Task scheduling algorithm for system-wide information management based on multiple QoS constraints

Gang LI; Zhijun WU

doi:10.11959/j.issn.1000-436x.2019166

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Task scheduling algorithm for system-wide information management based on multiple QoS constraints

Papers | 更新时间：2024-06-05

- Task scheduling algorithm for system-wide information management based on multiple QoS constraints
- Journal on Communications Vol. 40, Issue 7, Pages: 27-37(2019)
- 作者机构：
  
  1. 天津大学电气自动化与信息工程学院，天津 300072
  2. 白城师范学院机械工程学院，吉林白城137000
  3. 中国民航大学电子信息与自动化学院，天津 300300
- 作者简介：
- 基金信息：
  
  The Natural Science Foundation of Tianjin(17JCZDJC30900);The National Natural Science Foundation of China(61601467);The Fundamental Research Funds for the Central Universities(3122018D007)
- DOI：10.11959/j.issn.1000-436x.2019166
  CLC： TP393
- Online First：2019-07，
  
  Published：25 July 2019
- 稿件说明：
移动端阅览
Gang LI, Zhijun WU. Task scheduling algorithm for system-wide information management based on multiple QoS constraints[J]. Journal on Communications, 2019, 40(7): 27-37.
DOI：

Gang LI, Zhijun WU. Task scheduling algorithm for system-wide information management based on multiple QoS constraints[J]. Journal on Communications, 2019, 40(7): 27-37. DOI： 10.11959/j.issn.1000-436x.2019166.

摘要

提出了面向广域信息管理系统（SWIM）的多QoS约束条件的蚁群优化任务调度算法（QoS-ACO）。针对SWIM中用户对任务请求完成服务质量（QoS）的要求，综合考虑任务完成时间、执行安全性和可靠性因素，构造了新的用户综合满意度评价函数和系统任务调度模型，使用SWIM中业务调度QoS总效用评价函数来更新蚁群算法中的信息素。仿真实验结果表明，同等条件下QoS-ACO算法在任务完成时间、安全性、可靠性和QoS总效用值方面都优于传统 Min-Min 算法和粒子群优化算法，满足用户的任务调度服务质量要求，较好地完成了SWIM调度任务。

Abstract

An ant colony optimization task scheduling algorithm based on multiple quality of service constraint (QoS-ACO) for SWIM was proposed.Focusing on the multiple quality of service (QoS) requirements for task requests completed in system-wide information management (SWIM)

considering the task execution time

security and reliability factors

a new evaluate user satisfaction utility function and system task scheduling model were constructed.Using the QoS total utility evaluation function of SWIM service scheduling to update the pheromone of the ant colony algorithm.The simulation results show that under the same conditions

the QoS-ACO algorithm is better than the traditional Min-Min algorithm and particle swarm optimization (PSO) algorithm in terms of task completion time

security

reliability and quality of service total utility evaluation value

and it can ensure that the user's task scheduling quality of service requirements are met

and can better complete the scheduling tasks of the SWIM.

关键词

Keywords

references

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