An efficient simulated annealing-based task scheduling technique for task offloading in a Mobile Edge Architecture

Ayeh Mahjoubi; Karl Johan Grinnemo; Javid Taheri

doi:10.1109/CloudNet55617.2022.9978900

An efficient simulated annealing-based task scheduling technique for task offloading in a Mobile Edge Architecture

Ayeh Mahjoubi, Karl Johan Grinnemo, Javid Taheri

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

9 Citations (Scopus)

Abstract

The Internet of Things (IoT) has emerged as a fundamental cornerstone in the digitalization of industry and society. Still, IoT devices' limited processing and memory capacities pose a problem for conducting complex and time-sensitive computations such as AI-based shop floor monitoring or personalized health tracking on these devices, and offloading to the cloud is not an option due to excessive delays. Edge computing has recently appeared to address the requirements of these IoT applications. This paper formulates the scheduling of tasks between IoT devices, edge servers, and the cloud in a three-layer Mobile Edge Computing (MEC) architecture as a Mixed-Integer Linear Programming (MILP) problem. The paper proposes a simulated annealing-based task scheduling technique and demonstrates that it schedules tasks almost as time-efficient as if the MILP problem had been solved with a mixed integer programming optimization package; however, at a fraction of the cost in terms of CPU, memory, and network resources. Also, the paper demonstrates that the proposed task scheduling technique compares favorably in terms of efficiency, resource consumption, and timeliness with previously proposed techniques based on heuristics, including genetic programming.

Original language	English
Title of host publication	Proceedings of the 2022 IEEE 11th International Conference on Cloud Networking (CloudNet)
Editors	Stefano Secci, Ramakrishnan Durairajan, Leonardo Linguaglossa, Noriaki Kamiyama, Michele Nogueira, Stephane Rovedakis
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	159-167
Number of pages	9
ISBN (Electronic)	9781665486279
ISBN (Print)	9781665486286
DOIs	https://doi.org/10.1109/CloudNet55617.2022.9978900
Publication status	Published - 16 Dec 2022
Externally published	Yes
Event	11th IEEE International Conference on Cloud Networking, CloudNet 2022 - Paris, France Duration: 07 Nov 2022 → 10 Nov 2022

Publication series

Name	Proceedings of the IEEE Conference on Cloud Networking, CloudNet
ISSN (Print)	2374-3239
ISSN (Electronic)	2771-5663

Conference

Conference	11th IEEE International Conference on Cloud Networking, CloudNet 2022
Country/Territory	France
City	Paris
Period	07/11/2022 → 10/11/2022

Bibliographical note

Publisher Copyright:
© 2022 IEEE.

Keywords

Edge/Cloud computing
Simulated annealing
Task offloading
Task scheduling
Time sensitivity

ASJC Scopus subject areas

Artificial Intelligence
Computer Networks and Communications
Hardware and Architecture
Information Systems and Management

Access to Document

10.1109/CloudNet55617.2022.9978900Licence: Unspecified

Cite this

Mahjoubi, A., Grinnemo, K. J., & Taheri, J. (2022). An efficient simulated annealing-based task scheduling technique for task offloading in a Mobile Edge Architecture. In S. Secci, R. Durairajan, L. Linguaglossa, N. Kamiyama, M. Nogueira, & S. Rovedakis (Eds.), Proceedings of the 2022 IEEE 11th International Conference on Cloud Networking (CloudNet) (pp. 159-167). (Proceedings of the IEEE Conference on Cloud Networking, CloudNet). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/CloudNet55617.2022.9978900

Mahjoubi, Ayeh ; Grinnemo, Karl Johan ; Taheri, Javid. / An efficient simulated annealing-based task scheduling technique for task offloading in a Mobile Edge Architecture. Proceedings of the 2022 IEEE 11th International Conference on Cloud Networking (CloudNet). editor / Stefano Secci ; Ramakrishnan Durairajan ; Leonardo Linguaglossa ; Noriaki Kamiyama ; Michele Nogueira ; Stephane Rovedakis. Institute of Electrical and Electronics Engineers Inc., 2022. pp. 159-167 (Proceedings of the IEEE Conference on Cloud Networking, CloudNet).

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abstract = "The Internet of Things (IoT) has emerged as a fundamental cornerstone in the digitalization of industry and society. Still, IoT devices' limited processing and memory capacities pose a problem for conducting complex and time-sensitive computations such as AI-based shop floor monitoring or personalized health tracking on these devices, and offloading to the cloud is not an option due to excessive delays. Edge computing has recently appeared to address the requirements of these IoT applications. This paper formulates the scheduling of tasks between IoT devices, edge servers, and the cloud in a three-layer Mobile Edge Computing (MEC) architecture as a Mixed-Integer Linear Programming (MILP) problem. The paper proposes a simulated annealing-based task scheduling technique and demonstrates that it schedules tasks almost as time-efficient as if the MILP problem had been solved with a mixed integer programming optimization package; however, at a fraction of the cost in terms of CPU, memory, and network resources. Also, the paper demonstrates that the proposed task scheduling technique compares favorably in terms of efficiency, resource consumption, and timeliness with previously proposed techniques based on heuristics, including genetic programming.",

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Mahjoubi, A, Grinnemo, KJ & Taheri, J 2022, An efficient simulated annealing-based task scheduling technique for task offloading in a Mobile Edge Architecture. in S Secci, R Durairajan, L Linguaglossa, N Kamiyama, M Nogueira & S Rovedakis (eds), Proceedings of the 2022 IEEE 11th International Conference on Cloud Networking (CloudNet). Proceedings of the IEEE Conference on Cloud Networking, CloudNet, Institute of Electrical and Electronics Engineers Inc., pp. 159-167, 11th IEEE International Conference on Cloud Networking, CloudNet 2022, Paris, France, 07/11/2022. https://doi.org/10.1109/CloudNet55617.2022.9978900

An efficient simulated annealing-based task scheduling technique for task offloading in a Mobile Edge Architecture. / Mahjoubi, Ayeh; Grinnemo, Karl Johan; Taheri, Javid.
Proceedings of the 2022 IEEE 11th International Conference on Cloud Networking (CloudNet). ed. / Stefano Secci; Ramakrishnan Durairajan; Leonardo Linguaglossa; Noriaki Kamiyama; Michele Nogueira; Stephane Rovedakis. Institute of Electrical and Electronics Engineers Inc., 2022. p. 159-167 (Proceedings of the IEEE Conference on Cloud Networking, CloudNet).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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AU - Grinnemo, Karl Johan

AU - Taheri, Javid

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KW - Task scheduling

KW - Time sensitivity

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Mahjoubi A, Grinnemo KJ, Taheri J. An efficient simulated annealing-based task scheduling technique for task offloading in a Mobile Edge Architecture. In Secci S, Durairajan R, Linguaglossa L, Kamiyama N, Nogueira M, Rovedakis S, editors, Proceedings of the 2022 IEEE 11th International Conference on Cloud Networking (CloudNet). Institute of Electrical and Electronics Engineers Inc. 2022. p. 159-167. (Proceedings of the IEEE Conference on Cloud Networking, CloudNet). doi: 10.1109/CloudNet55617.2022.9978900

An efficient simulated annealing-based task scheduling technique for task offloading in a Mobile Edge Architecture

Abstract

Publication series

Conference

Bibliographical note

Keywords

ASJC Scopus subject areas

Access to Document

Fingerprint

Cite this