天空地一体化网络中的智能协同任务调度

Cuiqin Dai, Xian Li, Qianbin Chen
{"title":"天空地一体化网络中的智能协同任务调度","authors":"Cuiqin Dai, Xian Li, Qianbin Chen","doi":"10.1109/WCSP.2019.8928112","DOIUrl":null,"url":null,"abstract":"The Space-Air-Ground Integrated Network (SAGIN) is a new network structure integrating satellite systems, air networks and ground communications to achieve high throughput and reliability for data delivery. To realize the efficient data delivery and task management in SAGIN, task scheduling should be designed. In this paper, we first present a SAGIN model to reduce the number of satellite attitude adjustment and increase task scheduling time, which is constructed by satellites, Unmanned Aerial Vehicles (UAVs), and ground stations. Then, the scheduling problem in SAGIN is formulated to maximize sum priorities of successfully scheduled tasks under some constrains (e.g., switch time, storage capacity, etc.). After that, an intelligent coordinated scheduling algorithm named APSO-ICSA is proposed with an Adaptive Particle Swarm Optimization (APSO). In APSO-ICSA, three task scheduling processes of collection, storage and transmission are considered jointly for resource interaction, and the global and local search capabilities of particles are adjusted dynamically with adaptive inertia weight. Additionally, a two-criterion resource allocation method is developed for less scheduling conflict, and the scheduling order is determined in virtue of the task priority and deadline. Finally, simulation results show that the proposed APSO-ICSA has superiority both in the sum priority and guarantee ratio.","PeriodicalId":108635,"journal":{"name":"2019 11th International Conference on Wireless Communications and Signal Processing (WCSP)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"9","resultStr":"{\"title\":\"Intelligent Coordinated Task Scheduling in Space-Air-Ground Integrated Network\",\"authors\":\"Cuiqin Dai, Xian Li, Qianbin Chen\",\"doi\":\"10.1109/WCSP.2019.8928112\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The Space-Air-Ground Integrated Network (SAGIN) is a new network structure integrating satellite systems, air networks and ground communications to achieve high throughput and reliability for data delivery. To realize the efficient data delivery and task management in SAGIN, task scheduling should be designed. In this paper, we first present a SAGIN model to reduce the number of satellite attitude adjustment and increase task scheduling time, which is constructed by satellites, Unmanned Aerial Vehicles (UAVs), and ground stations. Then, the scheduling problem in SAGIN is formulated to maximize sum priorities of successfully scheduled tasks under some constrains (e.g., switch time, storage capacity, etc.). After that, an intelligent coordinated scheduling algorithm named APSO-ICSA is proposed with an Adaptive Particle Swarm Optimization (APSO). In APSO-ICSA, three task scheduling processes of collection, storage and transmission are considered jointly for resource interaction, and the global and local search capabilities of particles are adjusted dynamically with adaptive inertia weight. Additionally, a two-criterion resource allocation method is developed for less scheduling conflict, and the scheduling order is determined in virtue of the task priority and deadline. Finally, simulation results show that the proposed APSO-ICSA has superiority both in the sum priority and guarantee ratio.\",\"PeriodicalId\":108635,\"journal\":{\"name\":\"2019 11th International Conference on Wireless Communications and Signal Processing (WCSP)\",\"volume\":\"16 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"9\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 11th International Conference on Wireless Communications and Signal Processing (WCSP)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/WCSP.2019.8928112\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 11th International Conference on Wireless Communications and Signal Processing (WCSP)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/WCSP.2019.8928112","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 9

摘要

天空-地一体化网络(SAGIN)是一种集成卫星系统、空中网络和地面通信的新型网络结构,以实现数据传输的高吞吐量和可靠性。为了在SAGIN中实现高效的数据传递和任务管理,需要对任务调度进行设计。为了减少卫星姿态调整次数,增加任务调度时间,本文首先提出了一种由卫星、无人机和地面站共同构建的SAGIN模型。然后,在一定的约束条件下(如切换时间、存储容量等),制定SAGIN中的调度问题,使调度成功的任务的优先级总和最大化。在此基础上,提出了一种基于自适应粒子群算法的智能协调调度算法APSO- icsa。该算法将采集、存储和传输三个任务调度过程结合起来进行资源交互,利用自适应惯性权动态调整粒子的全局和局部搜索能力。此外,为了减少调度冲突,提出了一种双准则资源分配方法,并根据任务优先级和截止日期确定调度顺序。仿真结果表明,所提出的APSO-ICSA在总优先级和保证比方面都具有优势。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Intelligent Coordinated Task Scheduling in Space-Air-Ground Integrated Network
The Space-Air-Ground Integrated Network (SAGIN) is a new network structure integrating satellite systems, air networks and ground communications to achieve high throughput and reliability for data delivery. To realize the efficient data delivery and task management in SAGIN, task scheduling should be designed. In this paper, we first present a SAGIN model to reduce the number of satellite attitude adjustment and increase task scheduling time, which is constructed by satellites, Unmanned Aerial Vehicles (UAVs), and ground stations. Then, the scheduling problem in SAGIN is formulated to maximize sum priorities of successfully scheduled tasks under some constrains (e.g., switch time, storage capacity, etc.). After that, an intelligent coordinated scheduling algorithm named APSO-ICSA is proposed with an Adaptive Particle Swarm Optimization (APSO). In APSO-ICSA, three task scheduling processes of collection, storage and transmission are considered jointly for resource interaction, and the global and local search capabilities of particles are adjusted dynamically with adaptive inertia weight. Additionally, a two-criterion resource allocation method is developed for less scheduling conflict, and the scheduling order is determined in virtue of the task priority and deadline. Finally, simulation results show that the proposed APSO-ICSA has superiority both in the sum priority and guarantee ratio.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信