Title
Large buffer asymptotics for generalized processor sharing queues with Gaussian inputs
Abstract
In this paper we derive large-buffer asymptotics for a two-class Generalized Processor Sharing (GPS) model. We assume both classes to have Gaussian characteristics. We distinguish three cases depending on whether the GPS weights are above or below the average rate at which traffic is sent. First, we calculate exact asymptotic upper and lower bounds, then we calculate the logarithmic asymptotics, and finally we show that the decay rates of the upper and lower bound match. We apply our results to two special Gaussian models: the integrated Gaussian process and the fractional Brownian motion. Finally we derive the logarithmic large-buffer asymptotics for the case where a Gaussian flow interacts with an on-off flow.
Year
DOI
Venue
2006
10.1007/s11134-006-9147-6
Queueing Syst.
Keywords
Field
DocType
Large-buffer asymptotics,Gaussian traffic,Generalized processor sharing,Communication networks,Differentiated services
Mathematical optimization,Gaussian random field,Upper and lower bounds,Gaussian,Generalized processor sharing,Gaussian process,Asymptotic analysis,Fractional Brownian motion,Gaussian function,Mathematics
Journal
Volume
Issue
ISSN
54
2
0257-0130
Citations 
PageRank 
References 
2
0.47
14
Authors
2
Name
Order
Citations
PageRank
Krzysztof Dębicki1313.22
Miranda Van Uitert21036.97