Intelligent networking with Mobile Edge Computing: Vision and Challenges for Dynamic Network Scheduling [article]

Shuo Wan, Jiaxun Lu, Pingyi Fan, Khaled B. Letaief
2020 arXiv   pre-print
Mobile edge computing (MEC) has been considered as a promising technique for internet of things (IoT). By deploying edge servers at the proximity of devices, it is expected to provide services and process data at a relatively low delay by intelligent networking. However, the vast edge servers may face great challenges in terms of cooperation and resource allocation. Furthermore, intelligent networking requires online implementation in distributed mode. In such kinds of systems, the network
more » ... uling can not follow any previously known rule due to complicated application environment. Then statistical learning rises up as a promising technique for network scheduling, where edges dynamically learn environmental elements with cooperations. It is expected such learning based methods may relieve deficiency of model limitations, which enhance their practical use in dynamic network scheduling. In this paper, we investigate the vision and challenges of the intelligent IoT networking with mobile edge computing. From the systematic viewpoint, some major research opportunities are enumerated with respect to statistical learning.
arXiv:2004.13926v1 fatcat:r5talij4ujbidbxjb5rkohtv7i