Towards Multi-Criteria Heuristic Optimization for Computational Offloading in Multi-Access Edge Computing

Abstract

In recent years, there has been considerable interest in computational offloading algorithms. The interest is mainly driven by the potential savings that offloading offers in task completion time and mobile device energy consumption. This paper builds on authors' previous work on computational offloading and describes a multi-objective optimization model that optimizes time and energy in a network with multiple Multi-Access Edge Computing servers (MECs) and Mobile Devices (MDs). Each MD has multiple computational jobs to process, and each task can be processed locally or offloaded to one of the MEC servers. Several heuristic offloading policies are proposed and tested with an objective function with a range of weightings for optimizing time and energy. The approaches are illustrated with the help of three test cases of varying complexity. The objective function shows a continuous variation as the emphasis is placed on either time or energy saving by the weighting factors. The numerical tests demonstrate that the proposed heuristic algorithms produce nearoptimal computational offloading solutions while considering a combined weighted score for schedule task completion time and energy

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“…In particular, the implementation of Multi Access Edge Computing has a clear business case for service providers to develop services and products for "vertical" markets, i.e. where an entire sector such as healthcare is considered as a whole; hardware enterprises must also be flexible on precise mechanisms for implementing Multi-Access Edge Computing because a wide range of applications will be recognized with different requirements and market sizes [223,224].…”

A Survey on Cloudlet Computation Optimization in the Mobile Edge Computing Environment

“…Most of the strategies presented in these technical publications were based on mathematics, model-based, machine learning, game theory, www.ijacsa.thesai.org heuristic-based, meta-heuristic, or a combination of the abovementioned techniques. In the MEC context, computation offloading problems are a very difficult challenge [14]. The primary drawback of offloading work to a remote cloud is the latency, which disrupts user experiences in interactive applications like mobile gaming [15].…”