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An efficient fault tolerant cloud market mechanism for profit maximization

Published: 11 May 2021 Publication History

Abstract

In support of effectively discovering the market value of resources and dynamic resource provisioning, auction design has recently been studied in the cloud. However, there are limitations due to the inability to accept time-varying user demands or offline settings. These limitations create a large gap between the real needs of users and the services available from cloud providers. In addition, existing auction mechanisms do not consider service interruption due to server failures caused by software or hardware problems. To address the limitations of existing auction mechanisms and to avoid service interruption, this paper targets a more general scenario of online cloud resource auction design where: 1) users can request multiple types of time-varying resources; and 2) at least one server is available for each accepted bid even when one or more servers fail; and 3) profit is maximized over the system execution span. Specifically, we model the profit maximization problem using an Integral Linear Programming (ILP) optimization framework, which offers an elastic model for time-varying user demands. In addition, we design an online, truthful, and time efficient auction mechanism consisting of a price-based allocation strategy and a pricing function. The online allocation strategy allocates multiple types of resource to each user while satisfying the time-varying demands and ensuring at least one server is available for each user in each allocated time slot. Lastly, the efficacy of online auctions is validated through careful theoretical analysis and trace-driven simulation studies.

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    cover image ACM Conferences
    CF '21: Proceedings of the 18th ACM International Conference on Computing Frontiers
    May 2021
    254 pages
    ISBN:9781450384049
    DOI:10.1145/3457388
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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    New York, NY, United States

    Publication History

    Published: 11 May 2021

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    Author Tags

    1. auction
    2. cloud computing
    3. online algorithm
    4. pricing
    5. resource allocation
    6. truthful mechanisms

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    • Research-article

    Funding Sources

    • China Scholarship Council
    • National Key R\&D Program of China
    • National Science Foundation of China
    • the Key Research and Development Project of Sichuan Province

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    CF '21
    Sponsor:
    CF '21: Computing Frontiers Conference
    May 11 - 13, 2021
    Virtual Event, Italy

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    Overall Acceptance Rate 273 of 785 submissions, 35%

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    CF '25

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