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  • 标题:Ant Colony Optimization Task Scheduling Algorithm for SWIM Based on Load Balancing
  • 本地全文:下载
  • 作者:Gang Li ; Zhijun Wu
  • 期刊名称:Future Internet
  • 电子版ISSN:1999-5903
  • 出版年度:2019
  • 卷号:11
  • 期号:4
  • 页码:1-18
  • DOI:10.3390/fi11040090
  • 出版社:MDPI Publishing
  • 摘要:This paper focuses on the load imbalance problem in System Wide Information Management (SWIM) task scheduling. In order to meet the quality requirements of users for task completion, we studied large-scale network information system task scheduling methods. Combined with the traditional ant colony optimization (ACO) algorithm, using the hardware performance quality index and load standard deviation function of SWIM resource nodes to update the pheromone, a SWIM ant colony task scheduling algorithm based on load balancing (ACTS-LB) is presented in this paper. The experimental simulation results show that the ACTS-LB algorithm performance is better than the traditional min-min algorithm, ACO algorithm and particle swarm optimization (PSO) algorithm. It not only reduces the task execution time and improves the utilization of system resources, but also can maintain SWIM in a more load balanced state.
  • 关键词:System Wide Information Management; ant colony optimization algorithm; hardware performance quality index; load standard deviation function; load balancing System Wide Information Management ; ant colony optimization algorithm ; hardware performance quality index ; load standard deviation function ; load balancing
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