ACM SIGMOD Anthology ACM SIGMOD dblp.uni-trier.de

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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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
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