Joint computing, communication and cost-aware task offloading in D2D-enabled Het-MEC

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dc.contributor.author Abbas, Nadine
dc.contributor.author Sharafeddine, Sanaa
dc.contributor.author Mourad, Azzam
dc.contributor.author Abou-Rjeily, Chadi
dc.contributor.author Fawaz, Wissam
dc.date.accessioned 2022-11-18T13:29:05Z
dc.date.available 2022-11-18T13:29:05Z
dc.date.copyright 2022 en_US
dc.date.issued 2022-11-18
dc.identifier.issn 1389-1286 en_US
dc.identifier.uri http://hdl.handle.net/10725/14277
dc.description.abstract Due to the exploding traffic demands and the diversity of novel applications requiring extensive computation and radio resources, research has been active to devise mechanisms for responding to these challenges. Mobile edge computing (MEC) and device-to-device (D2D) computation task offloading are expected to play a major role in serving devices with limited capabilities, and thus enhance system performance. In this work, we propose a joint computing, communication and cost-aware task offloading optimization problem aiming at maximizing the number of completed tasks, while minimizing energy consumption and monetary cost in D2D-enabled heterogeneous MEC networks. Our proposed scheme allows partial offloading where a requester mobile terminal offloads different parts of its data task simultaneously to multiple peer mobile terminals (MTs), edge servers and cloud. We formulate and solve the optimal allocation strategy then decompose the problem into two sub-problems in an attempt to reduce its complexity. Furthermore, we propose a low-complexity algorithm that generates high performance results and can be applied for large-scale networks. Compared to conventional and state-of-the-art system models, results show the effectiveness of the proposed schemes and provide useful insights into the tradeoffs between the number of completed tasks, energy consumption and monetary cost. en_US
dc.language.iso en en_US
dc.title Joint computing, communication and cost-aware task offloading in D2D-enabled Het-MEC en_US
dc.type Article en_US
dc.description.version Published en_US
dc.author.school SAS en_US
dc.author.idnumber 201802638 en_US
dc.author.idnumber 200904853 en_US
dc.author.idnumber 200701131 en_US
dc.author.idnumber 200602957 en_US
dc.author.department Computer Science & Mathematics en_US
dc.relation.journal Computer Networks en_US
dc.journal.volume 209 en_US
dc.keywords Mobile edge computing en_US
dc.keywords Cloud computing en_US
dc.keywords Partial offloading en_US
dc.keywords Computation resource allocation en_US
dc.keywords Radio resource allocation en_US
dc.keywords D2D communication en_US
dc.keywords Multi-RAT en_US
dc.identifier.doi https://doi.org/10.1016/j.comnet.2022.108900 en_US
dc.identifier.ctation Abbas, N., Sharafeddine, S., Mourad, A., Abou-Rjeily, C., & Fawaz, W. (2022). Joint computing, communication and cost-aware task offloading in D2D-enabled Het-MEC. Computer Networks, 209. en_US
dc.author.email nadine.abbas@lau.edu.lb en_US
dc.author.email azzam.mourad@lau.edu.lb en_US
dc.author.email chadi.abourjeily@lau.edu.lb en_US
dc.author.email wissam.fawaz@lau.edu.lb en_US
dc.identifier.tou http://libraries.lau.edu.lb/research/laur/terms-of-use/articles.php en_US
dc.identifier.url https://www.sciencedirect.com/science/article/pii/S1389128622000974 en_US
dc.orcid.id https://orcid.org/0000-0003-3028-326X en_US
dc.orcid.id https://orcid.org/0000-0001-9434-5322 en_US
dc.orcid.id https://orcid.org/0000-0003-2255-1842 en_US
dc.orcid.id https://orcid.org/0000-0002-8012-1157 en_US
dc.author.affiliation Lebanese American University en_US

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