Research Article
Research on Task Scheduling Algorithms for Cloud-Edge Collaboration
@INPROCEEDINGS{10.1007/978-3-031-65123-6_12, author={Shuai Lu and Haibo Zhou and Shuaishuai Zhao and Wangbei Xu and Kai Fang}, title={Research on Task Scheduling Algorithms for Cloud-Edge Collaboration}, proceedings={Quality, Reliability, Security and Robustness in Heterogeneous Systems. 19th EAI International Conference, QShine 2023, Shenzhen, China, October 8 -- 9, 2023, Proceedings, Part II}, proceedings_a={QSHINE PART 2}, year={2024}, month={8}, keywords={Cloud-Edge Collaboration Optimization Objective Task Scheduling}, doi={10.1007/978-3-031-65123-6_12} }- Shuai Lu
Haibo Zhou
Shuaishuai Zhao
Wangbei Xu
Kai Fang
Year: 2024
Research on Task Scheduling Algorithms for Cloud-Edge Collaboration
QSHINE PART 2
Springer
DOI: 10.1007/978-3-031-65123-6_12
Abstract
With the advent of the 5G era, the development of IoT technology has been accelerated. Due to the continuous increase in the amount of data waiting to be processed from the edge, edge nodes may struggle to handle such a vast amount of data. Therefore, the technology of cloud-edge collaboration has emerged, and how to achieve cloud-edge collaborative task scheduling has become a current research hotspot. This article provides a detailed exposition of the relevant work on task scheduling in the cloud-edge environment, and outlines the common optimization objectives in the cloud-edge collaboration scenario. The methods used to solve task scheduling problems are classified and summarized, including heuristic, heuristic algorithm based on linear programming, and meta-heuristic algorithms. The advantages and disadvantages of each algorithm are analyzed. Finally, the development trends of large-scale task scheduling in the cloud-edge environment are discussed, providing valuable insights for achieving real-time performance, efficiency, and energy conservation in the Internet of Things.
