Presentation | 2003/12/12 An Intelligent State-Dependent Routing Scheme for Multicast Traffic PHAM VAN Tien, Yoshiaki TANAKA, |
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Abstract(in Japanese) | (See Japanese page) |
Abstract(in English) | This study introduces Reinforcement Learning (RL) to solve the problem of Call Admission Control (CAC) and Routing for multicast connections in networks serving multiple service classes. The network system is trained to find out the optimal control policy that brings up the highest amount of reward in long-run. For a manageable solution and realizable training time, decomposition is carried out. To demonstrate the prominence of RL-based routing against MOSPF (Multicast extension to Open Shortest Path First) protocol, which is a routing protocol with high performance among available ones, we consider different criteria, including reward rate and call drop rate in simulations. |
Keyword(in Japanese) | (See Japanese page) |
Keyword(in English) | CAC / Routing / Multicast / Reinforcement Learning / Reward |
Paper # | NS2003-211,PN2003-39 |
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Committee | NS |
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Conference Date | 2003/12/12(1days) |
Place (in Japanese) | (See Japanese page) |
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Topics (in Japanese) | (See Japanese page) |
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Paper Information | |
Registration To | Network Systems(NS) |
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Language | ENG |
Title (in Japanese) | (See Japanese page) |
Sub Title (in Japanese) | (See Japanese page) |
Title (in English) | An Intelligent State-Dependent Routing Scheme for Multicast Traffic |
Sub Title (in English) | |
Keyword(1) | CAC |
Keyword(2) | Routing |
Keyword(3) | Multicast |
Keyword(4) | Reinforcement Learning |
Keyword(5) | Reward |
1st Author's Name | PHAM VAN Tien |
1st Author's Affiliation | Global Information and Telecommunication Institute, Waseda University() |
2nd Author's Name | Yoshiaki TANAKA |
2nd Author's Affiliation | Global Information and Telecommunication Institute, Waseda University:Advanced Research Institute for Science and Engineering, Waseda University |
Date | 2003/12/12 |
Paper # | NS2003-211,PN2003-39 |
Volume (vol) | vol.103 |
Number (no) | 506 |
Page | pp.pp.- |
#Pages | 4 |
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