Interference-Aware Game-Theoretic Device Allocation for Mobile Edge Computing

Mobile edge computing (MEC), as an emerging and prospective mobile computing paradigm, allows a content provider to serve its users by allocating their mobile devices to nearby edge servers to lower the latency in the delivery of its content to those mobile services. From the content provider's perspective, a cost-effective mobile device allocation (MDA) aims to allocate maximum mobile devices to minimum edge servers. However, the allocation of excessive mobile devices to an edge server may result in severe communication interference and consequently, impact mobile devices’ data rates. Sometimes, not all the mobile devices can be allocated to edge servers and thus have to retrieve content from the remote cloud through base stations with high latency. The connection between these mobile devices and base stations also incur communication interference. In this paper, we formally model this Interference-aware mobile edge device allocation (I-MEDA) problem, and propose a game-theoretic based approach named I-MEDAGame to formulate the I-MEDA problem as an I-MEDA game. In the I-MEDA game, allocation decisions are made for individual mobile devices in parallel to alleviate the need for centralized optimization. Our theoretical analysis of I-MEDAGame shows that it admits at least one Nash equilibrium. To solve the I-MEDA problem, I-MEDAGame employs a novel decentralized algorithm to find the Nash equilibrium of the IMEDA game. The performance of I-MEDAGame is theoretically analyzed and experimentally evaluated. The results show that I-MEDAGame can solve the I-MEDA problem effectively and efficiently, outperforming four representative approaches significantly.