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Luis Zubieta

dblp:71/5945 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 1992
—ORCID · none

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

Computer networks · 1

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 measurement and analytics · 70% Physical-layer communications · 23% Internet architecture and protocols · 7%

Topics — the 5 heaviest of 5, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Physical-layer communications › signal processing for communications › statistical signal processing › estimation theory
spectral density estimation
0.011992
Measurement of ATM Traffic on the Cell, Burst and Activity Level by Traffic Sampling · INFOCOM 1992
Network measurement and analytics
traffic characterization
0.011992
Measurement of ATM Traffic on the Cell, Burst and Activity Level by Traffic Sampling · INFOCOM 1992
Network measurement and analytics
traffic measurement
0.011992
Measurement of ATM Traffic on the Cell, Burst and Activity Level by Traffic Sampling · INFOCOM 1992
Network measurement and analytics › sampling
traffic sampling
0.011992
Measurement of ATM Traffic on the Cell, Burst and Activity Level by Traffic Sampling · INFOCOM 1992
Internet architecture and protocols › ATM networks
ATM traffic
0.011992
Measurement of ATM Traffic on the Cell, Burst and Activity Level by Traffic Sampling · INFOCOM 1992

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

forward-backward least square spectral estimation · 0.0
YearPublicationVenuePosition
1992 Measurement of ATM Traffic on the Cell, Burst and Activity Level by Traffic Sampling
abstract
The authors address the problem of measuring asynchronous transfer mode (ATM) traffic on the cell, burst and activity level. With the aid of a traffic sampling mechanism it is shown that efficient data can be collected. These data are then used to estimate the spectral density on each level. It is shown that a forward-backward least square spectral estimator with prefiltering gives an accurate estimation even at low frequencies and that the power spectral density at frequency zero and the load are the most dominant parameters for the queue length and hence also for loss.>
Reto Grünenfelder, Luis Zubieta
INFOCOM2