Abstract
In edge computing, app vendors provide task-offloading services to small intelligent devices with limited resources via edge servers. Users of these devices aim to utilize a better quality of service at a lower cost, and the app vendor tries to maximize their user base. In this paper, we propose an edge computing resource allocation technique to address the critical issue of maintaining a trade-off between user cost and QoS while increasing the number of users served by the app vendor. In the proposed technique, we formulate the problem as an Edge Server Selection Game (ESSGame), where users can optimize individual objective functions. An Edge Server Selection Algorithm (ESSA) is presented by which the system quickly converges to a pure Nash equilibrium (PNE). It is proved that ESSAGame is a potential game with at least one PNE. The quality of the PNE in ESSGame is also determined in terms of the Price of Stability (PoS). Numerical results are also presented for the performance of the proposed technique.
Published Version
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