Intelligent CAC and routing for multi-point connections

Pham Van Tien, Franz Rammig, Yoshiaki Tanaka

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This study introduces Reinforcement Learning (RL) to solve the problem of Cull Admission Control (CAC)&Routing for multi-point connections in networks serving multiple service classes. The network system is trained to find out the optimal control policy which brings up the highest amount of reward in long-run. For a manageable solution and realizable training time, decomposition of network and connections into link level is implemented. To demonstrate the prominence of RL-based routing against MOSPF (Multicast extension to Open Shortest Path First) protocol, a routing protocol with high performance among available ones, we consider different criteria, including reward rate, call drop rate, and link usage rate.

Original languageEnglish
Title of host publicationProceedings of the International Conference on Communications in Computing, CIC'04
EditorsB.J. d'Auriol
Pages194-200
Number of pages7
Publication statusPublished - 2004
EventProceedings of the International Conference on Communications in Computing, CIC'04 - Las Vegas, NV, United States
Duration: 2004 Jun 212004 Jun 24

Publication series

NameProceedings of the International Conference on Communications in Computing, CIC'04

Conference

ConferenceProceedings of the International Conference on Communications in Computing, CIC'04
CountryUnited States
CityLas Vegas, NV
Period04/6/2104/6/24

Keywords

  • CAC
  • Multi-point connection
  • Reinforcement learning
  • Reward
  • Routing

ASJC Scopus subject areas

  • Engineering(all)

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  • Cite this

    Van Tien, P., Rammig, F., & Tanaka, Y. (2004). Intelligent CAC and routing for multi-point connections. In B. J. d'Auriol (Ed.), Proceedings of the International Conference on Communications in Computing, CIC'04 (pp. 194-200). (Proceedings of the International Conference on Communications in Computing, CIC'04).