Prediction and control of short-term congestion in ATM networks using artificial intelligence techniques

Producció científica: Capítol de llibreContribució a congrés/conferènciaAvaluat per experts

3 Cites (Scopus)


Nowadays high-speed transmissions and heterogeneous traffic are some of the most essential requirements that a communication network must satisfy. Therefore, the design and management of such networks must consider these requirements. Network congestion is a very important point that must be taken into consideration when a management system is designed. ATM networks support different types of services and this fact makes them less predictable networks. Congestion can be defined as a state of network elements in which the network cannot guarantee the established connections the negotiated QoS. This paper proposes a system to reduce short-term congestion in ATM networks. This system uses Artificial Intelligence techniques to predict future states of network congestion in order to take less drastic measures in advance.

Idioma originalAnglès
Títol de la publicacióNetworking - ICN 2001 - 1st International Conference on Networking, Proceedings
EditorsPascal Lorenz
EditorSpringer Verlag
Nombre de pàgines10
ISBN (electrònic)3540423036, 9783540423034
Estat de la publicacióPublicada - 2001
Esdeveniment1st International Conference on Networking, ICN 2001 - Colmar, France
Durada: 9 de jul. 200113 de jul. 2001

Sèrie de publicacions

NomLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
ISSN (imprès)0302-9743
ISSN (electrònic)1611-3349


Conferència1st International Conference on Networking, ICN 2001


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