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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