate with each other, especially in the presence of various failures. Our ultimate goal is to support automatic, timely failure recovery through cooperation among sites. We identify the unique challenges in the context of System S and present our initial design work. In particular, we consider a backup selection problem, specifying where to recover failed jobs, which we formulate as an optimization problem. We present an approximation algorithm together with empirical results obtained through simulations. Our numerical evaluations show that the proposed approximation algorithm is very efficient and effective compared to the optimal solutions. It exhibits a promising empirical performance ratio that is close to the theoretical limit of polynomial approximations of such a problem
Keywords
groupware; optimisation; polynomial approximation; system recovery; System S; approximation algorithm; cooperative data stream analysis; failure recovery; large-scale stream data analysis; optimization problem; polynomial approximations; Approximation algorithms; Availability; Computer science; Data analysis; Data mining; Data processing; Failure analysis; Information analysis; Large-scale systems; Polynomials;
fLanguage
English
Publisher
ieee
Conference_Titel
Availability, Reliability and Security, 2007. ARES 2007. The Second International Conference on
Conference_Location
Vienna
Print_ISBN
0-7695-2775-2
Type
conf
DOI
10.1109/ARES.2007.87
Filename
4159790
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