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Article: Redundant task offloading with dual-reliability in MEC-assisted vehicular networks

TitleRedundant task offloading with dual-reliability in MEC-assisted vehicular networks
Authors
KeywordsMalicious vehicles
Reliability
Task offloading
Vehicular networks
Issue Date4-Dec-2024
Citation
Vehicular Communications, 2025, v. 51 How to Cite?
Abstract

With the rise and development of intelligent vehicles, the computation capability of vehicles has increased rapidly and considerably. Vehicle-to-Vehicle (V2V) offloading, in which computation-intensive tasks are offloaded to underutilized vehicles, has been proposed. However, V2V offloading faces the challenges of task transmission reliability and task computation reliability. In V2V offloading, tasks are transmitted via V2V communication, which is volatile and spotty because of rapidly changing network topology and channel conditions between vehicles, resulting in time-varying delays of task transmission and even loss of connectivity. Thus, it is challenging to complete V2V offloading within a given delay constraint. In addition, the realistic diverse vehicular environment always comes with malicious vehicles, which can cause irreparable harm to V2V offloading. Therefore, in this paper, we propose a V2V task offloading scheme called Redundant Task Offloading with Dual-Reliability (RTODR), aiming to minimize task offloading costs while ensuring both task transmission reliability and task computation reliability in a Mobile Edge Computing (MEC)-assisted vehicular network. Specifically, for a computation task, a V2V connection is considered reliable only if the task can be successfully transmitted via the V2V connection within the deadline of the task. To ensure task computation reliability, task computation results from a trusty service vehicle are considered to be reliable. Then we formally model a Minimizing Task Offloading Cost with Dual-reliability (MTOCD) problem, which is mathematically formulated as a multi-objective optimization problem. Afterward, we propose a heuristic redundant task offloading algorithm, named Dual-Reliability Offloading (DRO), to solve the problem. Finally, comprehensive experiments have been conducted to demonstrate that RTODR achieves lower costs compared with other approaches.


Persistent Identifierhttp://hdl.handle.net/10722/359057
ISSN
2023 Impact Factor: 5.8
2023 SCImago Journal Rankings: 1.775

 

DC FieldValueLanguage
dc.contributor.authorDuan, Yaoxin-
dc.contributor.authorNie, Wendi-
dc.contributor.authorLee, Victor CS-
dc.contributor.authorLiu, Kai-
dc.date.accessioned2025-08-19T00:32:27Z-
dc.date.available2025-08-19T00:32:27Z-
dc.date.issued2024-12-04-
dc.identifier.citationVehicular Communications, 2025, v. 51-
dc.identifier.issn2214-2096-
dc.identifier.urihttp://hdl.handle.net/10722/359057-
dc.description.abstract<p>With the rise and development of intelligent vehicles, the computation capability of vehicles has increased rapidly and considerably. Vehicle-to-Vehicle (V2V) offloading, in which computation-intensive tasks are offloaded to underutilized vehicles, has been proposed. However, V2V offloading faces the challenges of task transmission reliability and task computation reliability. In V2V offloading, tasks are transmitted via V2V communication, which is volatile and spotty because of rapidly changing <a href="https://www.sciencedirect.com/topics/computer-science/network-topology" title="Learn more about network topology from ScienceDirect's AI-generated Topic Pages">network topology</a> and channel conditions between vehicles, resulting in time-varying delays of task transmission and even loss of connectivity. Thus, it is challenging to complete V2V offloading within a given delay constraint. In addition, the realistic diverse <a href="https://www.sciencedirect.com/topics/computer-science/vehicular-environment" title="Learn more about vehicular environment from ScienceDirect's AI-generated Topic Pages">vehicular environment</a> always comes with malicious vehicles, which can cause irreparable harm to V2V offloading. Therefore, in this paper, we propose a V2V task offloading scheme called Redundant Task Offloading with Dual-Reliability (RTODR), aiming to minimize task offloading costs while ensuring both task transmission reliability and task computation reliability in a <a href="https://www.sciencedirect.com/topics/computer-science/multi-access-edge-computing" title="Learn more about Mobile Edge Computing from ScienceDirect's AI-generated Topic Pages">Mobile Edge Computing</a> (MEC)-assisted <a href="https://www.sciencedirect.com/topics/computer-science/vehicular-network" title="Learn more about vehicular network from ScienceDirect's AI-generated Topic Pages">vehicular network</a>. Specifically, for a computation task, a V2V connection is considered reliable only if the task can be successfully transmitted via the V2V connection within the deadline of the task. To ensure task computation reliability, task computation results from a trusty service vehicle are considered to be reliable. Then we formally model a Minimizing Task Offloading Cost with Dual-reliability (MTOCD) problem, which is mathematically formulated as a multi-objective <a href="https://www.sciencedirect.com/topics/computer-science/optimization-problem" title="Learn more about optimization problem from ScienceDirect's AI-generated Topic Pages">optimization problem</a>. Afterward, we propose a heuristic redundant task offloading algorithm, named Dual-Reliability Offloading (DRO), to solve the problem. Finally, comprehensive experiments have been conducted to demonstrate that RTODR achieves lower costs compared with other approaches.<br></p>-
dc.languageeng-
dc.relation.ispartofVehicular Communications-
dc.rightsThis work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.-
dc.subjectMalicious vehicles-
dc.subjectReliability-
dc.subjectTask offloading-
dc.subjectVehicular networks-
dc.titleRedundant task offloading with dual-reliability in MEC-assisted vehicular networks-
dc.typeArticle-
dc.identifier.doi10.1016/j.vehcom.2024.100867-
dc.identifier.scopuseid_2-s2.0-85211148970-
dc.identifier.volume51-
dc.identifier.issnl2214-2096-

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