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Navid Haghighi

dblp:71/4697 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 1990
—ORCID · none

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

Databases, data management, data science and information retrieval · 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 architecture, parallel and distributed computing, and storage systems
1 paper
Performance modeling and evaluation · 100%
Databases, data mining, and information retrieval
1 paper
Transaction processing and concurrency control · 100%

Topics — the 3 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Transaction processing and concurrency control › concurrency control
multiversion concurrency control
0.011990
Performance Evaluation of Multiversion Database Systems · ICDE 1990
Performance modeling and evaluation › simulation › computer system simulation
database simulation
0.011990
Performance Evaluation of Multiversion Database Systems · ICDE 1990
Performance modeling and evaluation
simulation
0.011990
Performance Evaluation of Multiversion Database Systems · ICDE 1990

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

discrete-event simulation · 0.0
YearPublicationVenuePosition
1990 Performance Evaluation of Multiversion Database Systems
abstract
A description is given of a detailed simulation study of the performance of multiversion database systems. The characteristics and the extent to which they provide performance benefits over their single-version counterparts are investigated. First, the structure of a software prototyping environment for the evaluation of distributed database systems is presented. Using this environment, the authors shows that for specific workloads, multiversion database systems offer performance improvements despite additional CPU and I/O costs involved in accessing old versions of data. It is also shown that transaction size is one of the most critical parameters affecting the system performance.>
Sang Hyuk Son, Navid Haghighi
ICDE2