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Josh Helzer

dblp:77/993 · DBLP profile ↗
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2ranked-venue papers
0as first author
0since 2021 · last 2007
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Computer networks · 2

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Computer networks
1 paper
Transport protocols and congestion control · 50% Content delivery and video streaming · 50%
Computer architecture, parallel and distributed computing, and storage systems
1 paper
Performance modeling and evaluation · 100%

Topics — the 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Content delivery and video streaming › quality of experience
streaming quality
0.112006
Media Streaming via TFRC: An Analytical Study of the Impact of TFRC on User-Perceived Media Quality · INFOCOM 2006
Transport protocols and congestion control › equation-based rate control
TCP-friendly rate control
0.112006
Media Streaming via TFRC: An Analytical Study of the Impact of TFRC on User-Perceived Media Quality · INFOCOM 2006
Performance modeling and evaluation
queueing models
0.012006
Media Streaming via TFRC: An Analytical Study of the Impact of TFRC on User-Perceived Media Quality · INFOCOM 2006

Methods — techniques the papers use, named apart from their topics

queueing model · 0.1markov-renewal-modulated deterministic process · 0.1
YearPublicationVenuePosition
2007 Media streaming via TFRC: An analytical study of the impact of TFRC on user-perceived media quality
Lisong Xu, Josh Helzer
Comput. Networks2
2006 Media Streaming via TFRC: An Analytical Study of the Impact of TFRC on User-Perceived Media Quality
abstract
TCP-Friendly Rate Control (TFRC) is being adopted in Internet standards for congestion control of various streaming media applications. In this paper, we consider the transmission of pre-recorded media from a server to a client by using TFRC, and analytically study the impact of TFRC on user-perceived media quality, which is roughly measured by calculating the rebuffering probability. A rebuffering probability is defined to be the probability that the total duration of all rebuffering events experienced by a user is longer than a certain threshold. Two approaches are presented to help an application determine an appropriate initial buffering delay and media playback rate in order to achieve a certain rebuffering probability under a given network condition. First, we derive a closed- form expression to approximate the average TFRC sending rate, which could be used as the maximum allowed playback rate of a media stream. Second, we develop a queueing model for a TFRC client buffer with the traffic described by a Markov-Renewal- Modulated Deterministic Process (MRMDP), and present an iterative method to calculate the rebuffering probability.
Lisong Xu, Josh Helzer
INFOCOM2