A neural network approach to broadcasting in multihop packet radio networks

Nobuo Funabiki; Yoshiyasu Takefuji; Kuo Chun Lee; Yong Beom Cho; Takakazu Kurokawa; Hideo Aiso

A neural network approach to broadcasting in multihop packet radio networks

Nobuo Funabiki, Yoshiyasu Takefuji, Kuo Chun Lee, Yong Beom Cho, Takakazu Kurokawa, Hideo Aiso

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

A neural network model for broadcasting scheduling in multihop packet radio networks is presented. The problem of broadcast scheduling with a minimum number of time slots is NP-complete. The proposed neural network model finds a broadcasting schedule with a minimal number of time slots where it requires n processing elements for an n-node radio network. Fifteen different radio networks were examined where the neural network model found an m-time-slot solution in O(m) time with n processors.

Original language	English
Title of host publication	91 IEEE Int Jt Conf Neural Networks IJCNN 91
Publisher	Publ by IEEE
Pages	2540-2545
Number of pages	6
ISBN (Print)	0780302273
Publication status	Published - 1991
Externally published	Yes
Event	1991 IEEE International Joint Conference on Neural Networks - IJCNN '91 - Singapore, Singapore Duration: 1991 Nov 18 → 1991 Nov 21

Publication series

Name	91 IEEE Int Jt Conf Neural Networks IJCNN 91

Other

Other	1991 IEEE International Joint Conference on Neural Networks - IJCNN '91
City	Singapore, Singapore
Period	91/11/18 → 91/11/21

ASJC Scopus subject areas

Engineering(all)

Cite this

Funabiki, N, Takefuji, Y, Lee, KC, Cho, YB, Kurokawa, T & Aiso, H 1991, A neural network approach to broadcasting in multihop packet radio networks. in 91 IEEE Int Jt Conf Neural Networks IJCNN 91. 91 IEEE Int Jt Conf Neural Networks IJCNN 91, Publ by IEEE, pp. 2540-2545, 1991 IEEE International Joint Conference on Neural Networks - IJCNN '91, Singapore, Singapore, 91/11/18.

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title = "A neural network approach to broadcasting in multihop packet radio networks",

abstract = "A neural network model for broadcasting scheduling in multihop packet radio networks is presented. The problem of broadcast scheduling with a minimum number of time slots is NP-complete. The proposed neural network model finds a broadcasting schedule with a minimal number of time slots where it requires n processing elements for an n-node radio network. Fifteen different radio networks were examined where the neural network model found an m-time-slot solution in O(m) time with n processors.",

author = "Nobuo Funabiki and Yoshiyasu Takefuji and Lee, {Kuo Chun} and Cho, {Yong Beom} and Takakazu Kurokawa and Hideo Aiso",

year = "1991",

language = "English",

isbn = "0780302273",

series = "91 IEEE Int Jt Conf Neural Networks IJCNN 91",

publisher = "Publ by IEEE",

pages = "2540--2545",

booktitle = "91 IEEE Int Jt Conf Neural Networks IJCNN 91",

note = "1991 IEEE International Joint Conference on Neural Networks - IJCNN '91 ; Conference date: 18-11-1991 Through 21-11-1991",

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AU - Funabiki, Nobuo

AU - Takefuji, Yoshiyasu

AU - Lee, Kuo Chun

AU - Cho, Yong Beom

AU - Kurokawa, Takakazu

AU - Aiso, Hideo

PY - 1991

Y1 - 1991

N2 - A neural network model for broadcasting scheduling in multihop packet radio networks is presented. The problem of broadcast scheduling with a minimum number of time slots is NP-complete. The proposed neural network model finds a broadcasting schedule with a minimal number of time slots where it requires n processing elements for an n-node radio network. Fifteen different radio networks were examined where the neural network model found an m-time-slot solution in O(m) time with n processors.

AB - A neural network model for broadcasting scheduling in multihop packet radio networks is presented. The problem of broadcast scheduling with a minimum number of time slots is NP-complete. The proposed neural network model finds a broadcasting schedule with a minimal number of time slots where it requires n processing elements for an n-node radio network. Fifteen different radio networks were examined where the neural network model found an m-time-slot solution in O(m) time with n processors.

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M3 - Conference contribution

AN - SCOPUS:0026264271

SN - 0780302273

T3 - 91 IEEE Int Jt Conf Neural Networks IJCNN 91

SP - 2540

EP - 2545

BT - 91 IEEE Int Jt Conf Neural Networks IJCNN 91

PB - Publ by IEEE

T2 - 1991 IEEE International Joint Conference on Neural Networks - IJCNN '91

Y2 - 18 November 1991 through 21 November 1991

ER -

A neural network approach to broadcasting in multihop packet radio networks

Abstract

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