Location via proxy:   [ UP ]  
[Report a bug]   [Manage cookies]                
skip to main content
10.1145/1286380.1286390acmotherconferencesArticle/Chapter ViewAbstractPublication PagesdmsnConference Proceedingsconference-collections
Article

Declarative temporal data models for sensor-driven query processing

Published: 24 September 2007 Publication History

Abstract

Many sensor network applications monitor continuous phenomena by sampling, and fit time-varying models that capture the phenomena's behaviors. We introduce Pulse, a framework for processing continuous queries over these continuous-time data models. Pulse allows users to declaratively specify both their queries and models, and transforms these queries into simultaneous equation systems, which in many cases are significantly cheaper to process than a stream of discrete tuples. Pulse is able to guarantee user-defined error bounds between query results from continuous-time data models and sampled data, including cases of null results. We present a high-level overview of the design and architecture of Pulse and propose several query optimization techniques that are novel to our context, such as the simplification of our equation systems. We also discuss our plans for extending Pulse to support several novel model types, including differential equations and time series, and outline an abstraction to support query processing on these classes of models.

References

[1]
D. Abadi et. al. The design of the Borealis stream processing engine. In CIDR, 2005.
[2]
A. Deshpande and S. Madden. MauveDB: supporting model-based user views in database systems. In SIGMOD, 2006.
[3]
L. Girod et. al. The case for a signal-oriented data stream management system. In CIDR, 2007.
[4]
Global Disaster Alert and Coordination System (GDACS). http://www.gdacs.org/.
[5]
S. Grumbach, P. Rigaux, M. Scholl, and L. Segoufin. The DEDALE prototype. In Constraint Databases, 2000.
[6]
M. Hadjieleftheriou et. al. Complex spatio-temporal pattern queries. In VLDB, 2005.
[7]
A. C. Hindmarsh et. al. Sundials: Suite of nonlinear and differential/algebraic equation solvers. ACM Trans. Math. Softw., 31(3), 2005.
[8]
A. Jain, E. Chang and Y. Wang. Adaptive stream resource management using Kalman Filters. In SIGMOD, 2004.
[9]
S. R. Jeffery, M. N. Garofalakis, and M. J. Franklin. Adaptive cleaning for rfid data streams. In VLDB, 2006.
[10]
A. P. Marathe and K. Salem. A language for manipulating arrays. In VLDB, 1997.
[11]
P. Seshadri. Enhanced abstract data types in object-relational databases. VLDB J., 7(3), 1998.
[12]
D. Srivastava. Subsumption and indexing in constraint query languages with linear arithmetic constraints. Ann. Math. Artif. Intell, 8(3--4), 1993.
[13]
R. H. Wolniewicz and G. Graefe. Algebraic optimization of computations over scientific databases. In VLDB, 1993.
[14]
Y. Zhu and D. Shasha. Warping indexes with envelope transforms for query by humming. In SIGMOD, 2003.

Cited By

View all
  • (2013)A goal-oriented programming framework for grid sensor networks with reconfigurable embedded nodesACM Transactions on Embedded Computing Systems10.1145/2362336.236234611:4(1-30)Online publication date: 1-Jan-2013
  • (2008)Querying continuous functions in a database systemProceedings of the 2008 ACM SIGMOD international conference on Management of data10.1145/1376616.1376696(791-804)Online publication date: 9-Jun-2008
  • (2008)Simultaneous Equation Systems for Query Processing on Continuous-Time Data StreamsProceedings of the 2008 IEEE 24th International Conference on Data Engineering10.1109/ICDE.2008.4497475(666-675)Online publication date: 7-Apr-2008

Recommendations

Comments

Information & Contributors

Information

Published In

cover image ACM Other conferences
DMSN '07: Proceedings of the 4th workshop on Data management for sensor networks: in conjunction with 33rd International Conference on Very Large Data Bases
September 2007
46 pages
ISBN:9781595939111
DOI:10.1145/1286380
  • General Chairs:
  • Amol Deshpande,
  • Qiong Luo
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]

Sponsors

  • Intel: Intel

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 24 September 2007

Permissions

Request permissions for this article.

Check for updates

Qualifiers

  • Article

Conference

VLDB '07
Sponsor:
  • Intel

Acceptance Rates

Overall Acceptance Rate 6 of 16 submissions, 38%

Contributors

Other Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

  • Downloads (Last 12 months)1
  • Downloads (Last 6 weeks)1
Reflects downloads up to 06 Feb 2025

Other Metrics

Citations

Cited By

View all
  • (2013)A goal-oriented programming framework for grid sensor networks with reconfigurable embedded nodesACM Transactions on Embedded Computing Systems10.1145/2362336.236234611:4(1-30)Online publication date: 1-Jan-2013
  • (2008)Querying continuous functions in a database systemProceedings of the 2008 ACM SIGMOD international conference on Management of data10.1145/1376616.1376696(791-804)Online publication date: 9-Jun-2008
  • (2008)Simultaneous Equation Systems for Query Processing on Continuous-Time Data StreamsProceedings of the 2008 IEEE 24th International Conference on Data Engineering10.1109/ICDE.2008.4497475(666-675)Online publication date: 7-Apr-2008

View Options

Login options

View options

PDF

View or Download as a PDF file.

PDF

eReader

View online with eReader.

eReader

Figures

Tables

Media

Share

Share

Share this Publication link

Share on social media