• KSII Transactions on Internet and Information Systems
    Monthly Online Journal (eISSN: 1976-7277)

Profit-Maximizing Virtual Machine Provisioning Based on Workload Prediction in Computing Cloud


Abstract

Cloud providers now face the problem of estimating the amount of computing resources required to satisfy a future workload. In this paper, a virtual machine provisioning (VMP) mechanism is designed to adapt workload fluctuation. The arrival rate of forthcoming jobs is predicted for acquiring the proper service rate by adopting an exponential smoothing (ES) method. The proper service rate is estimated to guarantee the service level agreement (SLA) constraints by using a diffusion approximation statistical model. The VMP problem is formulated as a facility location problem. Furthermore, it is characterized as the maximization of submodular function subject to the matroid constraints. A greedy-based VMP algorithm is designed to obtain the optimal virtual machine provision pattern. Simulation results illustrate that the proposed mechanism could increase the average profit efficiently without incurring significant quality of service (QoS) violations.


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Cite this article

[IEEE Style]
Qing Li, Qinghai Yang, Qingsu He and Kyung Sup Kwak, "Profit-Maximizing Virtual Machine Provisioning Based on Workload Prediction in Computing Cloud," KSII Transactions on Internet and Information Systems, vol. 9, no. 12, pp. 4950-4966, 2015. DOI: 10.3837/tiis.2015.12.012

[ACM Style]
Li, Q., Yang, Q., He, Q., and Kwak, K. S. 2015. Profit-Maximizing Virtual Machine Provisioning Based on Workload Prediction in Computing Cloud. KSII Transactions on Internet and Information Systems, 9, 12, (2015), 4950-4966. DOI: 10.3837/tiis.2015.12.012