Towards the Development of a Multi-Agent Cognitive Networking System for the Lunar Environment

This paper details the development of a multi-agent cognitive system intended to optimize networking performance in the lunar environment. One concept of the future of lunar communication, LunaNet, outlines a complex network of networks. Challenges such as scalability, interoperability, and reliabil...

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Vydané v:IEEE journal of radio frequency identification (Online) Ročník 6
Hlavní autori: Dudukovich, Rachel, Gormley, Dylan, Kancharla, Shilpa, Wagner, Katherine, Short, Robert, Brooks, David, Fantl, Jason, Janardhanan, Shruti, Fung, Alexander
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Glenn Research Center IEEE 30.03.2022
Predmet:
Cybernetics, Artificial Intelligence And Robotics
Cognitive Radio
Spectrum Sensing
Cross-Layer Optimization
Multi-Agent Reinforcement Learning
Cognitive Networking
Delay Tolerant Networking
ISSN:2469-7281, 2469-729X
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Popis
Shrnutí:This paper details the development of a multi-agent cognitive system intended to optimize networking performance in the lunar environment. One concept of the future of lunar communication, LunaNet, outlines a complex network of networks. Challenges such as scalability, interoperability, and reliability must first be addressed to successfully fulfill this vision. Machine intelligence can greatly reduce the reliance on human operators and enable efficient operations for tasks such as scheduling and network management. Machine learning, artificial intelligence, and other automated decision-making techniques can be used to allow network nodes to intelligently sense and adapt to changes in the environment such as link disruptions, new nodes joining the network, and support for a diverse range of protocols. Cognitive networking seeks to evolve these technologies into an autonomous system with improved science data return, reliability, and scalability. In this paper, we study four main areas as a means to further develop cognitive networking capabilities: networking protocol development, analysis of wireless data for modeling and simulation, development of algorithms for a multi-agent system, and spectrum sensing technology.
Bibliografia:Glenn Research Center
GRC
ISSN:2469-7281
2469-729X
DOI:10.1109/JRFID.2022.3162952