Time cumulative complexity modeling and analysis for space-based networks

Du, Jun, Jiang, Chunxiao, Yu, Shui and Ren, Yong 2016, Time cumulative complexity modeling and analysis for space-based networks, in ICC 2016 : Proceedings of the 2016 IEEE International Conference on Communications, IEEE, Piscataway, N. J., pp. 1-6, doi: 10.1109/ICC.2016.7511259.

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Title Time cumulative complexity modeling and analysis for space-based networks
Author(s) Du, Jun
Jiang, Chunxiao
Yu, ShuiORCID iD for Yu, Shui orcid.org/0000-0003-4485-6743
Ren, Yong
Conference name IEEE Communications. Conference (2016 : Kuala Lumper, Malaysia)
Conference location Kuala Lumpur, Malaysia
Conference dates 22- 27 May. 2016
Title of proceedings ICC 2016 : Proceedings of the 2016 IEEE International Conference on Communications
Publication date 2016
Conference series IEEE Conference
Start page 1
End page 6
Total pages 6
Publisher IEEE
Place of publication Piscataway, N. J.
Keyword(s) satellites
satellite broadcasting
topology
complexity theory
orbits
vehicle dynamics
Summary In this paper, the notion of the cumulative time varying graph (C-TVG) is proposed to model the high dynamics and relationships between ordered static graph sequences for space-based information networks (SBINs). In order to improve the performance of management and control of the SBIN, the complexity and social properties of the SBIN's high dynamic topology during a period of time is investigated based on the proposed C-TVG. Moreover, a cumulative topology generation algorithm is designed to establish the topology evolution of the SBIN, which supports the C-TVG based complexity analysis and reduces network congestions and collisions resulting from traditional link establishment mechanisms between satellites. Simulations test the social properties of the SBIN cumulative topology generated through the proposed C-TVG algorithm. Results indicate that through the C-TVG based analysis, more complexity properties of the SBIN can be revealed than the topology analysis without time cumulation. In addition, the application of attack on the SBIN is simulated, and results indicate the validity and effectiveness of the proposed C-TVG and C-TVG based complexity analysis for the SBIN.
ISBN 9781479966646
Language eng
DOI 10.1109/ICC.2016.7511259
Field of Research 080109 Pattern Recognition and Data Mining
080503 Networking and Communications
Socio Economic Objective 970108 Expanding Knowledge in the Information and Computing Sciences
HERDC Research category E1 Full written paper - refereed
ERA Research output type E Conference publication
Copyright notice ©2016, IEEE
Persistent URL http://hdl.handle.net/10536/DRO/DU:30086206

Document type: Conference Paper
Collections: School of Information Technology
2018 ERA Submission
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