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

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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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Acknowledgements

This work is supported in part by the National Natural Science Foundation of China (Nos. 62062065, 61762091, 61662088, 12071417 and 11663007), the Project of the Natural Science Foundation of Yunnan Province of China (2019FB142 and 2018ZF017), and the Program for Excellent Young Talents, Yunnan University, China.

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Authors and Affiliations

  1. School of Information Science and Engineering, Yunnan University, Kunming, 650504, People’s Republic of China

    Jixian Zhang, Ning Xie, Xutao Yang & Xuejie Zhang

  2. School of Mathematics and Statistics, Yunnan University, Kunming, 650504, People’s Republic of China

    Weidong Li

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  1. Jixian Zhang
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Zhang, J., Xie, N., Yang, X. et al. Strategy-proof mechanism for time-varying batch virtual machine allocation in clouds. Cluster Comput 24, 3709–3724 (2021). https://doi.org/10.1007/s10586-021-03360-x

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