An Efficient Algorithm for Resource Allocation in Mobile Edge Computing Based on Convex Optimization and Karush–Kuhn–Tucker Method

Author:

Wang Kaijing1ORCID,Akhtar Shelily F.23ORCID,Al-Zahrani Fahad Ahmed4ORCID

Affiliation:

1. School of Management and Information, Chuzhou City Vocational College, Chuzhou 239000, Anhui, China

2. Electrical Engineering Department, Asia Pacific University, Dhaka, Bangladesh

3. Islamic University Centre for Scientific Research, The Islamic University, Najaf, Iraq

4. Department of Computer Engineering, Umm Al-Qura University, Mecca 24381, Saudi Arabia

Abstract

Mobile edge computing (MEC) is receiving more attention than centralized cloud computing due to the massive increase in transmission and compute requirements in 5G vehicle networks. It offers a significant amount of processing and storage resources to the edge of networks, offloading applications from vehicle terminals that are computation-intensive and delay-sensitive. For devices with limited resources, it uses edge resources to provide computationally heavy operations while conserving energy. This paper proposes a novel approach for computing offloading in MEC. To effectively optimize the MEC resources, this paper proposes a novel algorithm. First, the joint optimization and service cache decision subproblems were determined from continuous and discrete variables. Then, the near-optimal solution is determined from the subproblems through convex optimization and Karush–Kuhn–Tucker method. Simulation results show that the proposed algorithm has better computational offloading and resource allocation performance as compared to existing algorithms.

Funder

Ministry of Education – Kingdom of Saudi Arabia

Publisher

Hindawi Limited

Subject

Multidisciplinary,General Computer Science

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