Design, modeling, and analysis of online combinatorial double auction for mobile cloud computing markets

Yuchao Zhang, Ke Xu, Xuelin Shi, Haiyang Wang, Jiangchuan Liu, Yong Wang

Research output: Contribution to journalArticlepeer-review

5 Scopus citations

Abstract

With the burgeoning of cloud service companies, cloud computing is becoming an efficient means of providing computing resources. Amazon EC2, Rackspace, Google App, and Microsoft Azure are attracting more and more users over the Internet these years. However, in mobile cloud computing (MCC), traditional cloud pricing models can no longer support the above popular applications, because user behaviors are dynamic and time sensitive. As an MCC application is the combination of communication services (eg, wireless access services) and computation services (eg, cloud services), it lacks new auctions for capturing the feature of MCC markets based on the communication and computation cooperation (3C). In this paper, we design an efficient double-sided combinatorial auction model in the context of 3C-based MCC to mitigate this problem. We first propose the framework of online combinatorial double auctions to model mobile cloud computing market. On this base, we give four principles of design requirements, which can make the scheme more efficient and practical, and then we design a new winner determination algorithm that shows how the auction mechanism decides commodity allocation and transaction prices. At last, we conduct a series of experiments to deep analyze the property of our mechanism. The experiment results indicate that the proposed online auction mechanism obtains comparable allocation efficiency to the social optimal solution.

Original languageEnglish (US)
Article numbere3460
JournalInternational Journal of Communication Systems
Volume31
Issue number7
DOIs
StatePublished - May 10 2018
Externally publishedYes

Keywords

  • combinatorial double auction
  • mobile cloud computing
  • pricing model
  • resource allocation

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