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Riverbed Modeler Reinforcement Learning MS Framework Supported by Supervised Learning
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Publication Year
2021-01-13
Journal
International Conference on Information Networking
Publisher
IEEE Computer Society
Citation
International Conference on Information Networking, Vol.2021-January, pp.824-827
Keyword
learning efficiencynetwork simulatorreinforcement learningriverbed modeler
Mesh Keyword
Learning timeNetwork domainsNetwork models
All Science Classification Codes (ASJC)
Computer Networks and CommunicationsInformation Systems
Abstract
Riverbed Modeler is a useful simulation tool that can simulate a variety of standard network models. However, it does not provide a related tool that does not suit the situation in which research on applying machine learning to the network domain is actively progressing. In this paper, we implemented a framework to apply reinforcement learning in a riverbed modeler environment. In order to efficiently perform reinforcement learning, we proposed a reinforcement learning structure that supports supervised learning to improve network performance using Riverbed Modeler and MATLAB. The proposed method was evaluated that the learning time was shortened compared to the existing reinforcement learning environment through experiments.
ISSN
1976-7684
Language
eng
URI
https://aurora.ajou.ac.kr/handle/2018.oak/36690
https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85100704068&origin=inward
DOI
https://doi.org/10.1109/icoin50884.2021.9333963
Journal URL
http://www.icoin.org/
Type
Conference
Funding
Riverbed Modeler Reinforcement Learning M&S Framework Supported by Supervised Learning
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Roh, Byeong-hee Image
Roh, Byeong-hee노병희
Department of Software and Computer Engineering
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