Journal
IEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS
Volume 31, Issue 3, Pages 515-529Publisher
IEEE COMPUTER SOC
DOI: 10.1109/TPDS.2019.2938944
Keywords
Servers; Games; Edge computing; Resource management; Nash equilibrium; Cloud computing; Bandwidth; Edge user allocation; edge server; cost-effectiveness; pay-as-you-go; game theory; Nash equilibrium; multi-tenancy; edge computing
Funding
- Australian Research Council [DP170101932, DP180100212]
- National Science Foundation of China [61772461]
- Natural Science Foundation of Zhejiang Province [LR18F020003]
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Edge Computing provides mobile and Internet-of-Things (IoT) app vendors with a new distributed computing paradigm which allows an app vendor to deploy its app at hired edge servers distributed near app users at the edge of the cloud. This way, app users can be allocated to hired edge servers nearby to minimize network latency and energy consumption. A cost-effective edge user allocation (EUA) requires maximum app users to be served with minimum overall system cost. Finding a centralized optimal solution to this EUA problem is NP-hard. Thus, we propose EUAGame, a game-theoretic approach that formulates the EUA problem as a potential game. We analyze the game and show that it admits a Nash equilibrium. Then, we design a novel decentralized algorithm for finding a Nash equilibrium in the game as a solution to the EUA problem. The performance of this algorithm is theoretically analyzed and experimentally evaluated. The results show that the EUA problem can be solved effectively and efficiently.
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