Resource allocation and scheduling of multiple composite web services in cloud computing using cooperative coevolution genetic algorithm
Contribuinte(s) |
Lu, Baoliang |
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Data(s) |
13/11/2011
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Resumo |
In cloud computing, resource allocation and scheduling of multiple composite web services is an important and challenging problem. This is especially so in a hybrid cloud where there may be some low-cost resources available from private clouds and some high-cost resources from public clouds. Meeting this challenge involves two classical computational problems: one is assigning resources to each of the tasks in the composite web services; the other is scheduling the allocated resources when each resource may be used by multiple tasks at different points of time. In addition, Quality-of-Service (QoS) issues, such as execution time and running costs, must be considered in the resource allocation and scheduling problem. Here we present a Cooperative Coevolutionary Genetic Algorithm (CCGA) to solve the deadline-constrained resource allocation and scheduling problem for multiple composite web services. Experimental results show that our CCGA is both efficient and scalable. |
Formato |
application/pdf |
Identificador | |
Relação |
http://eprints.qut.edu.au/45475/4/45475a.pdf DOI:10.1007/978-3-642-24958-7_30 Ai, Lifeng, Tang, Maolin, & Fidge, Colin (2011) Resource allocation and scheduling of multiple composite web services in cloud computing using cooperative coevolution genetic algorithm. Lecture Notes in Computer Science, 7063, pp. 258-267. |
Direitos |
Copyright 2011 Springer This is the author-version of the work. Conference proceedings published, by Springer Verlag, will be available via SpringerLink. http://www.springerlink.com |
Fonte |
Computer Science; Faculty of Science and Technology |
Palavras-Chave | #080108 Neural Evolutionary and Fuzzy Computation #Cooperative Co-evolutionary Genetic Algorithm #Cloud Computing #Resource allocation and scheduling |
Tipo |
Journal Article |
Publicador |
Springer |