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

Jeff Sidell

dblp:34/2083 · DBLP profile ↗
← Back
2ranked-venue papers
1as first author
0since 2021 · last 1996
—ORCID · none

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

Databases, data management, data science and information retrieval · 2 · 1 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
Distributed systems · 100%
Databases, data mining, and information retrieval
2 papers
Distributed and cloud data management · 100%

Topics — the 4 heaviest of 5, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Distributed and cloud data management
data replication
0.011996
Data Replication in Mariposa · ICDE 1996
Distributed and cloud data management › data replication
update propagation
0.011996
Data Replication in Mariposa · ICDE 1996
Distributed systems
distributed coordination
0.011996
Mariposa: A Wide-Area Distributed Database System · VLDB J. 1996
Distributed systems › replication › geo-replication
wide-area replication
0.011996
Mariposa: A Wide-Area Distributed Database System · VLDB J. 1996

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

timestamp serialization · 0.0rule-based conflict resolution · 0.0economic model · 0.0
YearPublicationVenuePosition
1996 Data Replication in Mariposa
abstract
The Mariposa distributed data manager uses an economic model for managing the allocation of both storage objects and queries to servers. In this paper, we present extensions to the economic model which support replica management, as well as our mechanisms for propagating updates among replicas. We show how our replicacontrol mechanism can be used to provide consistent, although potentially stale, views of data across many machines without expensive pertransaction synchronization. We present a rule-based con#ict resolution mechanism, which can be usedto enhancetraditional time-stamp serialization. We discuss the e#ects of our replica system on query processing for both read-only and read-write queries. We further demonstrate how the replication model and mechanisms naturally support name service in Mariposa. 1 Introduction In this paper we describe replica managementin the Mariposa distributed data base management system #STON94a#. There has been considerable research devoted to stu...
Jeff Sidell, Paul M. Aoki, Adam Sah, Carl Staelin, Michael Stonebraker, Andrew Yu
ICDE1
1996 Mariposa: A Wide-Area Distributed Database System
Michael Stonebraker, Paul M. Aoki, Witold Litwin, Avi Pfeffer, Adam Sah, Jeff Sidell, Carl Staelin, Andrew Yu
VLDB J.6