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基于多QoS约束条件的广域信息管理系统任务调度算法
Task scheduling algorithm for system-wide information management based on multiple QoS constraints
- 通信学报 2019年40卷第7期 页码：27-37
- 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：
[ "李罡（1981- ），男，满族，吉林长春人，天津大学博士生，主要研究方向为网络与信息安全。" ]
[ "吴志军（1965- ），男，河南固始人，博士，中国民航大学教授、博士生导师，主要研究方向为网络空间安全、大数据信息安全和云计算安全等。" ]
- 基金信息：天津市自然科学基金资助项目(17JCZDJC30900);国家自然科学基金资助项目(61601467);中央高校基本科研业务费专项资金资助项目(3122018D007)
DOI：10.11959/j.issn.1000-436x.2019166
中图分类号： TP393-
网络出版日期：2019-07，
纸质出版日期：2019-07-25
- 稿件说明：
移动端阅览
李罡, 吴志军. 基于多QoS约束条件的广域信息管理系统任务调度算法[J]. 通信学报, 2019,40(7):27-37.
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.
李罡, 吴志军. 基于多QoS约束条件的广域信息管理系统任务调度算法[J]. 通信学报, 2019,40(7):27-37. DOI： 10.11959/j.issn.1000-436x.2019166.
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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