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Synergistic task-offloading in 6G edge networks based on propagation dynamics

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Bibliographic Details
Title: Synergistic task-offloading in 6G edge networks based on propagation dynamics
Authors: Chao Zhu, Yuexia Zhang, Xinyi Wang, Xuzhen Zhu
Source: Frontiers in Physics, Vol 13 (2025)
Publisher Information: Frontiers Media S.A., 2025.
Publication Year: 2025
Collection: LCC:Physics
Subject Terms: 6G edge networks, propagation dynamics, D2D, task-offloading, evolution mechanism, Physics, QC1-999
Description: In future 6G edge networks, Device-to-Device (D2D)-assisted Mobile Edge Computing (MEC) can fully utilize the idle resources of user terminals (UT) and alleviate the burden on backhaul links. However, the limited idle resources of UT and the over-reliance on D2D-assisted computation offloading may result in a large number of terminals experiencing task overload, which could lead to the risk of edge network paralysis. To address these issues, this paper establishes a Service-Auxiliary-Request-Healing (SARH) task-offloading propagation model based on propagation dynamics theory. This model describes the dynamic transmission process of offloaded tasks in 6G edge networks and constructs two linear threshold functions to characterize the differences in task processing capabilities between UT and edge servers (ES). Furthermore, the proposed task-offloading propagation model is theoretically analyzed using edge compartment theory, and the propagation dynamics equations are established to derive the saddle point and critical conditions leading to task overload in a large number of UT, providing theoretical guidance for preventing network paralysis. Finally, simulation results show that the SARH model effectively describes the task-offloading propagation process in edge networks, and by controlling key factors such as the proportion of UT selecting D2D-assisted MEC synergistic task-offloading, network connectivity density, and network degree distribution heterogeneity, network paralysis can be avoided.
Document Type: article
File Description: electronic resource
Language: English
ISSN: 2296-424X
Relation: https://www.frontiersin.org/articles/10.3389/fphy.2025.1629142/full; https://doaj.org/toc/2296-424X
DOI: 10.3389/fphy.2025.1629142
Access URL: https://doaj.org/article/a5ceca3cfde54e9a85674a2992bd3752
Accession Number: edsdoj.5ceca3cfde54e9a85674a2992bd3752
Database: Directory of Open Access Journals
Description
Abstract:In future 6G edge networks, Device-to-Device (D2D)-assisted Mobile Edge Computing (MEC) can fully utilize the idle resources of user terminals (UT) and alleviate the burden on backhaul links. However, the limited idle resources of UT and the over-reliance on D2D-assisted computation offloading may result in a large number of terminals experiencing task overload, which could lead to the risk of edge network paralysis. To address these issues, this paper establishes a Service-Auxiliary-Request-Healing (SARH) task-offloading propagation model based on propagation dynamics theory. This model describes the dynamic transmission process of offloaded tasks in 6G edge networks and constructs two linear threshold functions to characterize the differences in task processing capabilities between UT and edge servers (ES). Furthermore, the proposed task-offloading propagation model is theoretically analyzed using edge compartment theory, and the propagation dynamics equations are established to derive the saddle point and critical conditions leading to task overload in a large number of UT, providing theoretical guidance for preventing network paralysis. Finally, simulation results show that the SARH model effectively describes the task-offloading propagation process in edge networks, and by controlling key factors such as the proportion of UT selecting D2D-assisted MEC synergistic task-offloading, network connectivity density, and network degree distribution heterogeneity, network paralysis can be avoided.
ISSN:2296424X
DOI:10.3389/fphy.2025.1629142