Journal article
MIEC: A magnetism-inspired framework for MS deployment and joint task offloading and resource allocation optimization in LMREC
Vehicular Communications, v 55, 100948
Oct 2025
Featured in Collection : Drexel's Newest Publications
Abstract
With the rapid growth of Internet of Things (IoT) devices, Mobile Edge Computing (MEC) faces challenges in meeting increasing computational demands, especially in resource-constrained environments. To address this issue, we propose the LEO Satellite-MS-RSU Edge Computing (LMREC) framework, which integrates Mobile Servers (MSs), Low Earth Orbit (LEO) satellite networks, and Roadside Units (RSUs) into an innovative edge computing architecture. We first introduce “attraction” and “repulsion” metrics to model the willingness of vehicular satellite servers to serve specific users. Subsequently, we design a Magnetic Equilibrium Algorithm (MEA), which dynamically adjusts the MS deployment and service allocation by balancing user-driven attraction and server repulsion. To address the latency sensitivity of task scheduling and user satisfaction in LMREC, we formulate a mixed-integer nonlinear programming (MINLP) optimization problem for task offloading and resource allocation. Since this optimization problem is intractable to solve in polynomial time, we propose a Magnetic Domain Migration Algorithm (MDMA) to obtain a near-optimal solution. In MDMA, tasks are modeled as magnetic domains migrating in a magnetic field, and the optimization problem is decomposed into subproblems, which are solved using Exact Potential Game Theory, convex optimization, and a hybrid genetic algorithm. Finally, simulation results validate the effectiveness of the LMREC framework, demonstrating its superiority over existing methods and its potential to enhance collaboration among end devices, RSUs, and LEO satellite networks.
•Mobile servers with ample energy and computing capacity enhance service availability in constrained edge environments.•A hybrid edge framework combines satellites, mobile servers, and roadside units.•A magnetic-inspired algorithm optimizes mobile server deployment and user selection.•Magnetic-domain-based multi-level offloading and resource allocation reduce latency and improve system utility.
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Details
- Title
- MIEC: A magnetism-inspired framework for MS deployment and joint task offloading and resource allocation optimization in LMREC
- Creators
- Mingyu Zhang - Hebei UniversityZhibo Sun - Drexel University, Computer Science (Computing)Fengjie Li - Hebei UniversityHong Zhang - Hebei University
- Publication Details
- Vehicular Communications, v 55, 100948
- Publisher
- Elsevier
- Number of pages
- 19
- Grant note
- QN2020133 / Science and Technology Research Project of Hebei Higher Education Institutions 22567638H / Innovation Capacity Enhancement Program-Science and Technology Platform Project of Hebei Province
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- Computer Science (Computing)
- Web of Science ID
- WOS:001523366100001
- Scopus ID
- 2-s2.0-105008999724
- Other Identifier
- 991022061629904721
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- Collaboration types
- Domestic collaboration
- International collaboration
- Web of Science research areas
- Telecommunications
- Transportation Science & Technology