The Science and Information (SAI) Organization
  • Home
  • About Us
  • Journals
  • Conferences
  • Contact Us

Publication Links

  • IJACSA
  • Author Guidelines
  • Publication Policies
  • Digital Archiving Policy
  • Promote your Publication
  • Metadata Harvesting (OAI2)

IJACSA

  • About the Journal
  • Call for Papers
  • Editorial Board
  • Author Guidelines
  • Submit your Paper
  • Current Issue
  • Archives
  • Indexing
  • Fees/ APC
  • Reviewers
  • Apply as a Reviewer

IJARAI

  • About the Journal
  • Archives
  • Indexing & Archiving

Special Issues

  • Home
  • Archives
  • Proposals
  • Guest Editors
  • SUSAI-EE 2025
  • ICONS-BA 2025
  • IoT-BLOCK 2025

Future of Information and Communication Conference (FICC)

  • Home
  • Call for Papers
  • Submit your Paper/Poster
  • Register
  • Venue
  • Contact

Computing Conference

  • Home
  • Call for Papers
  • Submit your Paper/Poster
  • Register
  • Venue
  • Contact

Intelligent Systems Conference (IntelliSys)

  • Home
  • Call for Papers
  • Submit your Paper/Poster
  • Register
  • Venue
  • Contact

Future Technologies Conference (FTC)

  • Home
  • Call for Papers
  • Submit your Paper/Poster
  • Register
  • Venue
  • Contact
  • Home
  • Call for Papers
  • Editorial Board
  • Guidelines
  • Submit
  • Current Issue
  • Archives
  • Indexing
  • Fees
  • Reviewers
  • Subscribe

DOI: 10.14569/IJACSA.2024.01504122
PDF

Dynamic Task Offloading Optimization in Mobile Edge Computing Systems with Time-Varying Workloads Using Improved Particle Swarm Optimization

Author 1: Mohammad Asique E Rasool
Author 2: Anoop Kumar
Author 3: Asharul Islam

International Journal of Advanced Computer Science and Applications(IJACSA), Volume 15 Issue 4, 2024.

  • Abstract and Keywords
  • How to Cite this Article
  • {} BibTeX Source

Abstract: Mobile edge computing (MEC) enables offloading of compute-intensive and latency-sensitive tasks from resource-constrained mobile devices to servers at the network edge. This paper considers the dynamic optimization of task offloading in multi-user multi-server MEC systems with time-varying task workloads. The arrival times and computational demands of tasks are modeled as stochastic processes. The goal is to minimize the average task delay by optimal dynamic server selection over time. A particle swarm optimization (PSO) based algorithm is proposed that makes efficient offloading decisions in each time slot based on newly arrived tasks and pending workload across servers. The PSO-based policy is shown to outperform heuristics like genetic algorithms and simulated annealing in terms of adaptability to workload fluctuations and spikes. Experiments under varying task arrival rates demonstrate PSO’s capability to dynamically optimize time-averaged delay and energy costs through joint optimization of server selection and resource allocation. The proposed techniques provide a practical and efficient dynamic load balancing mechanism for real-time MEC systems with variable workloads.

Keywords: Particle Swarm Optimization (PSO); Mobile Edge Computing (MEC); Multi-User Multi-Server systems; dynamic load balancing

Mohammad Asique E Rasool, Anoop Kumar and Asharul Islam, “Dynamic Task Offloading Optimization in Mobile Edge Computing Systems with Time-Varying Workloads Using Improved Particle Swarm Optimization” International Journal of Advanced Computer Science and Applications(IJACSA), 15(4), 2024. http://dx.doi.org/10.14569/IJACSA.2024.01504122

@article{Rasool2024,
title = {Dynamic Task Offloading Optimization in Mobile Edge Computing Systems with Time-Varying Workloads Using Improved Particle Swarm Optimization},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2024.01504122},
url = {http://dx.doi.org/10.14569/IJACSA.2024.01504122},
year = {2024},
publisher = {The Science and Information Organization},
volume = {15},
number = {4},
author = {Mohammad Asique E Rasool and Anoop Kumar and Asharul Islam}
}



Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

IJACSA

Upcoming Conferences

IntelliSys 2025

28-29 August 2025

  • Amsterdam, The Netherlands

Future Technologies Conference 2025

6-7 November 2025

  • Munich, Germany

Healthcare Conference 2026

21-22 May 2026

  • Amsterdam, The Netherlands

Computing Conference 2026

9-10 July 2026

  • London, United Kingdom

IntelliSys 2026

3-4 September 2026

  • Amsterdam, The Netherlands

Computer Vision Conference 2026

15-16 October 2026

  • Berlin, Germany
The Science and Information (SAI) Organization
BACK TO TOP

Computer Science Journal

  • About the Journal
  • Call for Papers
  • Submit Paper
  • Indexing

Our Conferences

  • Computing Conference
  • Intelligent Systems Conference
  • Future Technologies Conference
  • Communication Conference

Help & Support

  • Contact Us
  • About Us
  • Terms and Conditions
  • Privacy Policy

© The Science and Information (SAI) Organization Limited. All rights reserved. Registered in England and Wales. Company Number 8933205. thesai.org