QoS-aware resource matching and recommendation for cloud computing systems

  • Shuai Ding
  • , Chengyi Xia
  • , Qiong Cai
  • , Kaile Zhou
  • , Shanlin Yang

Research output: Contribution to journalArticlepeer-review

28 Scopus citations

Abstract

Resource matching and recommendation is an important topic in the field of cloud computing. While a lot of cloud resource discovery and negotiation models have been proposed, resource matching and recommendation issues have often been neglected, such as the utilization of attribute weights and the collaborative application of empirical data, price utility and so on. To cope with this challenge, we focus on designing a novel resource recommendation method which can regulate multi-attribute matching between provider solutions and customer demands in this paper. At first, we describe a resource matching algorithm that considers both functional requirements and QoS attributes. Then, we propose a resource recommendation method for cloud computing system that integrates price utility, multi-attribute matching metric and group customer evaluation. Finally, the extensive simulation results demonstrate that our proposed method is effective in various simulated scenarios. Current results are of high significance to design an efficient resource matching and recommendation with guaranteed QoS requirements under the realistic cloud computing circumstances.

Original languageEnglish
Pages (from-to)941-950
Number of pages10
JournalApplied Mathematics and Computation
Volume247
DOIs
StatePublished - 15 Nov 2014
Externally publishedYes

Keywords

  • Cloud computing
  • Multi-attribute matching
  • Price utility
  • QoS
  • Resource recommendation

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