A binary neural network approach for one-shot scheduling problems in multicast packet switching systems

T. Baba, N. Funabiki, S. Nishikawa

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

1 Citation (Scopus)

Abstract

A multicast packet switching system can replicate a packet in the window of each input port to send out the copies from different output ports simultaneously. In order to maximize the throughput, a combinatorial optimization problem must be solved in real time of finding a switching configuration which does not only satisfy the constraints on the system, but also maximizes the number of copies under transmission demands. In this paper, we focus on the one-shot scheduling problem where all the copies of selected packets must be sent out simultaneously. We propose the neural network composed of W×N binary neurons for the problem in the W-window-N-input-port system. The motion equation is newly defined with three heuristic methods. We verify the performance through simulations in up to 3-window-1000-input-port systems, where our binary neural network provides the better performance than the existing methods so as to reduce the delay time under practical situations.

Original languageEnglish
Title of host publication1997 IEEE International Conference on Neural Networks, ICNN 1997
Pages1266-1271
Number of pages6
DOIs
Publication statusPublished - Dec 1 1997
Externally publishedYes
Event1997 IEEE International Conference on Neural Networks, ICNN 1997 - Houston, TX, United States
Duration: Jun 9 1997Jun 12 1997

Publication series

NameIEEE International Conference on Neural Networks - Conference Proceedings
Volume2
ISSN (Print)1098-7576

Conference

Conference1997 IEEE International Conference on Neural Networks, ICNN 1997
CountryUnited States
CityHouston, TX
Period6/9/976/12/97

ASJC Scopus subject areas

  • Software

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    Baba, T., Funabiki, N., & Nishikawa, S. (1997). A binary neural network approach for one-shot scheduling problems in multicast packet switching systems. In 1997 IEEE International Conference on Neural Networks, ICNN 1997 (pp. 1266-1271). [616216] (IEEE International Conference on Neural Networks - Conference Proceedings; Vol. 2). https://doi.org/10.1109/ICNN.1997.616216