Grouping Techniques for Update Propagation in Intermittently Connected Databases.
Sameer Mahajan, Michael J. Donahoo, Shamkant B. Navathe, Mostafa H. Ammar, Sanjoy Malik:
Grouping Techniques for Update Propagation in Intermittently Connected Databases.
ICDE 1998: 46-53@inproceedings{DBLP:conf/icde/MahajanDNAM98,
author = {Sameer Mahajan and
Michael J. Donahoo and
Shamkant B. Navathe and
Mostafa H. Ammar and
Sanjoy Malik},
title = {Grouping Techniques for Update Propagation in Intermittently
Connected Databases},
booktitle = {Proceedings of the Fourteenth International Conference on Data
Engineering, February 23-27, 1998, Orlando, Florida, USA},
publisher = {IEEE Computer Society},
year = {1998},
isbn = {0-8186-8289-2},
pages = {46-53},
ee = {db/conf/icde/MahajanDNAM98.html},
crossref = {DBLP:conf/icde/98},
bibsource = {DBLP, http://dblp.uni-trier.de}
}
Abstract
We consider an environment where one or more
servers carry databases that are of interest to a community
of clients. The clients are only intermittently connected to
the server for brief periods of time. Clients carry a part of
the database for their own processing and accumulate local
updates while disconnected. We call this the Intermittently
Connected Database (ICDB) environment. ICDBs have a wide variety
of applications including sales force automation, insurance claim
processing, and mobile work forces. Our focus in the paper is on
the problem of update propagation at the server in ICDBs and the
associated processing at the clients. The typical client-centric
approach involves the communication and processing of updates and
transactions on a per-client basis, ignoring the overlap of data
between clients. The complexity of this approach is on the order
of the number of connecting clients, thereby limiting the
scalability of the server. We propose a data-centric approach
which clusters data into groups and assigns to each client one
or more of these groups. The proposed scheme results in server
processing complexity on the order of the number of groups, which
we control. We propose various techniques for grouping and
discuss the processing required at the clients to enable the
grouping approach. While the client-centric approach is expected
to significantly degrade with the increasing number of clients,
we expect that a properly designed grouping scheme will sustain
a number of clients that is significantly larger. A prototype has
been developed and performance studies are currently in progress.
Copyright © 1998 by The Institute of
Electrical and Electronic Engineers, Inc. (IEEE).
Abstract used with permission.
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Printed Edition
Proceedings of the Fourteenth International Conference on Data Engineering, February 23-27, 1998, Orlando, Florida, USA.
IEEE Computer Society 1998, ISBN 0-8186-8289-2
Contents
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Copyright © Mon Mar 15 03:39:21 2010
by Michael Ley (ley@uni-trier.de)