NDLI: Worst closed-loop controlled bulk distributions of stochastic arrival processes for queue performance

Content Provider	IEEE Xplore Digital Library
Author	Lee, Daniel C.
Copyright Year	2011
Abstract	This paper presents basic queueing analysis contributing to teletraffc theory, with commonly accessible mathematical tools. This paper studies queueing systems with bulk arrivals. It is assumed that the number of arrivals and the expected number of arrivals in each bulk are bounded by some constraints B and λ, respectively. Subject to these constraints, convexity argument is used to show that the bulk-size probability distribution that results in the worst mean queue performance is an extremal distribution with support {1, B} and mean equal to λ. Furthermore, from the viewpoint of security against denial-of-service attacks, this distribution remains the worst even if an adversary were allowed to choose the bulk-size distribution at each arrival instant as a function of past queue lengths; that is, the adversary can produce as bad queueing performance with an open-loop strategy as with any closed-loop strategy. These results are proven for an arbitrary arrival process with bulk arrivals and a general service model.
Starting Page	87
Ending Page	92
Page Count	6
File Size	376580
File Format	PDF
ISSN	12292370
Volume Number	7
Issue Number	1
Language	English
Publisher	Editorial Department of Journal of Communications and Networks
Publisher Date	2005-03-01
Publisher Place	South Korea
Access Restriction	Subscribed
Rights Holder	JCN
Subject Keyword	Frequency modulation Loss measurement Stochastic processes Delay Queueing analysis Multiplexing Length measurement teletrafflc Performance tools and methodology queueing analysis
Content Type	Text
Resource Type	Article
Subject	Computer Networks and Communications Information Systems

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