Decentralized Self-optimization in Shared Resource Pools

E Loureiro, Patrick Nixon, S Dobson

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

Resource pools are collections of computational resources which can be shared by different applications. The goal with that is to accommodate the workload of each application, by splitting the total amount of resources in the pool among them. In this sense, utility functions have been pointed as the main tool for enabling self-optimizing behaviour in such pools. The goal with that is to allow resources from the pool to be split among applications, in a way that the best outcome is obtained. Whereas different solutions in this context exist, it has been found that none of them tackles the problem we deal with in a total decentralized way. In this paper, we then present a decentralized and self-optimizing approach for resource management in shared resource pools.
LanguageEnglish
Title of host publicationStudies in Computational Intelligence: Intelligent Networking, Collaborative Systems and Applications
EditorsS Caballé, F Xhafa, A Abraham
Place of PublicationBerlin
Pages149-170
Volume329
DOIs
Publication statusPublished - 2011

Keywords

  • Computational resources
  • decentralized algorithms
  • decentralized optimization
  • resource containers
  • resource management
  • resource pools
  • self-optimizing
  • servers
  • utility maximization

Cite this

Loureiro, E., Nixon, P., & Dobson, S. (2011). Decentralized Self-optimization in Shared Resource Pools. In S. Caballé, F. Xhafa, & A. Abraham (Eds.), Studies in Computational Intelligence: Intelligent Networking, Collaborative Systems and Applications (Vol. 329, pp. 149-170). Berlin. https://doi.org/10.1007/978-3-642-16793-5_7
Loureiro, E ; Nixon, Patrick ; Dobson, S. / Decentralized Self-optimization in Shared Resource Pools. Studies in Computational Intelligence: Intelligent Networking, Collaborative Systems and Applications. editor / S Caballé ; F Xhafa ; A Abraham. Vol. 329 Berlin, 2011. pp. 149-170
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Loureiro, E, Nixon, P & Dobson, S 2011, Decentralized Self-optimization in Shared Resource Pools. in S Caballé, F Xhafa & A Abraham (eds), Studies in Computational Intelligence: Intelligent Networking, Collaborative Systems and Applications. vol. 329, Berlin, pp. 149-170. https://doi.org/10.1007/978-3-642-16793-5_7

Decentralized Self-optimization in Shared Resource Pools. / Loureiro, E; Nixon, Patrick; Dobson, S.

Studies in Computational Intelligence: Intelligent Networking, Collaborative Systems and Applications. ed. / S Caballé; F Xhafa; A Abraham. Vol. 329 Berlin, 2011. p. 149-170.

Research output: Chapter in Book/Report/Conference proceedingChapter

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AB - Resource pools are collections of computational resources which can be shared by different applications. The goal with that is to accommodate the workload of each application, by splitting the total amount of resources in the pool among them. In this sense, utility functions have been pointed as the main tool for enabling self-optimizing behaviour in such pools. The goal with that is to allow resources from the pool to be split among applications, in a way that the best outcome is obtained. Whereas different solutions in this context exist, it has been found that none of them tackles the problem we deal with in a total decentralized way. In this paper, we then present a decentralized and self-optimizing approach for resource management in shared resource pools.

KW - Computational resources

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KW - decentralized optimization

KW - resource containers

KW - resource management

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KW - utility maximization

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Loureiro E, Nixon P, Dobson S. Decentralized Self-optimization in Shared Resource Pools. In Caballé S, Xhafa F, Abraham A, editors, Studies in Computational Intelligence: Intelligent Networking, Collaborative Systems and Applications. Vol. 329. Berlin. 2011. p. 149-170 https://doi.org/10.1007/978-3-642-16793-5_7