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- Title
Online Cloud Provider Selection for QoS-Sensitive Users: Learning with Competition.
- Authors
Zhihao Wang; Junfang Wang; Bowen Li; Yijing Liu; Jinlong Ma
- Abstract
The expanding cloud computing services offer great opportunities for consumers to obtain better and cheaper service conveniently, which however raises new challenges on how to select the best service provider out of the huge pool. Although existing literatures have proposed several provider selection frameworks, none of them considered the performance unpredictability and dynamics caused by competition among cloud users. In this paper, we consider the online provider selection framework, where users dynamically and individually select their service providers based on experienced performance, and investigate the distributed decision-making strategy to achieve overall and individual performance guarantee. Specifically, we propose the learning-based selection policy, named Exp3.C, which regulates the system converging to a set of pure Nash equilibriums (PNE) of a congestion game in the homogeneous scenarios. Further, we show that even in a chaotic scenario where cloud users maybe irrational (which results in disordered and unpredictable behaviors) and the available resource of providers may change, the user's profit is guaranteed to approach that of selecting the best provider (which is derived with the assumption that all providers' status evolution are known) at the rate O(√T) in T rounds. Finally, numerical results validate the effectiveness of the proposed algorithm.
- Subjects
CLOUD computing; FEATURE selection; QUALITY of service; GAME theory; DISTANCE education
- Publication
IAENG International Journal of Computer Science, 2016, Vol 43, Issue 3, p108
- ISSN
1819-656X
- Publication type
Article