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Florence Clévenot

dblp:60/3284 · DBLP profile ↗
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2ranked-venue papers
2as first author
0since 2021 · last 2005
—ORCID · none

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

Systems, architecture and hardware · 1 · 1 first-authorComputer networks · 1 · 1 first-author

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
Network performance modeling · 50% Internet architecture and protocols · 25% Content delivery and video streaming · 25%

Topics — the 4 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Content delivery and video streaming › caching › web caching
cooperative web caching		 0.012004
A Simple Model for the Analysis of SQUIRREL · INFOCOM 2004
Network performance modeling › queueing analysis
fluid model		 0.012004
A Simple Model for the Analysis of SQUIRREL · INFOCOM 2004
Network performance modeling › cache performance analysis
hit probability		 0.012004
A Simple Model for the Analysis of SQUIRREL · INFOCOM 2004
Internet architecture and protocols
peer-to-peer networks		 0.012004
A Simple Model for the Analysis of SQUIRREL · INFOCOM 2004

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

fluid model · 0.0discrete-event simulation · 0.0
YearPublicationVenuePosition
2005 Stochastic fluid models for cache clusters
Florence Clévenot, Philippe Nain, Keith W. Ross
 Perform. Evaluation1
2004 A Simple Model for the Analysis of SQUIRREL
abstract
Peer-to-peer (P2P) systems are complex to analyze due to their large number of users who connect intermittently and to the frequency of requests for files or Web objects. In this paper we propose a mathematical model in which request streams are represented as fluid flows and then apply this model in an analysis of Squirrel: a recent P2P cooperative Web cache. Our fluid model provides a low-complexity means to estimate the performance of Squirrel (hit probability and latency) and exhibits the key qualitative properties of this system. The accuracy of our model is validated by a comparison with discrete-event simulation.
Florence Clévenot, Philippe Nain
 INFOCOM1