International Research Journal of Innovations in Engineering and Technology - IRJIET International Open Access, Monthly, Peer Reviewed, Reputed Journal ISSN (online): 2581-3048

Impact Factor (2025): 6.9

DOI Prefix: 10.47001/IRJIET

User-Centric Evaluation and Optimization of Resource Allocation in Edge Computing Environments

Mohamed Koroma (Ing)Lecturer, School of Technology, Computer Science & I.T Department, Njala University, Sierra Leone, West AfricaAlimamy Saidu kontehLecturer, Milton Margai Technical University, Electrical & Electronics Department Sierra Leone, West AfricaYahya Labay KamaraLecturer, School of Technology, Computer Science & I.T Department, Njala University, Sierra Leone, West AfricaChernor Gurasiue JallohSoftware Engineer, Nankai University, School of Software Engineering, Tianjin City, P.R. ChinaJustin Alhaji Conteh (Ing)MSc Scholar, Electrical Engineering, Xi’an Jiaotong University, Xi’an city, P.R. China

Vol 9 No 6 (2025): Volume 9, Issue 6, June 2025 | Pages: 80-100

International Research Journal of Innovations in Engineering and Technology

OPEN ACCESS | Research Article | Published Date: 14-06-2025

doi Logo doi.org/10.47001/IRJIET/2025.906010

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Abstract

The proliferation of mobile applications with intensive computational demands has necessitated the adoption of edge computing to reduce latency and energy consumption. However, edge servers face challenges such as limited resources, dynamic wireless conditions, and inefficient task offloading strategies, particularly in multi-user environments. This paper proposes a user-centric evaluation and optimization framework for resource allocation in edge computing, aiming to minimize latency and energy consumption while maximizing system efficiency. We introduce a greedy-competitive algorithm for dynamic task offloading and a joint communication-computation optimization model that adapts to real-time channel conditions and user requirements. The proposed approach leverages partial task offloading, dynamic voltage frequency scaling (DVFS), and optimal resource partitioning between edge and cloud servers. Simulation results demonstrate significant improvements in energy efficiency (up to 21.2% reduction) and latency reduction (up to 20% fewer task drops) compared to conventional greedy and local execution strategies. The study provides insights into optimal resource allocation, task scheduling, and energy-delay trade-offs in edge computing environments.

Keywords

Edge computing, resource optimization, task offloading, energy efficiency, latency minimization, greedy-competitive algorithm, dynamic computation offloading


Citation of this Article

Mohamed Koroma (Ing), Alimamy Saidu konteh, Yahya Labay Kamara, Chernor Gurasiue Jalloh, & Justin Alhaji Conteh (Ing). (2025). User-Centric Evaluation and Optimization of Resource Allocation in Edge Computing Environments. International Research Journal of Innovations in Engineering and Technology - IRJIET, 9(6), 80-100. Article DOI https://doi.org/10.47001/IRJIET/2025.906010

Licence Copyright (c) 2026 International Research Journal of Innovations in Engineering and Technology creative common licence This work is licensed under Creative common Attribution Non Commercial 4.0 Internation Licence
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