TU Darmstadt / ULB / TUbiblio

Reconciling Task Assignment and Scheduling in Mobile Edge Clouds

Wang, Lin and Jiao, Lei and Kliazovich, Dzmitry and Bouvry, Pascal (2016):
Reconciling Task Assignment and Scheduling in Mobile Edge Clouds.
In: 2016 IEEE 24th International Conference on Network Protocols (ICNP), IEEE, Singapore, Singapore, DOI: 10.1109/ICNP.2016.7785317,
[Conference or Workshop Item]

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.

Item Type: Conference or Workshop Item
Erschienen: 2016
Creators: Wang, Lin and Jiao, Lei and Kliazovich, Dzmitry and Bouvry, Pascal
Title: Reconciling Task Assignment and Scheduling in Mobile Edge Clouds
Language: German
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.

Title of Book: 2016 IEEE 24th International Conference on Network Protocols (ICNP)
Number: 24
Publisher: IEEE
Uncontrolled Keywords: Internet of Things;cloud computing;electronic data interchange;integer programming;mobile computing;Internet-of-Things industry;NP-hardness;cloudlet heterogeneity;data computation;data transfer;mixed integer program;mobile computational tasks;mobile devic
Divisions: Profile Areas
Profile Areas > Cybersecurity (CYSEC)
Event Location: Singapore, Singapore
Date Deposited: 10 Aug 2017 16:03
DOI: 10.1109/ICNP.2016.7785317
Identification Number: TUD-CS-2016-14762
Export:

Optionen (nur für Redakteure)

View Item View Item