• DocumentCode
    127583
  • Title

    A Strategy to Optimize Resource Allocation in Auction-Based Cloud Markets

  • Author

    Bonacquisto, Paolo ; Di Modica, Giuseppe ; Petralia, Giuseppe ; Tomarchio, Orazio

  • Author_Institution
    Dept. of Electr., Electron. & Comput. Eng., Univ. of Catania, Catania, Italy
  • fYear
    2014
  • fDate
    June 27 2014-July 2 2014
  • Firstpage
    339
  • Lastpage
    346
  • Abstract
    Current markets of cloud resources are mainly based on a fixed pricing model. In the recent literature several market-based resource allocation models and algorithms have been proposed, showing that dynamic pricing models could result more profitable for both providers and consumers. In this paper we propose a market of resources where the demand and the offer of resources is matched in auction-based sales. Specifically, we looked at this market from the perspective of the provider, who needs a strategy to allocate at best their unused computing capacity. We proposed an adaptive strategy that, suitably customized to the provider´s business objective, help them to maximize the revenue in the context of procurement auctions. Furthermore, the impact of resource overbooking onto the utilization level of cloud data centers has been analyzed by means of extensive simulations.
  • Keywords
    cloud computing; computer centres; pricing; procurement; resource allocation; adaptive strategy; auction-based cloud markets; auction-based sales; cloud data centers; cloud resources; computing capacity; dynamic pricing models; fixed pricing model; market-based resource allocation models; procurement auctions; provider business objective; resource overbooking; resources demand; resources offer; utilization level; Bandwidth; Computational modeling; Computer architecture; Cooling; Procurement; Random access memory; bidding strategy; cloud market; overbooking; procurement auction;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Services Computing (SCC), 2014 IEEE International Conference on
  • Conference_Location
    Anchorage, AK
  • Print_ISBN
    978-1-4799-5065-2
  • Type

    conf

  • DOI
    10.1109/SCC.2014.52
  • Filename
    6930552