基于改进蚁群算法的天基资源调度研究与仿真

doi:10.12068/j.issn.1005-3026.2023.02.003

东北大学学报（自然科学版） ›› 2023, Vol. 44 ›› Issue (2): 168-176.DOI: 10.12068/j.issn.1005-3026.2023.02.003

基于改进蚁群算法的天基资源调度研究与仿真

耿蓉，张昭，牛天水，王宇飞

(东北大学计算机科学与工程学院，辽宁沈阳110169)

修回日期:2021-12-16 接受日期:2021-12-16 发布日期:2023-02-27
通讯作者: 耿蓉
作者简介:耿蓉(1979-)，女，辽宁沈阳人，东北大学副教授.
基金资助:
中央高校基本科研业务费专项资金资助项目(N2116015，N2116020)；辽宁省医工交叉基金资助项目(2021-YGJC-24).

Research and Simulation of Space-based Resource Scheduling Based on Improved Ant Colony Algorithm

GENG Rong， ZHANG Zhao， NIU Tian-shui， WANG Yu-fei

School of Computer Science & Engineering， Northeastern University， Shenyang 110169， China.

Revised:2021-12-16 Accepted:2021-12-16 Published:2023-02-27
Contact: WANG Yu-fei
About author:-
Supported by:
-

摘要/Abstract

摘要： 天基信息网中卫星资源有限，在轨升级难度大，链路间通信时延高，导致大规模并发任务处理效率低下.针对任务简单并发且每个任务由一个节点处理的情况，构建基于动态优先级的任务模型，对天基信息网计算与存储资源构建基于模糊聚类理论的资源模型.提出基于改进蚁群算法的天基资源调度策略，引入负载均衡因子，改变信息素更新规则，调整任务分配策略，结合Min-Min算法促进任务执行及资源分配.仿真结果表明，本文算法和对比算法相比，任务完成时间缩短29.2%，任务累积价值高出37.9%，资源负载均衡度缩小75.5%，资源利用率高出22.4%，验证了本文算法的优异性.

关键词: 天基信息网；任务动态排序；资源聚类；蚁群算法；资源调度

Abstract: The satellite resources of the space-based information network are limited.It is difficult to upgrade in orbit and the delay of inter-link communication is high， which results in inefficient processing of large-scale concurrent tasks. A dynamic priority-based task model is constructed for situations where the task is simple and concurrent and each task is handled by one node. A resource model based on fuzzy clustering theory is constructed for computing and storage resources in space-based information network. Space-based resource scheduling strategy based on improved ant colony algorithm is proposed. Load balancing factor is introduced. Pheromone update rule is changed. Task allocation strategy is adjusted. Min-Min-algorithm is combined to promote task execution and resource allocation. Simulation results show that compared with the comparison algorithm， the task completion time is 29.2% shorter， the task cumulative value is 37.9% higher， the resource load equilibrium degree is 75.5% smaller， and the resource utilization rate is 22.4% higher， which verifies the excellence of the algorithm.

Key words: space-based information network; task dynamic sorting; resource clustering; ant colony algorithm; resource scheduling

中图分类号:

TP20

耿蓉，张昭，牛天水，王宇飞. 基于改进蚁群算法的天基资源调度研究与仿真[J]. 东北大学学报（自然科学版）, 2023, 44(2): 168-176.

GENG Rong， ZHANG Zhao， NIU Tian-shui， WANG Yu-fei. Research and Simulation of Space-based Resource Scheduling Based on Improved Ant Colony Algorithm[J]. Journal of Northeastern University(Natural Science), 2023, 44(2): 168-176.

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基于改进蚁群算法的天基资源调度研究与仿真

Research and Simulation of Space-based Resource Scheduling Based on Improved Ant Colony Algorithm

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