loading page

An elastic framework construction method based on task migration in edge computing
  • +2
  • Yonglin Pu,
  • Ziyang Li,
  • Jiong Yu,
  • Liang Lu,
  • Binglei Guo
Yonglin Pu
Nanjing University of Information Science and Technology
Author Profile
Ziyang Li
Xinjiang University
Author Profile
Jiong Yu
Xinjiang University
Author Profile
Liang Lu
Civil Aviation University of China

Corresponding Author:[email protected]

Author Profile
Binglei Guo
Hubei University of Arts and Science
Author Profile


Edge computing (EC) is an efficient technology that enables end users to achieve the goal of high bandwidth and low latency by offloading computationally intensive tasks from mobile devices to edge servers. However, a major challenge arises when the processing load fluctuates continuously, leading to a performance bottleneck due to the inability to rescale edge node (EN) resources. To address this problem, the approach of task migration is introduced, and the resource constrained model, optimal communication overhead model, and optimal task migration model are built to form a theoretical foundation from which to propose a task migration based resilient framework construction method in EC. With the aid of the domino effect and the combined effect of task migration, a dynamic node-growing algorithm (DNGA) and a dynamic node-shrinking algorithm (DNSA), both based on the task migration strategy, are proposed. Specifically, the DNGA smoothly expands the EN scale when the processing load increases, while the DNSA shrinks the EN scale when the processing load decreases. The experimental results show that for standard benchmarks deployed on an elastic framework, the proposed method realizes a smooth scaling mechanism in the EC, which reduces the latency and improves the reliability of data processing.
28 Aug 2023Submitted to Software: Practice and Experience
28 Aug 2023Submission Checks Completed
28 Aug 2023Assigned to Editor
06 Sep 2023Review(s) Completed, Editorial Evaluation Pending
20 Sep 2023Reviewer(s) Assigned
30 Sep 2023Editorial Decision: Revise Major
21 Oct 20231st Revision Received
21 Oct 2023Submission Checks Completed
21 Oct 2023Assigned to Editor
21 Oct 2023Review(s) Completed, Editorial Evaluation Pending
24 Oct 2023Reviewer(s) Assigned
06 Nov 2023Editorial Decision: Revise Minor
15 Nov 20232nd Revision Received
16 Nov 2023Submission Checks Completed
16 Nov 2023Assigned to Editor
16 Nov 2023Review(s) Completed, Editorial Evaluation Pending
17 Nov 2023Reviewer(s) Assigned