Demonstration venue · read-only. Every page can be browsed; the buttons that would change it are switched off. Create an account to run TaxoReview on your own data. A simulation from public publication records: the people listed were not invited and did not agree to review.
? Tutorial for this page

M. W. Doss

dblp:271/5582 · DBLP profile ↗
← Back
1ranked-venue papers
0as first author
0since 2021 · last 1981
—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 management and operations · 77% Network performance modeling · 23%

Topics — the 2 heaviest of 2, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Network management and operations
availability analysis
0.011981
Communication Network Availability Predictions Based on Measurement Data · IEEE Trans. Commun. 1981
Network performance modeling › simulation modeling
simulation validation
0.011981
Communication Network Availability Predictions Based on Measurement Data · IEEE Trans. Commun. 1981

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

heuristic modeling · 0.0computer simulation · 0.0
YearPublicationVenuePosition
1981 Communication Network Availability Predictions Based on Measurement Data
abstract
Published data describing the probability distributions of data communication system reliability parameters such as availability are very sparse. This paper describes a set of data collected in order to model communication line availability by monitoring operational communication systems. Probability distribution functions for single line availabilities and for the durations of failures are given. A heuristic model for estimating availabilities for more complex systems is presented along with computer simulation data validating the accuracy of the model. The results presented make possible more realistic availability predictions for common types of networks than have previously been computable.
John D. Spragins, James D. Markov, M. W. Doss, Stephanie A. Mitchell, David C. Squire
IEEE Trans. Commun.3