A packet routing strategy using neural networks on scale-free networks
抄録
We propose a dynamic packet routing strategy by using neural networks on scale-free networks. In this strategy, in order to determine the nodes to which the packets should be transmitted, we use path lengths to the destinations of the packets, and adjust the connection weights of the neural networks attached to the nodes from local information and the path lengths. The performances of this strategy on scale-free networks which have the same degree distribution and different degree correlations are compared to one another. Our numerical simulations confirm that this routing strategy is more effective than the shortest path based strategy on scale-free networks with any degree correlations and that the performance of our strategy on assortative scale-free networks is better than that on disassortative and uncorrelated scale-free networks.
収録刊行物
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- Physica A: Statistical Mechanics and its Applications
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Physica A: Statistical Mechanics and its Applications 389 (3), 623-628, 2010-02
Elsevier
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詳細情報 詳細情報について
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- CRID
- 1050001202110952576
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- NII論文ID
- 120001700244
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- ISSN
- 03784371
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- HANDLE
- 2433/87417
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- 本文言語コード
- en
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- 資料種別
- journal article
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- データソース種別
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- IRDB
- CiNii Articles