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Title:Cloud Resource Allocation Games
Author(s):Jalaparti, Virajith; Nguyen, Giang D.
Contributor(s):Gupta, Indranil; Caesar, Matthew
Subject(s):Cloud Computing
Resource allocation
Game theory
Abstract:Cloud computing is a newly emerging paradigm in which a client pays as it uses computing resources owned by a cloud provider. Since multiple clients share the cloud's resources, they could potentially interfere with each others' tasks. Current pricing and resource allocation mechanisms are quite preliminary (e.g., fixed pricing in Amazon EC2/S3) and do not take into account the conflict of interests between multiple clients using the cloud simultaneously. This can lead to clients being overpriced, depending upon their allocated resources. Further, these mechanisms do not allow the provider to optimize its resource utilization. In this paper, we take the first step towards modeling the complex client-client and client-provider interactions in a cloud by using game theory. We define a new class of games called Cloud Resource Allocation Games (CRAGs). CRAGs solve the resource allocation problem in clouds using game-theoretic mechanisms, ensuring that clients are charged (near) optimal {\em prices} for their resource usage and that resources of the cloud are used near their optimal capacity. We present the conditions for reaching various stable equilibria in CRAGs and provide algorithms that ensure close to optimal performance. We further provide results of several experiments performed using traces from PlanetLab and the Parallel Workload Archives which show that the new mechanisms result in as much as 15\% to 88\% increase in performance compared to existing resource allocation mechanisms like Round-Robin.
Issue Date:2010-12-02
Genre:Technical Report
Publication Status:published or submitted for publication
Peer Reviewed:not peer reviewed
Date Available in IDEALS:2010-12-02

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