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Moura, J. & Hutchison, D. (2019). Game theory for multi-access edge computing: survey, use cases, and future trends. IEEE Communications Surveys and Tutorials. 21 (1), 260-288

J. A. Moura and D. Hutchison,  "Game theory for multi-access edge computing: survey, use cases, and future trends", in IEEE Communications Surveys and Tutorials, vol. 21, no. 1, pp. 260-288, 2019

@article{moura2019_1714288437032,
	author = "Moura, J. and Hutchison, D.",
	title = "Game theory for multi-access edge computing: survey, use cases, and future trends",
	journal = "IEEE Communications Surveys and Tutorials",
	year = "2019",
	volume = "21",
	number = "1",
	doi = "10.1109/COMST.2018.2863030",
	pages = "260-288",
	url = "https://ieeexplore.ieee.org/document/8424815/"
}

TY  - JOUR
TI  - Game theory for multi-access edge computing: survey, use cases, and future trends
T2  - IEEE Communications Surveys and Tutorials
VL  - 21
IS  - 1
AU  - Moura, J.
AU  - Hutchison, D.
PY  - 2019
SP  - 260-288
SN  - 1553-877X
DO  - 10.1109/COMST.2018.2863030
UR  - https://ieeexplore.ieee.org/document/8424815/
AB  - 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’s usefulness, namely: rational vs. evolving strategies, cooperation among players, available game information, the way the game is played (single turn, repeated), the game’s 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. 
ER  -