Abstract
Cloud computing and other computing paradigms share the similar visions which aim to implement parallel computations on large distributed resources. However, this cloud computing is more involved in purchasing and consuming manners between providers and users than others. So how to allocate resources reasonably to cater requirements from both sides attracts wide attentions. Based on game theory, we introduce a new Bayesian Nash Equilibrium Allocation algorithm to solve resource management problem in cloud computing. This algorithm fully considers several criteria such as the heterogeneous distribution of resources, rational exchange behaviors of cloud users, incomplete common information and dynamic successive allocation. Compared to former researches, experimental results presented in this paper show that even though rivals’ information is uncertain, cloud users can receive Nash equilibrium allocation solutions by gambling stage by stage. Furthermore, the resource price evaluated by the algorithm will converge to the optimal price at the end of the gambling sequence.
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Teng, F., Magoulès, F. (2010). A New Game Theoretical Resource Allocation Algorithm for Cloud Computing. In: Bellavista, P., Chang, RS., Chao, HC., Lin, SF., Sloot, P.M.A. (eds) Advances in Grid and Pervasive Computing. GPC 2010. Lecture Notes in Computer Science, vol 6104. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-13067-0_35
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DOI: https://doi.org/10.1007/978-3-642-13067-0_35
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-13066-3
Online ISBN: 978-3-642-13067-0
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