Resource allocation and scheduling of multiple composite web services in cloud computing using cooperative coevolution genetic algorithm

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.

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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.

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8 citations in Scopus
4 citations in Web of Science®
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ID Code: 45475
Item Type: Journal Article
Refereed: Yes
Additional Information: Paper presented in International Conference on Neural Information Processing (ICONIP 2011), Majesty Plaza, Shanghai, China, 13-17 September 2011
Keywords: Cooperative Co-evolutionary Genetic Algorithm, Cloud Computing, Resource allocation and scheduling
DOI: 10.1007/978-3-642-24958-7_30
Subjects: Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > ARTIFICIAL INTELLIGENCE AND IMAGE PROCESSING (080100) > Neural Evolutionary and Fuzzy Computation (080108)
Divisions: Past > Schools > Computer Science
Past > QUT Faculties & Divisions > Faculty of Science and Technology
Copyright Owner: Copyright 2011 Springer
Deposited On: 28 Aug 2011 22:15
Last Modified: 10 Oct 2016 04:22

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