Energy Minimization of Mobile Edge Computation Networks Based on Multi-variable

DING Jiawei

doi:10.15892/j.cnki.djzdxb.2023.03.006

Journal of Projectiles, Rockets, Missiles and Guidance >

2023 , Vol. 43 >Issue 3: 39 - 44

DOI: https://doi.org/10.15892/j.cnki.djzdxb.2023.03.006

Energy Minimization of Mobile Edge Computation Networks Based on Multi-variable

DING Jiawei

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School of Information Engineering, Zhengzhou University of Industrial Technology, Zhengzhou 451150, Henan, China

Received date: 2022-06-21

Online published: 2025-02-07

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Abstract

An unmanned aerial vehicle (UAV)-assisted mobile edge computing (MEC) networks fulfil the on-demand computation services for the mobile terminals (MTs). But the energy efficiency is still a major issue in this network. Therefore, for UAV-based mobile edge computation networks, energy consumption minimization algorithm (ECMA) is proposed in this paper. First, a target problem with three variables of time slot allocation, task allocation and UAV movement trajectory is constructed. Then, the target problem is divided into two subproblems:joint time slot allocation and task computation capacity, and UAV trajectory optimization. To solve the joint time allocation and computation task capacity, we proposed an iterative algorithm. Finally, to optimize the trajectory of the UAV, we used the successive convex approximation technique. Simulation results show that the proposed ECMA algorithm can effectively reduce energy consumption of networks, compared with orthogonal multiple access algorithm (OMAA) and equal power allocation algorithm (EPAA).

Key words： mobile edge computation; energy consumption; time slot allocation; task allocation; UAV movement trajectory

Cite this article

DING Jiawei . Energy Minimization of Mobile Edge Computation Networks Based on Multi-variable[J]. Journal of Projectiles, Rockets, Missiles and Guidance, 2023 , 43(3) : 39 -44 . DOI: 10.15892/j.cnki.djzdxb.2023.03.006

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