ATM call control by neural networks

• Autor(es): Neves, Joaquim E. ; Almeida, Luís B. ; Leitão, Mário J.
• Data: 1993
• Identificador Persistente: http://hdl.handle.net/1822/2174
• Origem: RepositóriUM - Universidade do Minho
• Assunto(s): ATM call control; Traffic prediction
• Tipo de Documento: Documento de conferência
• Idioma: Inglês

Descrição

The resource allocation in the Broadband Integrated Services Digital Network (B-ISDN) must guarantee the quality of service negotiated with new and existing calls, taking into account the Asynchronous Transfer Mode (ATM) statistical characteristics. A quality of operation function, characterizing the overall network performance, is proposed, and based on this function, it is introduced a new strategy for the admission control and routing of the ATM call connections. As it is shown by simulation results, feedforword Neural Networks trained with the backpropagation algorithm, can learn the traffic patterns in previous traffic situations, and can be used to predict the quality of operation changes caused by each new call.