一种面向空间信息网络的星地协同计算迁移方法
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摘要
面向空间平台构建星地一体化的空间信息网络近年来成为信息网络建设的热点。传统的信息网络建设趋于流量驱动,以满足节点间的通信需求为主。空间信息网络的建设更着重于以应用业务中的任务为向导,牵引从通信资源到计算、存储资源的优化重组与协同服务。如何在应用任务与有限网络资源间形成联动机制,有效解决星上遥感数据存储、处理与传输能力受限的问题,是实现空间信息网络高效数据处理的关键技术问题。针对遥感数据星地协同处理的机制,在任务驱动的空间信息网络体系架构基础上,提出一种面向空间信息网络的星地协同计算迁移方法,建立了计算迁移的优化模型,提出了计算迁移的实现技术,通过案例仿真结果与分析,验证了该方法的可行性。
Recent years, orienting space platform to construct satellite-ground integrative spatial information network has become a hot topic of information network construction. Conventional information network construction tends to be flow driven to meet the communication requirement between nodes. The construction of spatial information network focuses more on taking tasks in the application business as guide, and pulls from communication resources to optimal recombination and cooperative ser-vice of computing and storage resources. How to form linkage mechanism between application tasks and limited network resources, which can effectively solve the capacity constrained problems of remote sensing data storage, processing and transmission, is the key technical problem to realize the efficient data processing in spatial information network. According to the mechanism of satellite-ground collaborative remote sensing data processing, based on the task driven spatial information network architecture, an approach of spatial information network oriented satellite-ground collaborative computing migration is presented. We build an optimization model of computing migration, propose the implementation technique of computing migration and verify the feasibility of the approach through results analysis of the simulation case.
Recent years, orienting space platform to construct satellite-ground integrative spatial information network has become a hot topic of information network construction. Conventional information network construction tends to be flow driven to meet the communication requirement between nodes. The construction of spatial information network focuses more on taking tasks in the application business as guide, and pulls from communication resources to optimal recombination and cooperative ser-vice of computing and storage resources. How to form linkage mechanism between application tasks and limited network resources, which can effectively solve the capacity constrained problems of remote sensing data storage, processing and transmission, is the key technical problem to realize the efficient data processing in spatial information network. According to the mechanism of satellite-ground collaborative remote sensing data processing, based on the task driven spatial information network architecture, an approach of spatial information network oriented satellite-ground collaborative computing migration is presented. We build an optimization model of computing migration, propose the implementation technique of computing migration and verify the feasibility of the approach through results analysis of the simulation case.
引文
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[2] Li Deren, Shen Xin, Li Dilong, et al. On Civil-Mili-tary Integrated Space-Based Real-Time Information Service System[J]. Geomatics and Information Science of Wuhan University, 2017, 42(11): 1 501-1 505(李德仁, 沈欣, 李迪龙, 等. 论军民融合的卫星通信、遥感、导航一体天基信息实时服务系统[J]. 武汉大学学报·信息科学版, 2017, 42(11): 1 501-1 505)
[3] Li Deren, Wang Mi, Shen Xin, et al. From Earth Observation Satellite to Earth Observation Brain[J]. Geomatics and Information Science of Wuhan University, 2017, 42(2): 143-149(李德仁, 王密, 沈欣, 等. 从对地观测卫星到对地观测脑[J]. 武汉大学学报·信息科学版,2017, 42(2): 143-149)
[4] He You, Yao Libo. Space-Based Sea Target Information Awareness and Fusion[J]. Geomatics and Information Science of Wuhan University, 2017, 42(11):1 530-1 536(何友, 姚力波. 天基海洋目标信息感知与融合技术研究[J]. 武汉大学学报·信息科学版,2017, 42(11): 1 530-1 536)
[5] Li Deren, Shen Xin, Gong Jianya, et al. On Constraction of China’s Space Information Network[J]. Geomatics and Information Science of Wuhan University, 2015, 40(6): 711-715(李德仁, 沈欣, 龚健雅, 等. 论中国空间信息网络的构建[J]. 武汉大学学报·信息科学版,2015, 40(6): 711-715)
[6] Pan Chengsheng. Several Key Technologies of Spatial Information Network[J]. Communications of CCF, 2013, 9(4): 46-51(潘成胜. 空间信息网络的若干关键技术[J]. 中国计算机学会通信, 2013, 9(4): 46-51)
[7] Gavras A, Karila A, Fdida S, et al. Future Internet Research and Experimentation: The FIRE Initiative[J]. ACM SIGCOMM Computer Communication Review, 2007, 37(3): 89-92
[8] Reinhart R C, Kacpura T J, Johnson S K, et al. NASA’s Space Communications and Navigation Test Bed Aboard the International Space Station[J]. IEEE Aerospace and Electronic Systems Magazine, 2013, 28(4): 4-15
[9] Wang Sai, Deng Fuxing, Cheng Zijing, et al. Analy-sis of Routing Algorithm for Space Delay/Disruption Tolerant Network[J]. Geomatics and Information Science of Wuhan University, 2015, 40(10): 1 312-1 316(王赛, 邓福兴, 程子敬, 等. 面向空间延迟可容忍网络的路由协议仿真研究[J]. 武汉大学学报·信息科学版,2015, 40(10): 1 312-1 316)
[10] Yan Hongcheng, Zhang Qingjun, Sun Yong. Routing Performance Evaluation in Navigation Constellation Network Based on Contact Graph Routing[C]. China Satellite Navigation Conference, Beijing, China, 2014(燕洪成, 张庆君, 孙勇. 基于连接图路由算法的导航星座网络路由性能研究[C]. 中国卫星导航学术年会, 北京,2014)
[11] Schut P. OGC 05-007r7, OpenGIS Web Processing Service[R]. Open Geospatial Consortium, Wayland, MA, USA,2007
[12] Baumann P. OGC 08–068r2, OGC Web Coverage Processing Service (WCPS) Language Interface Standard[R]. Open Geospatial Consortium, Wayland, MA, USA,2009
[13] Whiteside A, Evans J D. OGC 07-067r5, Web Cove-rage Service (WCS) Implementation Standard[R]. Open Geospatial Consortium, Wayland, MA, USA,2008
[14] Baumann P. The OGC Web Coverage Processing Service (WCPS) Standard[J]. GeoInformatica, 2010, 14(4): 447-479
[15] Baumann P, Dehmel A, Furtado P, et al. The Multi-dimensional Database System RasDaMan[C]. The 1998 ACM SIGMOD International Conference on Management of Data, Seattle, Washington, USA, 1998
[16] Ker?nen A, Ott J, K?rkk?inen T. The ONE Simulator for DTN Protocol Evaluation[C]. The 2nd International Conference on Simulation Tools and Techniques, Rome, Italy, 2009
[17] Evans D, Merri M. OPS-SAT: An ESA Nanosatellite for Accelerating Innovation in Satellite Control[C]. SpaceOps Conference, Pasadena, California, USA, 2014
[18] Baumann P, Dumitru A, Merticariu V, et al. Breaking the Big Data Barrier by Enhancing On-board Sensor Flexibility[C]. The 2nd ACM SIGSPATIAL International Workshop on Analytics for Big Geospatial Data, Orlando, Florida, USA, 2013