Latency and Reliability-Aware Workload Assignment in IoT Networks with Mobile Edge Clouds

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dc.contributor.author Kherraf, Nouha
dc.contributor.author Sharafeddine, Sanaa
dc.contributor.author Assi, Chadi
dc.contributor.author Ghrayeb, Ali
dc.date.accessioned 2019-11-08T14:15:45Z
dc.date.available 2019-11-08T14:15:45Z
dc.date.copyright 2019 en_US
dc.date.issued 2019-11-08
dc.identifier.issn 1932-4537 en_US
dc.identifier.uri http://hdl.handle.net/10725/11509
dc.description.abstract Along with the dramatic increase in the number of IoT devices, different IoT services with heterogeneous QoS requirements are evolving with the aim of making the current society smarter and more connected. In order to deliver such services to the end users, the network infrastructure has to accommodate the tremendous workload generated by the smart devices and their heterogeneous and stringent latency and reliability requirements. This would only be possible with the emergence of ultra reliable low latency communications (uRLLC) promised by 5G. Mobile Edge Computing (MEC) has emerged as an enabling technology to help with the realization of such services by bringing the remote computing and storage capabilities of the cloud closer to the users. However, integrating uRLLC with MEC would require the network operator to efficiently map the generated workloads to MEC nodes along with resolving the trade-off between the latency and reliability requirements. Thus, we study in this paper the problem of Workload Assignment (WA) and formulate it as a Mixed Integer Program (MIP) to decide on the assignment of the workloads to the available MEC nodes. Due to the complexity of the WA problem, we decompose the problem into two subproblems; Reliability Aware Candidate Selection (RACS) and Latency Aware Workload Assignment (LAWA-MIP). We evaluate the performance of the decomposition approach and propose a more scalable approach; Tabu meta-heuristic (WA-Tabu). Through extensive numerical evaluation, we analyze the performance and show the efficiency of our proposed approach under different system parameters. en_US
dc.language.iso en en_US
dc.title Latency and Reliability-Aware Workload Assignment in IoT Networks with Mobile Edge Clouds en_US
dc.type Article en_US
dc.description.version Published en_US
dc.author.school SAS en_US
dc.author.idnumber 200502746 en_US
dc.author.department Computer Science And Mathematics en_US
dc.description.embargo N/A en_US
dc.relation.journal IEEE Transactions on Network and Service Management en_US
dc.journal.volume 16
dc.journal.issue 4
dc.article.pages 1435-1449
dc.keywords Reliability en_US
dc.keywords Internet of Things en_US
dc.keywords 5G mobile communication en_US
dc.keywords Task analysis en_US
dc.keywords Energy consumption en_US
dc.keywords Cloud computing en_US
dc.identifier.doi https://doi.org/10.1109/TNSM.2019.2946467 en_US
dc.identifier.ctation Kherraf, N., Sharafeddine, S., Assi, C. M., & Ghrayeb, A. (2019). Latency and reliability-aware workload assignment in iot networks with mobile edge clouds. IEEE Transactions on Network and Service Management, 16(4), 1435-1449. en_US
dc.author.email sanaa.sharafeddine@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://ieeexplore.ieee.org/abstract/document/8863420 en_US
dc.orcid.id https://orcid.org/0000-0001-6548-1624 en_US
dc.author.affiliation Lebanese American University en_US

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