Game Theory for Multi-Access Edge Computing: Survey, Use Cases, and Future Trends

TL;DR

This survey explores how game theory models are applied to Multi-Access Edge Computing (MEC) to optimize wireless network resources, address challenges, and guide future research directions.

Contribution

It provides a comprehensive review of classical and evolutionary game applications in MEC, highlighting challenges, strategies, and future trends in this emerging field.

Findings

Survey of classical and evolutionary game models in MEC

Identification of key challenges and strategies in MEC resource management

Future research directions in applying game theory to MEC services

Abstract

Game Theory (GT) has been used with significant success to formulate, and either design or optimize, the operation of many representative communications and networking scenarios. The games in these scenarios involve, as usual, diverse players with conflicting goals. This paper primarily surveys the literature that has applied theoretical games to wireless networks, emphasizing use cases of upcoming Multi-Access Edge Computing (MEC). MEC is relatively new and offers cloud services at the network periphery, aiming to reduce service latency backhaul load, and enhance relevant operational aspects such as Quality of Experience or security. Our presentation of GT is focused on the major challenges imposed by MEC services over the wireless resources. The survey is divided into classical and evolutionary games. Then, our discussion proceeds to more specific aspects which have a considerable impact on the game usefulness, namely: rational vs. evolving strategies, cooperation among players, available game information, the way the game is played (single turn, repeated), the game model evaluation, and how the model results can be applied for both optimizing resource-constrained resources and balancing diverse trade-offs in real edge networking scenarios. Finally, we reflect on lessons learned, highlighting future trends and research directions for applying theoretical model games in upcoming MEC services, considering both network design issues and usage scenarios.