Open AccessArtificial Intelligence based Edge Computing Framework for Optimization of Mobile Communication
Author(s) -
A. Sathesh
Publication year - 2020
Publication title -
journal of ismac the journal of iot in social, mobile, analytics, and cloud
Language(s) - English
Resource type - Journals
ISSN - 2582-1369
DOI - 10.36548/jismac.2020.3.004
Subject(s) - computer science , mobile edge computing , edge computing , enhanced data rates for gsm evolution , distributed computing , cloud computing , overhead (engineering) , mobile computing , mobile device , edge device , computer network , artificial intelligence , operating system
For improving the mobile service quality and acceleration of content delivery, edge computing techniques have been providing optimal solution to bridge the device requirements and cloud capacity by network edges. The advancements of technologies like edge computing and mobile communication has contributed greatly towards these developments. The mobile edge system is enabled with Machine Learning techniques in order to improve the edge system intelligence, optimization of communication, caching and mobile edge computing. For this purpose, a smart framework is developed based on artificial intelligence enabling reduction of unwanted communication load of the system as well as enhancement of applications and optimization of the system dynamically. The models can be trained more accurately using the learning parameters that are exchanged between the edge nodes and the collaborating devices. The adaptivity and cognitive ability of the system is enhanced towards the mobile communication system despite the low learning overhead and helps in attaining a near optimal performance. The opportunities and challenges of smart systems in the near future are also discussed in this paper.