Offloading Decision Making in Mobile Edge Computing: A Survey

Abstract

Mobile Edge Computing (MEC) is considered as a promising solution to augment the computational capabilities of mobile devices. Because of frequently changing locations, mobile users often see dynamically changing network conditions which have a great impact on the perceived application performance. Mobile users can offload computation-intensive tasks to edge clouds collocated with base stations. Task offloading in MEC is a solution to handle such computational-intensive applications. However, making high-quality offloading decisions at runtime is difficult in mobile environments. This paper presents a survey for offloading decisions in MEC. It shows the most critical issues and challenges that affect offloading decisions. In addition, the survey discusses the existing offloading decision-making approaches and models which have been categorized according to their schemes� optimization. Furthermore, a literature review of offloading decisions for various studies is investigated and analyzed from the perspectives of objectives, infrastructures, and optimization approach. Finally, the survey highlights the open research challenges and trends in the field of offloading decisions in MEC.