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A STUDY ON CLOUD FEDERATION MODELS USING COOPERATIVE GAME THEORYAuthor: Yash Khandelwal Date: 2019-07-05 Report no: IIIT/TH/2019/74 Advisor:Suresh Purini AbstractThis thesis is mainly divided into two parts, first we formulate the optimal coalition formation in federated clouds as an integer linear programming problem under the cloud service brokerage model proposed by Mashayekhy et al [14]. Then we propose a fast polynomial time greedy algorithm to find a near optimal coalition. The profit generated by the federation obtained using the greedy algorithm is within a negligible 0.06 percent of the optimal on an average. The greedy algorithm finds a federation 200 times faster on an average when compared with the Merge-Split algorithm. The payoff distribution within a federation is determined using exact Banzhaf index computation whereas the Merge-Split algorithm arrives at a payoff using an estimate of Banzhaf values. By computing the payoff distribution after the federation formation, we are able to achieve 66x speedup when compared with the Merge-Split algorithm. Finally, we describe an ensemble of problem instances wherein the ratio between the value of an optimal federation and that of the federation generated by the Merge-Split algorithm is unbounded. In the second part, we study how an oligopolist influences the coalition structure in federated cloud markets. Specifically, we use cooperative game theory to model the circumstances under which a cloud provider prefers to join a cloud federation vis-a-vis consider taking a price offer made by an oligopolist. Full thesis: pdf Centre for Software Engineering Research Lab |
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