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复杂系统与复杂性科学  2024, Vol. 21 Issue (1): 51-57    DOI: 10.13306/j.1672-3813.2024.01.007
  复杂网络 本期目录 | 过刊浏览 | 高级检索 |
基于含时网络数据的卫星网络模体识别方法研究
胡博仁a, 裴忠民a, 罗章凯a, 丁杰b
航天工程大学 a. 复杂电子系统仿真重点实验室; b.电子与光学工程系,北京 101416
On Motif Counts Method of Satellite Network Based on Temporal Network Data
HU Borena, PEI Zhongmina, LUO Zhangkaia, DING Jieb
a. Science and Technology on Complex Electronic System Simulation Laboratory; b. Department of Electronics and Optical Engineering, Space Engineering University, Beijing 101416,China
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摘要 鉴于开展卫星网络局部结构研究是理解网络性质的重要手段,考虑星间链路天线可见性约束等条件,提出了一种基于含时网络数据的卫星网络模体识别方法,建立了从TLE文件输入到子结构识别输出的模体识别流程。以GPS卫星网络的三节点三边模体识别为例,结果发现在短时段内卫星天线最大扫描范围与具有特殊结构意义的三角形M4子图浓度呈正相关。
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胡博仁
裴忠民
罗章凯
丁杰
关键词 卫星网络模体识别子图浓度    
Abstract:Conducting research on the local structure of satellite networks is an important means to understand the nature of networks. Considering the visibility constraints of inter-satellite link antennas, a satellite network motif counts method based on temporal network data is proposed, and a motif counts process is established from TLE file input to substructure identification output; taking the three-node three-edge motif counts of GPS satellite network as an example, we found that in a short period of time maximum scanning range of the satellite antenna was positively correlated with the concentration of the triangular M4 subgraph with special structural significance.
Key wordssatellite network    motif counts    subgraph concentration
收稿日期: 2022-04-07      出版日期: 2024-04-26
ZTFLH:  TP393  
  TP399  
基金资助:复杂电子系统仿真重点实验室基础研究项目(DXZT-JC-ZZ-2020-001)
通讯作者: 裴忠民(1976-),男,山东济宁人,博士,副研究员,主要研究方向为计算机科学与技术、系统科学。   
作者简介: 胡博仁(1999-),男,湖南宁乡人,硕士研究生,主要研究方向为复杂网络、系统科学。
引用本文:   
胡博仁, 裴忠民, 罗章凯, 丁杰. 基于含时网络数据的卫星网络模体识别方法研究[J]. 复杂系统与复杂性科学, 2024, 21(1): 51-57.
HU Boren, PEI Zhongmin, LUO Zhangkai, DING Jie. On Motif Counts Method of Satellite Network Based on Temporal Network Data[J]. Complex Systems and Complexity Science, 2024, 21(1): 51-57.
链接本文:  
https://fzkx.qdu.edu.cn/CN/10.13306/j.1672-3813.2024.01.007      或      https://fzkx.qdu.edu.cn/CN/Y2024/V21/I1/51
[1] 武健,刘新学,舒健生,等. 基于复杂网络的卫星重要度评估[J]. 火力与指挥控制, 2014, 39(5): 60-63.
WU J, LIU X X, SHU J S, et al. Satellite significance assessment based on complex network[J]. Fire Power and Command Control, 2014, 39(5): 60-63.
[2] 朱林,方胜良,胡卿,等.卫星时变拓扑网络节点重要度评估方法[J].系统工程与电子技术,2017,39(6):1274-1279.
ZHU L, FANG S L, HU Q, et al. Evaluation method of node significance of satellite time-varying topology network[J]. System Engineering and ElectronicTechnology,2017,39(6):1274-1279.
[3] 王莹.卫星移动通信网若干理论和技术研究[D].武汉:华中科技大学,2008.
WANG Y.Research on theoretical and technical of satellite mobile communication network[D]. Wuhan: Huazhong University of Science and Technology,2008.
[4] 林琪,李智.基于拓扑特征的卫星网络效能评估[J].中南大学学报(自然科学版),2013,44(S2):368-371.
