@inproceedings{80aa7bcb87864bd1b96e1ec9ef4fad7d,
title = "Efficient computation offloading for multi-access edge computing in 5G HetNets",
abstract = "To meet the mobile devices' surging demands for throughput and computation resources in 5G networks, heterogeneous networks (HetNets) and multi-access edge computing (MEC) are expected to be two key distinct but complementary technologies. By offloading the computation tasks of the mobile devices (MDs) to the nearby MEC servers at the edge of radio access networks, MEC can largely augment the MDs' computation resources and battery lifetime. However, existing research on mobile-edge computation offloading only focused on multi-user single-MEC scenarios and little work can be found on designing computation offloading schemes for the case of multi-user multi-MEC. Toward this end, we investigate the problem of collaborative mobile-edge computation offloading in 5G HetNets and propose a game-theoretical computation offloading scheme. Numerical results corroborate that our collaborative computation offloading scheme for multiple MEC servers can not only reduce the overall computation overhead efficiently, but also achieve a Nash equilibrium in a finite number of steps.",
keywords = "5G, Computation offloading, Game theory, HetNets, MEC, Multi-access edge computing",
author = "Hongzhi Guo and Jiajia Liu and Jie Zhang",
note = "Publisher Copyright: {\textcopyright} 2018 IEEE.; 2018 IEEE International Conference on Communications, ICC 2018 ; Conference date: 20-05-2018 Through 24-05-2018",
year = "2018",
month = jul,
day = "27",
doi = "10.1109/ICC.2018.8422238",
language = "英语",
isbn = "9781538631805",
series = "IEEE International Conference on Communications",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "2018 IEEE International Conference on Communications, ICC 2018 - Proceedings",
}