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An adaptive service selection method for cross‐cloud service composition
Author(s) -
Yang Jun,
Lin Wenmin,
Dou Wanchun
Publication year - 2013
Publication title -
concurrency and computation: practice and experience
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.309
H-Index - 67
eISSN - 1532-0634
pISSN - 1532-0626
DOI - 10.1002/cpe.3080
Subject(s) - computer science , cloud computing , service (business) , distributed computing , flexibility (engineering) , service composition , selection (genetic algorithm) , set (abstract data type) , service delivery framework , process (computing) , database , web service , world wide web , operating system , artificial intelligence , statistics , economy , mathematics , economics , programming language
SUMMARY Cloud computing aims at providing elastic applications that can be scaled at runtime. In practice, traditional service composition methods are not flexible enough to changes in cross‐cloud environment. In view of this challenge, an adaptive service selection method for cross‐cloud service composition is proposed in this paper, by dynamically selecting proper services with near‐optimal performance for adapting to changes in time. First, concretely speaking, the service selection and execution are modeled with Markov decision process to ensure flexibility. Second, service pair is defined, and the way to build service pairs set is proposed to predict the performance of candidate services. Third, the adaptive service selection algorithm is designed to select proper cloud services for changing cross‐cloud environment. Finally, a case study for cross‐cloud service composition and experiments are presented for validating the feasibility of our proposal. Concurrency and Computation: Practice and Experience, 2013.© 2013 Wiley Periodicals, Inc.