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Waheed Qureshi

dblp:45/4598 · DBLP profile ↗
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2ranked-venue papers
0as first author
0since 2021 · last 1992
—ORCID · none

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

Databases, data management, data science and information retrieval · 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 architecture, parallel and distributed computing, and storage systems
1 paper
Storage systems · 39% Parallel and multicore computing · 30% Performance modeling and evaluation · 30%
Databases, data mining, and information retrieval
1 paper
Distributed and cloud data management · 100%
Computer networks
1 paper
Content delivery and video streaming · 100%

Topics — the 5 heaviest of 6, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Storage systems
declustering		 0.011992
A Performance Analysis of Alternative Multi-Attribute Declustering Strategies · SIGMOD Conference 1992
Parallel and multicore computing › parallel computing
parallel database systems		 0.011992
A Performance Analysis of Alternative Multi-Attribute Declustering Strategies · SIGMOD Conference 1992
Performance modeling and evaluation
workload characterization		 0.011992
A Performance Analysis of Alternative Multi-Attribute Declustering Strategies · SIGMOD Conference 1992
Distributed and cloud data management › data placement
object placement		 0.011991
Object Placement in Parallel Hypermedia Systems · VLDB 1991
Storage systems
data layout		 0.011992
A Performance Analysis of Alternative Multi-Attribute Declustering Strategies · SIGMOD Conference 1992

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

performance analysis · 0.0
YearPublicationVenuePosition
1992 A Performance Analysis of Alternative Multi-Attribute Declustering Strategies
abstract
During the past decade, parallel database systems have gained increased popularity due to their high performance, scalability and availability characteristics. With the predicted future database sizes and the complexity of queries, the scalability of these systems to hundreds and thousands of processors is essential for satisfying the projected demand. Several studies have repeatedly demonstrated that both the performance and scalability of a paralel database system is contingent on the physical layout of data across the processors of the system. If the data is not declustered properly, the execution of an operator might waste resources, reducing the overall processing capability of the system.
Shahram Ghandeharizadeh, David J. DeWitt, Waheed Qureshi
 SIGMOD Conference3
1991 Object Placement in Parallel Hypermedia Systems
Shahram Ghandeharizadeh, Luis Ramos, Zubair Asad, Waheed Qureshi
 VLDB4