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Synchronizing a database to improve freshness

Authors:

Junghoo Cho,

Hector Garcia-MolinaAuthors Info & Claims

SIGMOD '00: Proceedings of the 2000 ACM SIGMOD international conference on Management of data

Pages 117 - 128

https://doi.org/10.1145/342009.335391

Published: 16 May 2000 Publication History

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Abstract

In this paper we study how to refresh a local copy of an autonomous data source to maintain the copy up-to-date. As the size of the data grows, it becomes more difficult to maintain the copy \ fresh, “making it crucial to synchronize the copy effectively. We define two freshness metrics, change models of the underlying data, and synchronization policies. We analytically study how effective the various policies are. We also experimentally verify our analysis, based on data collected from 270 web sites for more than 4 months, and we show that our new policy improves the \ freshness” very significantly compared to current policies in use.

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Index Terms

Synchronizing a database to improve freshness
1. Information systems
  1. Data management systems
    1. Database design and models
      1. Physical data models

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Information

Published In

SIGMOD '00: Proceedings of the 2000 ACM SIGMOD international conference on Management of data

May 2000

604 pages

ISBN:1581132174

DOI:10.1145/342009

Chairmen:
Maggie Dunham
Southern Methodist Univ.
,
Jeffrey F. Naughton
Univ. of Wisconsin-Madison
,
Weidong Chen
Southern Methodist Univ.
,
Nick Koudas
AT &T Labs

ACM SIGMOD Record Volume 29, Issue 2
June 2000
609 pages
ISSN:0163-5808
DOI:10.1145/335191
Editors:
Weidong Chen
Southern Methodist Univ., Dallas, TX
,
Jeffrey Naughton
Univ. of Wisconsin-Madison, Madison
,
Philip A. Bernstein
Microsoft
Issue’s Table of Contents

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 16 May 2000

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SIGMOD/PODS00

Sponsor:

SIGMOD

SIGMOD/PODS00: ACM International Conference on Management of Data and Symposium on Principles of Database Systems

May 15 - 18, 2000

Texas, Dallas, USA

Acceptance Rates

SIGMOD '00 Paper Acceptance Rate 42 of 248 submissions, 17%;

Overall Acceptance Rate 785 of 4,003 submissions, 20%

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Cited By

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Kiryanov D(2022)A Scalable Aggregation System Designed to Process 50,000 RSS FeedsПрограммные системы и вычислительные методы10.7256/2454-0714.2022.4.39124(20-38)Online publication date: Apr-2022
https://doi.org/10.7256/2454-0714.2022.4.39124
Kiryanov D(2022)Research of the methods of creating content aggregation systemsПрограммные системы и вычислительные методы10.7256/2454-0714.2022.1.37341(9-31)Online publication date: Jan-2022
https://doi.org/10.7256/2454-0714.2022.1.37341
Hu HXiong KLu YGao BFan PLetaief K(2022) α–β AoI Penalty in Wireless-Powered Status Update Networks IEEE Internet of Things Journal10.1109/JIOT.2021.30841619:1(474-484)Online publication date: 1-Jan-2022
https://doi.org/10.1109/JIOT.2021.3084161
Long SYan L(2022)Crawling Deep Web Data Based on Three-stage Template2022 7th International Conference on Big Data Analytics (ICBDA)10.1109/ICBDA55095.2022.9760358(30-34)Online publication date: 4-Mar-2022
https://doi.org/10.1109/ICBDA55095.2022.9760358
Keller MDöschl AMandl PSchill A(2021)When she posts next? A comparison of refresh strategies for Online Social NetworksThe 23rd International Conference on Information Integration and Web Intelligence10.1145/3487664.3487778(123-129)Online publication date: 29-Nov-2021
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Bedewy ASun YKompella SShroff N(2021)Optimal Sampling and Scheduling for Timely Status Updates in Multi-Source NetworksIEEE Transactions on Information Theory10.1109/TIT.2021.306038767:6(4019-4034)Online publication date: Jun-2021
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Kolobov ABubeck SZimmert JDaumé HSingh A(2020)Online learning for active cache synchronizationProceedings of the 37th International Conference on Machine Learning10.5555/3524938.3525436(5371-5380)Online publication date: 13-Jul-2020
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Han SBendersky MGajda PNovikov SNajork MBrodowsky BPopescul A(2020)Adversarial Bandits Policy for Crawling Commercial Web ContentProceedings of The Web Conference 202010.1145/3366423.3380125(407-417)Online publication date: 20-Apr-2020
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Hsu YModiano EDuan L(2020)Scheduling Algorithms for Minimizing Age of Information in Wireless Broadcast Networks with Random ArrivalsIEEE Transactions on Mobile Computing10.1109/TMC.2019.293619919:12(2903-2915)Online publication date: 1-Dec-2020
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Synchronizing a database to improve freshness

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