Real-time Scheduling Strategy for Energy-aware Workflows in Edge-Cloud Collaborative Environments

Paper Title

Real-time Scheduling Strategy for Energy-aware Workflows in Edge-Cloud Collaborative Environments

Authors

Qin Zhiwei1,2, Li Juan1,2 (Corresponding Author), Liu Xiao3, Zhu Mengyuan1,2

Affiliations

1. School of Computer Science and Engineering, Wuhan University of Engineering

2. Hubei Key Laboratory of Intelligent Robotics, Wuhan University of Engineering

3. School of Information Technology, Deakin University

Funding

National Natural Science Foundation of China (62102292)

Hubei Natural Science Foundation (2019CFB172)

Youth Teacher Fund of Wuhan University of Engineering (K202035)

Research Fund of Hubei Key Laboratory of Intelligent Robotics (HBIRL202006)

Abstract

This paper addresses the challenges in workflow applications within edge-cloud collaborative environments, including the mobility of smart terminals, limited service range of edge servers, high real-time requirements from users, and terminal energy consumption. We establish a workflow task execution time model and a terminal energy consumption model based on effective collaboration of heterogeneous resources in edge-cloud environments. Building on this, we develop a real-time scheduling model for energy-aware workflows and propose an energy-aware workflow task scheduling algorithm. This algorithm first prioritizes subtasks based on workflow characteristics; then, it utilizes an improved particle swarm optimization algorithm to find an optimal resource scheduling scheme based on the initial location information of the terminal; subsequently, it filters transferable resources according to the terminal’s movement trajectory and dynamically selects the optimal migration decision for each task. Simulation results indicate that compared to existing strategies, the new strategy can reduce terminal energy consumption while meeting time delay constraints, achieving optimal system fitness values.

Author Biographies

Qin Zhiwei (1998-)

Male, from Xiaogan, Hubei, Master’s student at Wuhan University of Engineering, research interests: edge-cloud integration, edge computing, workflow scheduling.

E-mail: [email protected]

Li Juan (1989-)

Female, from Wuhan, Hubei, Lecturer at Wuhan University of Engineering, PhD, research interests: edge-cloud integration, workflow scheduling, Corresponding Author.

E-mail: [email protected]

Liu Xiao (1982-)

Male, from Tongling, Anhui, Senior Lecturer at Deakin University, PhD, research interests: edge computing, workflow systems.

E-mail: [email protected]

Zhu Mengyuan (1999-)

Female, from Suizhou, Hubei, Master’s student at Wuhan University of Engineering, research interests: edge computing, workflow scheduling.

E-mail: [email protected]

Paper Information

Qin Zhiwei, Li Juan, Liu Xiao, Zhu Mengyuan. Real-time Scheduling Strategy for Energy-aware Workflows in Edge-Cloud Collaborative Environments. Computer Integrated Manufacturing Systems, 2022, 28(10): 3122-3130.

DOI: 10.13196/j.cims.2022.10.009

Real-time Scheduling Strategy for Energy-aware Workflows in Edge-Cloud Collaborative EnvironmentsReal-time Scheduling Strategy for Energy-aware Workflows in Edge-Cloud Collaborative EnvironmentsReal-time Scheduling Strategy for Energy-aware Workflows in Edge-Cloud Collaborative EnvironmentsReal-time Scheduling Strategy for Energy-aware Workflows in Edge-Cloud Collaborative EnvironmentsReal-time Scheduling Strategy for Energy-aware Workflows in Edge-Cloud Collaborative EnvironmentsReal-time Scheduling Strategy for Energy-aware Workflows in Edge-Cloud Collaborative EnvironmentsReal-time Scheduling Strategy for Energy-aware Workflows in Edge-Cloud Collaborative EnvironmentsReal-time Scheduling Strategy for Energy-aware Workflows in Edge-Cloud Collaborative EnvironmentsReal-time Scheduling Strategy for Energy-aware Workflows in Edge-Cloud Collaborative Environments

This article is published in Computer Integrated Manufacturing Systems, Volume 28, Issue 10, 2022. Interested readers can click the bottom left corner to read the full text for free. The full text can be downloaded for free from the journal’s official website (www.cims-journal.cn).

Editorial Office of Computer Integrated Manufacturing Systems

Real-time Scheduling Strategy for Energy-aware Workflows in Edge-Cloud Collaborative Environments

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