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Probabilistic analysis of buffer starvation in Markovian queues

Authors: Xu, Yuedong; Altman, Eitan; El-Azouzi, Rachid; Elayoubi, Salah Eddine; Haddad, Majed; Jimenez, Tania;

Probabilistic analysis of buffer starvation in Markovian queues

Abstract

Our purpose in this paper is to obtain the \emph{exact distribution} of the number of buffer starvations within a sequence of $N$ consecutive packet arrivals. The buffer is modeled as an M/M/1 queue. When the buffer is empty, the service restarts after a certain amount of packets are \emph{prefetched}. With this goal, we propose two approaches, one of which is based on \emph{Ballot theorem}, and the other uses recursive equations. The Ballot theorem approach gives an explicit solution, but at the cost of the high complexity order in certain circumstances. The recursive approach, though not offering an explicit result, needs fewer computations. We further propose a fluid analysis of starvation probability on the file level, given the distribution of file size and the traffic intensity. The starvation probabilities of this paper have many potential applications. We apply them to optimize the quality of experience (QoE) of media streaming service, by exploiting the tradeoff between the start-up delay and the starvation.

Country
France
Keywords

Ballot Theorem, Starvation Probability, [INFO.INFO-NI] Computer Science [cs]/Networking and Internet Architecture [cs.NI], Recursive Approach, Quality of Experience

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    influence
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
23
Average
Top 10%
Top 10%
Green