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Reconciling Task Assignment and Scheduling in Mobile Edge Clouds

Wang, Lin ; Jiao, Lei ; Kliazovich, Dzmitry ; Bouvry, Pascal (2016)
Reconciling Task Assignment and Scheduling in Mobile Edge Clouds.
Singapore
Konferenzveröffentlichung, Bibliographie

Kurzbeschreibung (Abstract)

The prosperous growth of the Internet-of-Things industry attracts numerous interests in employing edge clouds (a.k.a. cloudlets) to enhance the performance of mobile services and applications. Most existing research has been focused on offloading computational tasks from mobile devices to a single cloudlet or a central location, yet overlooked the issue of jointly coordinating the offloaded tasks in a system of multiple cloudlets. In this paper, we fill this gap by investigating the assignment and the scheduling of mobile computational tasks over multiple cloudlets, while optimizing the overall cost efficiency by leveraging the heterogeneity of cloudlets. We model both data transfer and computation in terms of monetary and time costs, with task deadlines guaranteed. We formulate the problem as a mixed integer program and prove its NP-hardness. By introducing admission control for the cloudlet provider to shape the system workload, we transform our problem into maximizing the task admission rate over the two coupled phases: data transfer and computation. We propose an efficient two-phase scheduling algorithm, and demonstrate that, compared with the conventional approach of always selecting the closest cloudlet, our approach achieves significantly higher admission rate with up to 20\% reduction in the average cost of all offloaded tasks.

Typ des Eintrags: Konferenzveröffentlichung
Erschienen: 2016
Autor(en): Wang, Lin ; Jiao, Lei ; Kliazovich, Dzmitry ; Bouvry, Pascal
Art des Eintrags: Bibliographie
Titel: Reconciling Task Assignment and Scheduling in Mobile Edge Clouds
Sprache: Englisch
Publikationsjahr: November 2016
Buchtitel: Workshop on Hot Topics in Practical Networked Systems, in conjunction with International Conference on Network Protocols (ICNP)
Veranstaltungsort: Singapore
Kurzbeschreibung (Abstract):

The prosperous growth of the Internet-of-Things industry attracts numerous interests in employing edge clouds (a.k.a. cloudlets) to enhance the performance of mobile services and applications. Most existing research has been focused on offloading computational tasks from mobile devices to a single cloudlet or a central location, yet overlooked the issue of jointly coordinating the offloaded tasks in a system of multiple cloudlets. In this paper, we fill this gap by investigating the assignment and the scheduling of mobile computational tasks over multiple cloudlets, while optimizing the overall cost efficiency by leveraging the heterogeneity of cloudlets. We model both data transfer and computation in terms of monetary and time costs, with task deadlines guaranteed. We formulate the problem as a mixed integer program and prove its NP-hardness. By introducing admission control for the cloudlet provider to shape the system workload, we transform our problem into maximizing the task admission rate over the two coupled phases: data transfer and computation. We propose an efficient two-phase scheduling algorithm, and demonstrate that, compared with the conventional approach of always selecting the closest cloudlet, our approach achieves significantly higher admission rate with up to 20\% reduction in the average cost of all offloaded tasks.

Freie Schlagworte: - SUN - Smart Urban Networks
ID-Nummer: TUD-CS-2016-1439
Fachbereich(e)/-gebiet(e): 20 Fachbereich Informatik
20 Fachbereich Informatik > Telekooperation
Hinterlegungsdatum: 31 Dez 2016 12:59
Letzte Änderung: 03 Jun 2018 21:29
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