Streaming video packet scheduling by geoY/G/∞ input process modeling

Sujeong Choi, Sang H. Kang, Bara Kim

Research output: Contribution to journalArticle

6 Citations (Scopus)

Abstract

We introduce GeoY/G/∞ input process with beta-distributed batch size and Weibull-like autocorrelation function in order to model video traffic. Investigating the overflow probability of queueing system by large deviation theory, we develop a streaming scheduling algorithm by applying the overflow analysis result to estimating the packet deadline-missing probability. Through experiments with 30-second long movie traces, we show that our proposed scheduling scheme outperforms existing schemes based on fractional Brownian motion and Markovian models.

Original languageEnglish
Pages (from-to)474-476
Number of pages3
JournalIEEE Communications Letters
Volume9
Issue number5
DOIs
Publication statusPublished - 2005 May 1

Fingerprint

Packet Scheduling
Video Streaming
Overflow
Video streaming
Process Modeling
Scheduling
Large Deviation Theory
Brownian movement
Weibull
Fractional Brownian Motion
Queueing System
Deadline
Autocorrelation Function
Scheduling algorithms
Streaming
Scheduling Algorithm
Autocorrelation
Batch
Trace
Traffic

Keywords

  • Geo/G/∞ input process
  • Packet scheduling
  • Streaming media

ASJC Scopus subject areas

  • Computer Networks and Communications

Cite this

Streaming video packet scheduling by geoY/G/∞ input process modeling. / Choi, Sujeong; Kang, Sang H.; Kim, Bara.

In: IEEE Communications Letters, Vol. 9, No. 5, 01.05.2005, p. 474-476.

Research output: Contribution to journalArticle

Choi, Sujeong ; Kang, Sang H. ; Kim, Bara. / Streaming video packet scheduling by geoY/G/∞ input process modeling. In: IEEE Communications Letters. 2005 ; Vol. 9, No. 5. pp. 474-476.
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