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Return to Stream and Sensor Processing
, a dataflow system for processing continuous queries over data streams. TelegraphCQ is based on a novel, highly-adaptive architecture supporting dynamic query workloads in volatile data streaming environments. In this demonstration we show our current version of TelegraphCQ, which we implemented by leveraging the code base of the open source PostgreSQL database system. Although TelegraphCQ differs significantly from a traditional database system, we found that a significant portion of the PostgreSQL code was easily reusable. We also found the extensibility features of PostgreSQL very useful, particularly its rich data types and the ability to load user-developed functions. In this demonstration we use two applications to show how TelegraphCQ's adaptive architecture enables the dynamic introduction of new queries into a running system, as well as how it reacts to volatility in the input data streams. First, we integrate TelegraphCQ with a sensor network to show how the system adapts to abrupt changes in the content and volume of data streams. Next we use a simulation of freeway traffic sensors to show TelegraphCQ scales to large numbers of input streams and queries.
@inproceedings {DBLP:conf/sigmod/ChandrasekaranCDFHHKMRS03, author = {Sirish Chandrasekaran and Owen Cooper and Amol Deshpande and Michael J. Franklin and Joseph M. Hellerstein and Wei Hong and Sailesh Krishnamurthy and Samuel Madden and Fred Reiss and Mehul A. Shah}, booktitle = {SIGMOD Conference}, title = {TelegraphCQ: Continuous Dataflow Processing.}, pages = {668}, year = {2003}, url = {db/conf/sigmod/sigmod2003.html#ChandrasekaranCDFHHKMRS03}, ee = {http://www.acm.org/sigmod/sigmod03/eproceedings/papers/dem12.pdf}, crossref = {conf/sigmod/2003}, bibsource = {DBLP, http://dblp.uni-trier.de} }  ©2004 Association for Computing Machinery |
