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Scheduling Policies for Minimizing Job Migration and Server Running Costs for Cloud Computing Platforms

Haritha, K and Singh, C (2019) Scheduling Policies for Minimizing Job Migration and Server Running Costs for Cloud Computing Platforms. In: 57th Annual Allerton Conference on Communication, Control, and Computing, Allerton 2019, 24-27 September 2019, Monticello, IL, USA, USA, pp. 855-862.

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Official URL: http://dx.doi.org/10.1109/ALLERTON.2019.8919909


We propose job scheduling algorithms to minimize job migration and server running costs in cloud computing platforms offering Infrastructure as a Service. We first consider algorithms that assume knowledge of job-size on arrival of jobs. We characterize the optimal cost subject to system stability. We develop a drift-plus-penalty framework based algorithm that can achieve optimal cost arbitrarily closely. Specifically this algorithm yields a trade-off between delay and costs. We then relax the job-size knowledge assumption and give an algorithm that uses readily offered service to the jobs. We show that this algorithm gives order-wise identical cost as the job size based algorithm. We illustrate the performance of the proposed algorithms and compare these to the existing algorithms via simulation.

Item Type: Conference Paper
Additional Information: Copyright of this article belongs to IEEE
Keywords: Costs; Economic and social effects; Infrastructure as a service (IaaS); System stability, Cloud computing platforms; Job migration; Job scheduling algorithms; Job size; Optimal costs; Running cost; Scheduling policies; Trade off, Scheduling algorithms
Department/Centre: Division of Electrical Sciences > Electronic Systems Engineering (Formerly Centre for Electronic Design & Technology)
Depositing User: Id for Latest eprints
Date Deposited: 10 Feb 2020 11:29
Last Modified: 10 Feb 2020 11:29
URI: http://eprints.iisc.ac.in/id/eprint/64453

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