{"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}
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.