Edge Cloud Offloading Algorithms

Author:

Wang Jianyu1ORCID,Pan Jianli1,Esposito Flavio2,Calyam Prasad3,Yang Zhicheng4,Mohapatra Prasant4

Affiliation:

1. University of Missouri-St. Louis, St.Louis, MO

2. Saint Louis University, St. Louis, MO

3. University of Missouri-Columbia, Columbia, MO

4. University of California, Davis, CA

Abstract

Mobile devices supporting the “Internet of Things” often have limited capabilities in computation, battery energy, and storage space, especially to support resource-intensive applications involving virtual reality, augmented reality, multimedia delivery, and artificial intelligence, which could require broad bandwidth, low response latency, and large computational power. Edge cloud or edge computing is an emerging topic and a technology that can tackle the deficiencies of the currently centralized-only cloud computing model and move the computation and storage resources closer to the devices in support of the above-mentioned applications. To make this happen, efficient coordination mechanisms and “offloading” algorithms are needed to allow mobile devices and the edge cloud to work together smoothly. In this survey article, we investigate the key issues, methods, and various state-of-the-art efforts related to the offloading problem. We adopt a new characterizing model to study the whole process of offloading from mobile devices to the edge cloud. Through comprehensive discussions, we aim to draw an overall “big picture” on the existing efforts and research directions. Our study also indicates that the offloading algorithms in the edge cloud have demonstrated profound potentials for future technology and application development.

Funder

University of Missouri Research Board

National Science Foundation

Publisher

Association for Computing Machinery (ACM)

Subject

General Computer Science,Theoretical Computer Science

Reference53 articles.

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4. IoTFLiP: IoT-based flipped learning platform for medical education

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