2005 Special Issue: Broadcast scheduling in wireless multihop networks using a neural-network-based hybrid algorithm

Authors:
Haixiang Shi;Lipo Wang
Affiliations:
Software Engineering Laboratory, School of Electrical & Electronic Engineering, Nanyang Technological University, S2.2-B4-04, 50 Nanyang Avenue, 639798, Singapore;Software Engineering Laboratory, School of Electrical & Electronic Engineering, Nanyang Technological University, S2.2-B4-04, 50 Nanyang Avenue, 639798, Singapore
Venue:
Neural Networks - 2005 Special issue: IJCNN 2005
Year:
2005

Citing 5
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An evolutionary algorithm for broadcast scheduling in wireless multihop networks

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Abstract

In wireless multihop networks, the objective of the broadcast scheduling problem is to find a conflict free transmission schedule for each node at different time slots in a fixed length time cycle, called TDMA cycle. The optimization criterion is to find an optimal TDMA schedule with minimal TDMA cycle length and maximal node transmissions. In this paper we propose a two-stage hybrid method to solve this broadcast scheduling problem in wireless multihop networks. In the first stage, we use a sequential vertex-coloring algorithm to obtain a minimal TDMA frame length. In the second stage, we apply the noisy chaotic neural network to find the maximum node transmission based on the results obtained in the previous stage. Simulation results show that this hybrid method outperforms previous approaches, such as mean field annealing, a hybrid of the Hopfield neural network and genetic algorithms, the sequential vertex coloring algorithm, and the gradual neural network.