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B. Paul Jenq

dblp:70/4065 · DBLP profile ↗
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3ranked-venue papers
3as 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 · 3 · 3 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 architecture, parallel and distributed computing, and storage systems
2 papers
Performance modeling and evaluation · 57% Parallel and multicore computing · 24% Cloud and datacenter computing · 19%
Databases, data mining, and information retrieval
2 papers
Transaction processing and concurrency control · 100%

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

TopicWeightPapersLastEvidence papers
Transaction processing and concurrency control › concurrency control › locking protocols
two-phase locking		 0.021989
Locking Performance in a Shared-Nothing Parallel Database Machine · IEEE Trans. Knowl. Data Eng. 1989
Locking Performance in a Shared Nothing Parallel Database Machine · ICDE 1989
Performance modeling and evaluation
simulation		 0.021989
Locking Performance in a Shared-Nothing Parallel Database Machine · IEEE Trans. Knowl. Data Eng. 1989
Locking Performance in a Shared Nothing Parallel Database Machine · ICDE 1989
Parallel and multicore computing › parallel computing
parallel database systems		 0.021989
Locking Performance in a Shared-Nothing Parallel Database Machine · IEEE Trans. Knowl. Data Eng. 1989
Locking Performance in a Shared Nothing Parallel Database Machine · ICDE 1989
Transaction processing and concurrency control › concurrency control
locking		 0.011989
Locking Performance in a Shared-Nothing Parallel Database Machine · IEEE Trans. Knowl. Data Eng. 1989
Performance modeling and evaluation › simulation › discrete-event simulation
petri net simulation		 0.011989
Locking Performance in a Shared-Nothing Parallel Database Machine · IEEE Trans. Knowl. Data Eng. 1989
Cloud and datacenter computing › datacenter architecture
shared-nothing architecture		 0.011989
Locking Performance in a Shared-Nothing Parallel Database Machine · IEEE Trans. Knowl. Data Eng. 1989

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

queuing network model · 0.0queueing network modeling · 0.0petri net modeling · 0.0DBSIM · 0.0petri net models · 0.0petri net model · 0.0
YearPublicationVenuePosition
1990 Query Processing in Distributed ORION
B. Paul Jenq, Darrell Woelk, Won Kim 0001, Wan-Lik Lee
 EDBT1
1989 Locking Performance in a Shared Nothing Parallel Database Machine
abstract
A quantitative performance study of two-phase locking in a parallel database machine using a simulation-based methodology is presented. The DBSIM simulation methodology uses a Petri-net model at the higher level and a queuing network model at the lower level. The Petri net model captures the characteristics of parallelism and synchronization at the workload level, while the queuing network model captures queuing aspects of the system at the physical resource level. Transactions in a workload are specified using a performance-oriented specification language based on the transaction component graph: a data-flow graph with database operators. The transaction specifications are translated into Petri-net representations to drive the simulation experiments. Results of an analysis of a two-phase locking strategy with machine sizes ranging from 4 to 256 processors are presented.>
B. Paul Jenq, Brian C. Twichell, Tom W. Keller
 ICDE1
1989 Locking Performance in a Shared-Nothing Parallel Database Machine
abstract
A quantitative performance study of two-phase locking in a parallel database machine using a simulation-based methodology is described. The DBSIM simulation methodology uses models at two levels: a Petri net model at the higher level and a queuing network model at the lower level. The Petri net model captures the characteristics of parallelism and synchronization at the workload level, while the queuing network model captures queuing aspects of the system at the physical resource level. Transactions in a workload are specified using a performance-oriented specification language based on the transaction component graph, a data flow graph with database operators. The transaction specifications are translated into Petri net representations to derive the simulation experiments. The workload is a transaction taken from an order-entry application. A shared-nothing parallel machine architecture is assumed. Results of analysis of a two-phase locking strategy with machine sizes ranging from 4 to 256 processors are presented.>
B. Paul Jenq, Brian C. Twichell, Tom W. Keller
 IEEE Trans. Knowl. Data Eng.1