Unloadable Computing Problem Based on Edge Distributed Computing

Xiaoliang He, Jiazhen Xu, Zhilin Yan

2025

Abstract

Due to limitations in power, computing power, and storage, mobile devices struggle to meet the demands of rapidly developing applications. Offloading computing has emerged as a promising solution, becoming a research focus. Edge distributed systems address this by offloading tasks from mobile devices to nearby edge servers or networked devices. This paper focuses on edge distributed computing offloading and conducts the following research: (1) An overview of common MEC mechanisms is provided, covering key technologies like virtualization, SDN, CDN, SON, cloud computing, and collaborative computing. The characteristics of edge distributed systems, such as scalability, location relevance, diversity, randomness, time-varying nature, and autonomy, are discussed. Typical MEC implementation methods and future trends are explored. (2) A shared bandwidth allocation algorithm using blockchain smart contracts is proposed to address wireless resource scheduling challenges. This scheme eliminates the need for a central server, reducing latency and enhancing scalability. (3) An optimized mobile edge collaborative learning algorithm is proposed, which reduces data traffic and communication delays by shifting machine learning tasks to local devices. A compact parameter set replaces redundant models to minimize excessive transmission.

Paper Citation

in Harvard Style

He X., Xu J. and Yan Z. (2025). Unloadable Computing Problem Based on Edge Distributed Computing. In Proceedings of the 2nd International Conference on Data Science and Engineering - Volume 1: ICDSE; ISBN 978-989-758-765-8, SciTePress, pages 638-644. DOI: 10.5220/0013703200004670

in Bibtex Style

@conference{icdse25,
author={Xiaoliang He and Jiazhen Xu and Zhilin Yan},
title={Unloadable Computing Problem Based on Edge Distributed Computing},
booktitle={Proceedings of the 2nd International Conference on Data Science and Engineering - Volume 1: ICDSE},
year={2025},
pages={638-644},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013703200004670},
isbn={978-989-758-765-8},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 2nd International Conference on Data Science and Engineering - Volume 1: ICDSE
TI - Unloadable Computing Problem Based on Edge Distributed Computing
SN - 978-989-758-765-8
AU - He X.
AU - Xu J.
AU - Yan Z.
PY - 2025
SP - 638
EP - 644
DO - 10.5220/0013703200004670
PB - SciTePress