LAPSE:2023.35131
Published Article
LAPSE:2023.35131
M-E-AWA: A Novel Task Scheduling Approach Based on Weight Vector Adaptive Updating for Fog Computing
April 28, 2023
Task offloading and real-time scheduling are hot topics in fog computing. This paper aims to address the challenges of complex modeling and solving multi-objective task scheduling in fog computing environments caused by widely distributed resources and strong load uncertainties. Firstly, a task unloading model based on dynamic priority adjustment is proposed. Secondly, a multi-objective optimization model is constructed for task scheduling based on the task unloading model, which optimizes time delay and energy consumption. The experimental results show that M-E-AWA (MOEA/D with adaptive weight adjustment based on external archives) can effectively handle multi-objective optimization problems with complex Pareto fronts and reduce the response time and energy consumption costs of task scheduling.
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Keywords
fog computing, MOEA/D, multi-objective evolutionary algorithm, task scheduling
Subject
Suggested Citation
Dai Z, Ding W, Min Q, Gu C, Yao B, Shen X. M-E-AWA: A Novel Task Scheduling Approach Based on Weight Vector Adaptive Updating for Fog Computing. (2023). LAPSE:2023.35131
Author Affiliations
Dai Z: School of Information Science and Engineering, East China University of Science and Technology, Shanghai 200237, China; School of Information Technology, Shanghai Jian Qiao University, Shanghai 201306, China [ORCID]
Ding W: School of Information Science and Engineering, East China University of Science and Technology, Shanghai 200237, China
Min Q: School of Information Science and Engineering, East China University of Science and Technology, Shanghai 200237, China
Gu C: School of Information Science and Engineering, East China University of Science and Technology, Shanghai 200237, China
Yao B: Shanghai Institute of Civil Defense Science, Shanghai 200020, China
Shen X: School of Information Science and Engineering, East China University of Science and Technology, Shanghai 200237, China
Ding W: School of Information Science and Engineering, East China University of Science and Technology, Shanghai 200237, China
Min Q: School of Information Science and Engineering, East China University of Science and Technology, Shanghai 200237, China
Gu C: School of Information Science and Engineering, East China University of Science and Technology, Shanghai 200237, China
Yao B: Shanghai Institute of Civil Defense Science, Shanghai 200020, China
Shen X: School of Information Science and Engineering, East China University of Science and Technology, Shanghai 200237, China
Journal Name
Processes
Volume
11
Issue
4
First Page
1053
Year
2023
Publication Date
2023-03-31
Published Version
ISSN
2227-9717
Version Comments
Original Submission
Other Meta
PII: pr11041053, Publication Type: Journal Article
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LAPSE:2023.35131
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doi:10.3390/pr11041053
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[v1] (Original Submission)
Apr 28, 2023
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Apr 28, 2023
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