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KCES: A Workflow Containerization Scheduling Scheme Under Cloud-Edge Collaboration Framework

delete2025-01-15
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PRE
AI
C
Chenggang Shan
R
Runze Gao
Q
Qinghua Han
T
Tian Liu
Z
Zhen Yang *
张金会 cover
张金会 (Jinhui Zhang)
Y
Yuanqing Xia *
DOI:10.1109/JIOT.2024.3466231delete
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Abstract

Abstract

En 中文
As more Internet of Things (IoT) applications gradually move toward the cloud-edge collaborative model, the containerized scheduling of workflows extends from the cloud to the edge. However, given the high delay of the communication network, loose coupling of structure, and resource heterogeneity between the cloud and the edge, workflow containerization scheduling in the cloud-edge scenarios faces the difficulty of resource collaboration and application collaboration management. To address these two issues, we propose a KubeEdge-cloud-edge-scheduling scheme named KCES. This workflow containerization scheduling scheme includes a cloud-edge workflow scheduling engine for KubeEdge and incorporates workflow scheduling strategies for tasks' horizontal roaming and vertical offloading. This article proposes a cloud-edge workflow scheduling model and node model, as well as a workflow scheduling engine designed to maximize cloud-edge resource utilization under the constraint of workflow task delay. A cloud-edge resource hybrid management technology is used to devise the cloud-edge resource evaluation and resource allocation algorithms to achieve cloud-edge resource collaboration. Based on the ideas of distributed functional roles and the hierarchical division of computing power, the horizontal roaming among the edges and cloud-edge vertical offloading strategies for workflow tasks are designed to realize cloud-edge application collaboration. Experimental results using a customized IoT application workflow instance demonstrate that KCES outperforms three comparing algorithms in total workflow time, average workflow time, and resource usage and features horizontal roaming and vertical offloading of workflow tasks.
Keywords:
Cloud computing
Collaboration
Scheduling
Job shop scheduling
Processor scheduling
Containers
Image edge detection
Application collaboration
cloud-edge collaboration
horizontal roaming
resource collaboration
vertical offloading
workflow scheduling

Journal

IEEE Internet of Things Journal cover
IEEE Internet of Things Journal
IF:
8.9
Papers:
1.4W
Citations:
7.8W

Organization

Z
zaozhuang university
Scholars:
940
Papers: 664
Citations: 1
B
beijing institute of technology
Scholars:
5.4W
Papers: 3.9W
Citations: 63