LIN Q, LI Z. Evaluation of Satellite network performance based on topological characteristics[J]. Journal of Central South University(Natural Science Edition),2013,44(S-2):368-371.
[5] MILO R, SHEN-ORR S, ITZKOVITZ N,et al. Network motifs:simple building blocks of complex networks[J]. Science, 298(5594):824-827.
[6] CASALS M R, Corominas-Murtra B. Assessing european power grid reliability by means of topological measures[J]. OAI, 2009,121:527-537.
[7] PAUL S, JOBST H, KURTHS J,et al. Detours around basin stability in power networks[J].New Journal of Physics,2014,16(12):125001.
[8] 孙晓伟. 基于网络模体的科学学数据研究[D].成都:电子科技大学,2019.
SUN X W. Scientific data research based on networkmotif[D]. Chengdu: University of Electronic Science and Technology of China,2019.
[9] 高贺. 北斗导航系统星间链路分配方法研究[D].湖南:湖南大学,2018.
GAO H. Research on inter-satellite link allocation method of BDS[D]. Hunan: Hunan University,2018.
[10] 辜姣,郭龙,江健,等.多层网络和含时网络的相关问题研究[J].复杂系统与复杂性科学,2016,13(1):58-63,67.
GU J, GUO L, JIANG J, et al. Research on related problems of multilayer networks andtemporal networks[J]. Complex Systems and Complexity Science,2016,13(1):58-63,67.
[11] HOLME P, SARAMÄKI J. Temporal networks[J]. Physics Reports, 2012, 519(3):97-125.
[12] 覃桂敏.复杂网络模式挖掘算法研究[D]. 西安:西安电子科技大学, 2013.
QIN G M. Research on complex network pattern mining algorithm[D]. Xi'an: Xidian University, 2013.
[13] KASHTAN N, ITZKOVITZ S, MILO R, et al. Efficient sampling algorithm for estimating subgraph concentrations and detecting network motifs.[J]. Bioinformatics,2004,20(11):1746-1758.
[14] WERNICKE S, RASCHE F. FANMOD: a tool for fast network motif detection[J]. Bioinformatics,2006,22(9):1152-1153.
[15] SAEED O, FALK S, MASOUDI-NEJAD, et al. MODA: an efficient algorithm for network motif discovery in biological networks[J]. Genes & Genetic Systems,2009,84(5):385-395.
[16] TIEN H, SOMADINA M, KIM W, et al. NemoMap improved motifcentric network motif discovery algorithm[J]. Advances in Science, Technology and Engineering Systems,2018,3(5):186-199.
[17] SCHILLER B, JAGER S, HAMACHER K, et al. Strea m-a stream-based algorithm for counting motifs in dynamic graphs[C]// International Conference on Algorithms for Computational Biology. Mexico: Springer, Cham, 2015.
[18] EDIGER D, JIANG K, RIEDY J, et al. Massive streaming data analytics: a case study with clustering coefficients[C]// IEEE International Symposium on Parallel & Distributed Processing. Atlanta, Georgia, USA: IEEE, 2010.
[19] ASHWIN P, AUSTIN R B, JURE L. Motifs in temporal-networks[J].CoRR,2016,abs/1612.09259.
[20] SARPE I, VANDIN F. odeN: simultaneous approximation of multiple motif counts in large temporal networks[C]. Proceedings of the 30th ACM International Conference on Information & Knowledge Management, Virtual Event. Queensland, Australia: 2021: 1568-1577.
[21] 刘天雄.GPS全球定位系统由几部分组成?[J].卫星与网络,2012(4):56-62.
LIU T X. How many parts does GPS system consist of? [J]. Satellite and Network,2012(4):56-62.
[22] 李朝瑞,孟新. 星座仿真中天线扫描范围对系统的影响分析[C]//中国空间科学学会空间探测专业委员会第十九次学术会议论文集(下册).宁波, 2006,2:433-437.
LI C R, MENG X. Analysis of the influence of antenna scanning range on the system in constellation simulation[C]//Proceedings of the 19th Academic Conference of the Space Exploration Professional Committee of the Chinese Society of Space Sciences 2. Ningbo, 2006, 2: 433-437.
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