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Broadcast scheduling in packet radio networks by Hopfield neural networks

✍ Scribed by Wei Li-Chiun; Ruay-Shiung Chang

Publisher: Elsevier Science
Year: 1997
Tongue: English
Weight: 363 KB
Volume: 63
Category: Article
ISSN: 0020-0190
DOI: 10.1016/s0020-0190(97)00108-7

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✦ Synopsis

A multihop packet radio network is a packet switching network where nodes communicate by radio signals. When used in real-time multimedia or military communication networks, it is very important to broadcast a packet from a source node to all other nodes as quickly as possible. Unfortunately, the problem of finding an optimal schedule to minimize the time needed to complete the broadcast for a general multihop packet radio network is NP-complete. We propose a Hopfield neural network solution for one-source-node broadcasting in a multihop packet radio network. The proposed neural network model always finds a good solution by trying to maximize the number of correctly receiving nodes in every time slot. Experiments indicate good results. The model requires n processing elements (neurons) for an n-node radio network.

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