Title :
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
fDate :
27 Jun-2 Jul 1994
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;
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
DOI :
10.1109/ICNN.1994.375035
