An adaptive data replication algorithm

Article Properties
  • Language
    English
  • Publication Date
    1997/06/01
  • Indian UGC (Journal)
  • Refrences
    46
  • Citations
    103
  • Ouri Wolfson Univ. of Illinois, Chicago, and NASA/CESDIS, Goddard Space Flight Center, Greenbelt, MD
  • Sushil Jajodia George Mason Univ., Fairfax, VA
  • Yixiu Huang Univ. of Illinois, Chicago
Abstract
Cite
Wolfson, Ouri, et al. “An Adaptive Data Replication Algorithm”. ACM Transactions on Database Systems, vol. 22, no. 2, 1997, pp. 255-14, https://doi.org/10.1145/249978.249982.
Wolfson, O., Jajodia, S., & Huang, Y. (1997). An adaptive data replication algorithm. ACM Transactions on Database Systems, 22(2), 255-314. https://doi.org/10.1145/249978.249982
Wolfson O, Jajodia S, Huang Y. An adaptive data replication algorithm. ACM Transactions on Database Systems. 1997;22(2):255-314.
Journal Categories
Science
Mathematics
Instruments and machines
Electronic computers
Computer science
Science
Mathematics
Instruments and machines
Electronic computers
Computer science
Computer software
Science
Science (General)
Cybernetics
Information theory
Technology
Electrical engineering
Electronics
Nuclear engineering
Electronics
Computer engineering
Computer hardware
Description

Improve distributed database performance with dynamic data replication. This article introduces an adaptive algorithm that optimizes data replication in distributed systems. The algorithm dynamically adjusts the replication scheme – the set of processors storing a copy of the object – based on changes in read-write patterns, ensuring efficient data access. The algorithm aims to continuously move the replication scheme towards an optimal configuration. Demonstrated theoretically and experimentally, the algorithm can integrate with concurrency control and recovery mechanisms in a distributed database management system. The way we provide a lower bound on the performance of any dynamic replication algorithm. The results of this study are relevant for database administrators, engineers, and researchers who use distributed database systems, and more generally to scientists working on distributed computing.

While the abstract is about database systems, ACM Transactions on Database Systems also focuses on broader aspects of computer science, such as information theory and software engineering. Therefore, contextualizing the paper directly within a narrow journal scope may be limited. Considering the provided information, the paper makes a valuable contribution to database technology within the broad field of computer science.

Refrences
Citations
Citations Analysis
The first research to cite this article was titled Information systems research at George Mason University and was published in 1997. The most recent citation comes from a 2023 study titled Information systems research at George Mason University . This article reached its peak citation in 2006 , with 8 citations.It has been cited in 60 different journals, 3% of which are open access. Among related journals, the IEEE Transactions on Knowledge and Data Engineering cited this research the most, with 9 citations. The chart below illustrates the annual citation trends for this article.
Citations used this article by year