ATM connection admission control using pRAM based artificial neural networks
As they learn from observed data, neural networks have found many applications in communication networks. Here, a neural network for connection admission control (CAC) based on the probabilistic-RAM (pRAM) neuron model is presented. Because pRAM neural networks can be implemented in hardware easily...
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Veröffentlicht in: | Computer networks (Amsterdam, Netherlands : 1999) Netherlands : 1999), 2000-07, Vol.34 (1), p.49-63 |
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Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | As they learn from observed data, neural networks have found many applications in communication networks. Here, a neural network for connection admission control (CAC) based on the probabilistic-RAM (pRAM) neuron model is presented. Because pRAM neural networks can be implemented in hardware easily and at a low cost, they make excellent controllers in the ATM environment. The performance of such a controller is analysed through simulations, and the results are compared with the Equivalent Capacity of Connections CAC algorithm. The results show that, the proposed hardware-based controller guarantees the required quality of service (QoS) and at the same time provides an improvement in network utilization. |
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ISSN: | 1389-1286 1872-7069 |
DOI: | 10.1016/S1389-1286(00)00096-7 |