research-article

Strategy-proof mechanism for time-varying batch virtual machine allocation in clouds

Authors:

Weidong LiAuthors Info & Claims

Cluster Computing, Volume 24, Issue 4

Pages 3709 - 3724

https://doi.org/10.1007/s10586-021-03360-x

Published: 01 December 2021 Publication History

Abstract

Time-varying resource allocation allows users to define their own unique resource requirement plans during different time periods. This mode of allocation can increase the flexibility of resource usage and reduce resource usage costs for users. Moreover, combining this approach with an auction mechanism can enable resource providers to obtain greater social welfare and benefits; therefore, such resource allocation has become a hot topic in cloud computing. This paper addresses the problem of time-varying batch virtual machine (VM) allocation and pricing in the cloud. Specifically, (1) we propose a novel integer programming model for the time-varying batch VM allocation problem, and (2) we design two truthful auction mechanisms to solve the allocation and pricing problem in a competitive environment. The optimal mechanism includes a dynamic programming (DP)-based resource allocation algorithm and a Vickrey–Clarke–Groves (VCG)-based payment price algorithm. Meanwhile, we also design a greedy mechanism that includes a dominant-resource-based allocation algorithm and a dichotomy-based payment price algorithm. We prove the economic characteristics, including truthfulness and individual rationality, of the above two mechanisms. Furthermore, we prove the approximation ratio of the allocation algorithm in the greedy mechanism. Compared to state-of-the-art research, our approach is characterized by high social welfare, a high served user ratio and a short execution time.

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Cited By

Zhang JWang ZVasilakos ALi W(2024)A resource competition-based truthful mechanism for IoV edge computing resource allocation with a lowest revenue limitJournal of Cloud Computing: Advances, Systems and Applications10.1186/s13677-023-00572-x13:1Online publication date: 10-Jan-2024
https://dl.acm.org/doi/10.1186/s13677-023-00572-x
Zang WLi SYang X(2023)A dueling DQN-based online resource allocation algorithm for cloud computingProceedings of the 2023 International Conference on Communication Network and Machine Learning10.1145/3640912.3640986(371-376)Online publication date: 27-Oct-2023
https://dl.acm.org/doi/10.1145/3640912.3640986
Peng XZhang J(2022)An online auction mechanism for double time-varying constraints in vehicular edge computingProceedings of the 2022 6th International Conference on Computer Science and Artificial Intelligence10.1145/3577530.3577570(249-257)Online publication date: 9-Dec-2022
https://dl.acm.org/doi/10.1145/3577530.3577570

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Strategy-proof mechanism for time-varying batch virtual machine allocation in clouds

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Published In

cover image Cluster Computing

Cluster Computing Volume 24, Issue 4

Dec 2021

1105 pages

ISSN:1386-7857

Issue’s Table of Contents

© The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2021.

Publisher

Kluwer Academic Publishers

United States

Publication History

Published: 01 December 2021

Accepted: 11 July 2021

Revision received: 16 June 2021

Received: 11 November 2020

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National Natural Science Foundation of China

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Cited By

Zhang JWang ZVasilakos ALi W(2024)A resource competition-based truthful mechanism for IoV edge computing resource allocation with a lowest revenue limitJournal of Cloud Computing: Advances, Systems and Applications10.1186/s13677-023-00572-x13:1Online publication date: 10-Jan-2024
https://dl.acm.org/doi/10.1186/s13677-023-00572-x
Zang WLi SYang X(2023)A dueling DQN-based online resource allocation algorithm for cloud computingProceedings of the 2023 International Conference on Communication Network and Machine Learning10.1145/3640912.3640986(371-376)Online publication date: 27-Oct-2023
https://dl.acm.org/doi/10.1145/3640912.3640986
Peng XZhang J(2022)An online auction mechanism for double time-varying constraints in vehicular edge computingProceedings of the 2022 6th International Conference on Computer Science and Artificial Intelligence10.1145/3577530.3577570(249-257)Online publication date: 9-Dec-2022
https://dl.acm.org/doi/10.1145/3577530.3577570

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