A neural network approach to broadcast scheduling in multi-hop radio networks

Author

Wang, Gangsheng ; Ansari, Nirwan

Author_Institution

Center for Commun. & Signal Process. Res., New Jersey Inst. of Technol., Newark, NJ, USA

Volume

7

fYear

1994

fDate

27 Jun-2 Jul 1994

Firstpage

4699

Abstract

The problem of scheduling interference-free transmissions with maximum throughput in a multi-hop radio network is NP-complete. The computational complexity becomes intractable as the network size increases. In this paper, the scheduling is formulated as a combinatorial optimization problem. An efficient neural network approach, namely, mean field annealing, is applied to obtain optimal transmission schedules. Numerical examples show that this method is capable of finding an interference-free schedule with (almost) optimal throughput

Keywords

combinatorial mathematics; computational complexity; interference (signal); neural nets; optimisation; radio broadcasting; radio networks; scheduling; telecommunication computing; NP-complete; almost optimal throughput; broadcast scheduling; combinatorial optimization problem; computational complexity; interference-free transmissions; maximum throughput; mean field annealing; multi-hop radio networks; network size; neural network approach; optimal transmission schedules; Intelligent networks; Interference; Neural networks; Optimal scheduling; Processor scheduling; Radio broadcasting; Radio network; Radio networks; Spread spectrum communication; Throughput;

fLanguage

English

Publisher

ieee

Conference_Titel

Neural Networks, 1994. IEEE World Congress on Computational Intelligence., 1994 IEEE International Conference on

Conference_Location

Orlando, FL

Print_ISBN

0-7803-1901-X

Type

conf

DOI

10.1109/ICNN.1994.375035

Filename

375035