Electronic Science and Technology ›› 2022, Vol. 35 ›› Issue (9): 58-64.doi: 10.16180/j.cnki.issn1007-7820.2022.09.009

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Workflow Scheduling Algorithm Based on Mobile Perception in Mobile Edge Environment

WEI Zefeng1,ZHOU Yuanyuan2   

  1. 1. Computer and Software School,Hangzhou Dianzi University,Hangzhou 310018,China
    2. Anhui Province Key Laboratory of Simulation and Design for Electronic Information System,Hefei Normal University,Hefei 230039,China
  • Received:2021-03-29 Online:2022-09-15 Published:2022-09-15
  • Supported by:
    Key R&D Program of Zhejiang(2018C01012);Special Project of Provincial Scientific Research Platform of Hefei Normal University(2020PTZD07)


In the mobile edge computing environment, users can offload local computing-intensive tasks to the edge server, thereby shortening the completion time of the workflow and saving equipment energy consumption. However, many studies have neglected the influence of network connection changes caused by user movement on workflow scheduling. In view of the unreasonable unloading problem in the existing algorithms, a workflow scheduling algorithm MaWS is proposed. The algorithm predicts the user's movement trajectory to obtain a set of future communicable base stations, and incorporates genetic algorithms to formulate reasonable task execution sequence and execution position. The simulation results show that compared with algorithms such as HEFT and Greedy, the MaWS algorithm can effectively shorten the completion time of the workflow by 10% to 15% and reduce the energy consumption of the equipment by 8% to 13%, which indicates that the proposed MaWS algorithm is an effective solution for workflow scheduling under mobile edge computing.

Key words: mobile edge computing, workflow scheduling, mobile perception, task offloading, genetic algorithm, energy-saving, trajectory prediction, network connection changes

CLC Number: 

  • TP393