Network heavy traffic modeling using α-stable self-similar processes.

Network heavy traffic modeling using α-stable self-similar processes.

We propose a new model for network heavy traffic approximation, based on α-stable self-similar processes, namely the skewed linear fractional stable noise. The model demonstrates more flexibility than existing models in fitting different levels of burstiness and correlation in the data. Nonetheless,...

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Détails bibliographiques
Publié dans:IEEE Transactions on communications 49, 7 (2001).
Auteur principal: Karasaridis, A.
Format: Article
Langue:English
Sujets:
α-stable self-similar processes.
Bellcore Laboratories.
G/D/1 system.
Telcordia.
Web Wide Web.
Webcasting traffic.
Algorithmic procedure.
Asymptotic lower bound.
Bursty Ethernet data.
Data correlation.
Network heavy traffic approximation.
Network heavy traffic modeling.
Parameter estimation.
Queue distribution tail.
Queueing simulations.
Residual queueing distribution.
Simulations.
Skewed linear fractional stable noise.