In modern satellite communication systems, the quality of service (QoS) management has became a crucial topic due to the increasing interest in multimedia traffic. The actual trends consider the satellite networks as an integrated part of the terrestrial data networks. In IP networks, the differentiated service (DiffServ) approach seems to be the best that satisfies the QoS constraints, due to its end-to-end philosophy. Actual trend considers the satellite on-board switching capabilities for managing multibeam inputs and outputs. In particular this paper deals with the proposal of a new cellular neural network (CNN) for the on-board switching problem to reduce the computational complexity; several traffic classes, according to the DiffServ approach, have been considered and the switch takes into account their priority, queue length and time spent inside queues. Numerical results have shown that the performance is similar to the optimal switching solution of the flexible cellular neural network. Simulation results have been driven with a memoryless distribution and heavy-tailed distribution for several input buffer size and switch dimension.

R. Fantacci, R. Gubellini, D. Tarchi, T. Pecorella (2004). DiffServ on-board satellite switching based on cellular neural networks. s.l : IEEE [10.1109/ICC.2004.1313293].

DiffServ on-board satellite switching based on cellular neural networks

TARCHI, DANIELE;
2004

Abstract

In modern satellite communication systems, the quality of service (QoS) management has became a crucial topic due to the increasing interest in multimedia traffic. The actual trends consider the satellite networks as an integrated part of the terrestrial data networks. In IP networks, the differentiated service (DiffServ) approach seems to be the best that satisfies the QoS constraints, due to its end-to-end philosophy. Actual trend considers the satellite on-board switching capabilities for managing multibeam inputs and outputs. In particular this paper deals with the proposal of a new cellular neural network (CNN) for the on-board switching problem to reduce the computational complexity; several traffic classes, according to the DiffServ approach, have been considered and the switch takes into account their priority, queue length and time spent inside queues. Numerical results have shown that the performance is similar to the optimal switching solution of the flexible cellular neural network. Simulation results have been driven with a memoryless distribution and heavy-tailed distribution for several input buffer size and switch dimension.
2004
Proceedings of IEEE International Conference on Communications, 2004
3953
3957
R. Fantacci, R. Gubellini, D. Tarchi, T. Pecorella (2004). DiffServ on-board satellite switching based on cellular neural networks. s.l : IEEE [10.1109/ICC.2004.1313293].
R. Fantacci; R. Gubellini; D. Tarchi; T. Pecorella
File in questo prodotto:
Eventuali allegati, non sono esposti

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/99846
 Attenzione

Attenzione! I dati visualizzati non sono stati sottoposti a validazione da parte dell'ateneo

Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 2
  • ???jsp.display-item.citation.isi??? 0
social impact