IMPROMPTU: A Reactive and Distributed Resource Consolidation Manager for Clouds

Yağız Onat Yazır, Adel Guitouni, Stephen W. Neville and Roozbeh Farahbod
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Yağız Onat Yazır: Department of Computer Science, University of Victoria, Victoria, British Columbia, Canada
Adel Guitouni: Peter B. Gustavson School of Business, University of Victoria, Victoria, British Columbia, Canada
Stephen W. Neville: Department of Electrical and Computer Engineering, University of Victoria, Victoria, British Columbia, Canada
Roozbeh Farahbod: SAP Research, Karlsruhe, Baden-Wŭrttemberg, Germany5Chris Matthews, Sudhakar Ganti and Yvonne Coady, Department of Computer Science, University of Victoria, Victoria, British Columbia, Canada

International Journal of Information Technology & Decision Making (IJITDM), 2018, vol. 17, issue 05, 1499-1535

Abstract: In this paper, we present IMPROMPTU, a distributed resource consolidation manager for larger-scale commodity computing clouds. The main contribution of this work is two-fold. First, IMPROMPTU fully distributes the responsibility of resource consolidation management among autonomous node agents that have a one-to-one mapping with the physical machines in the cloud. Second, autonomous node agents manage virtual to physical machine resource consolidation using multiple criteria decision analysis (MCDA) through PROMETHEE II method. MCDA has been previously used within the context of computing systems, particularly in fields such as multi-agent systems, data mining, and wireless communications. However, to the best of our knowledge, IMPROMPTU represents the first fully distributed MCDA approach applied to the problem of autonomous resource consolidation management for commodity computing clouds. Moreover, IMPROMPTU improves on our previous studies by introducing key extensions to enhance the granularity of the MCDA model. Simulation results show that the proposed solution provides a strong alternative to prior resource consolidation management approaches for the key industry problem of mitigating SLA violations. This establishes solid groundwork for further applications and extensions of MCDA to this important problem domain.

Keywords: Multiple criteria decision analysis; cloud computing; resource consolidation management (search for similar items in EconPapers)
Date: 2018
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DOI: 10.1142/S0219622018500487

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