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Evaluation of Classifier Complexity for Delay Tolerant Network RoutingThe growing popularity of small cost effective satellites (SmallSats, CubeSats, etc.) creates the potential for a variety of new science applications involving multiple nodes functioning together or independently to achieve a task, such as swarms and constellations. As this technology develops and is deployed for missions in Low Earth Orbit and beyond, the use of delay tolerant networking (DTN) techniques may improve communication capabilities within the network. In this paper, a network hierarchy is developed from heterogeneous networks of SmallSats, surface vehicles, relay satellites and ground stations which form an integrated network. There is a tradeoff between complexity, flexibility, and scalability of user defined schedules versus autonomous routing as the number of nodes in the network increases. To address these issues, this work proposes a machine learning classifier based on DTN routing metrics. A framework is developed which will allow for the use of several categories of machine learning algorithms (decision tree, random forest and deep learning) to be applied to a dataset of historical network statistics, which allows for the evaluation of algorithm complexity versus performance to be explored. We develop the emulation of a hierarchical network, consisting of tens of nodes which form a cognitive network architecture. CORE (Common Open Research Emulator) is used to emulate the network using bundle protocol and DTN IP neighbor discovery.
Document ID
20190027070
Acquisition Source
Glenn Research Center
Document Type
Conference Paper
Authors
Dudukovich, Rachel
(NASA Glenn Research Center Cleveland, OH, United States)
Clark, Gilbert
(NASA Glenn Research Center Cleveland, OH, United States)
Papachristou, Christos
(Case Western Reserve Univ. Cleveland, OH, United States)
Date Acquired
July 9, 2019
Publication Date
June 25, 2019
Subject Category
Space Communications, Spacecraft Communications, Command And Tracking
Report/Patent Number
GRC-E-DAA-TN67967
Meeting Information
Meeting: IEEE Cognitive Communications for Aerospace Applications Workshop
Location: Cleveland, OH
Country: United States
Start Date: June 25, 2019
End Date: June 26, 2019
Sponsors: Institute of Electrical and Electronics Engineers
Funding Number(s)
WBS: 277985.04.05.03.01
Distribution Limits
Public
Copyright
Public Use Permitted.
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