Towards Sensor Database Systems

Sensor networks are being widely deployed for measurement, detection and surveillance applications. In these new applications, users issue long-running queries over a combination of stored data and sensor data. Most existing applications rely on a centralized system for collecting sensor data. These systems lack flexibility because data is extracted in a predefined way; also, they do not scale to a large number of devices because large volumes of raw data are transferred regardless of the queries that are submitted. In our new concept of sensor database system, queries dictate which data is extracted from the sensors. In this paper, we define the concept of sensor databases mixing stored data represented as relations and sensor data represented as time series. Each long-running query formulated over a sensor database defines a persistent view, which is maintained during a given time interval. We also describe the design and implementation of the COUGAR sensor database system.

[1]  Hamid Pirahesh,et al.  Alert: An Architecture for Transforming a Passive DBMS into an Active DBMS , 1991, VLDB.

[2]  Douglas B. Terry,et al.  Continuous queries over append-only databases , 1992, SIGMOD '92.

[3]  Miron Livny,et al.  SEQ: A model for sequence databases , 1995, Proceedings of the Eleventh International Conference on Data Engineering.

[4]  Abraham Silberschatz,et al.  View maintenance issues for the chronicle data model (extended abstract) , 1995, PODS.

[5]  Evaggelia Pitoura,et al.  Data Management for Mobile Computing , 1997, The Kluwer International Series on Advances in Database Systems.

[6]  Praveen Seshadri,et al.  Enhanced abstract data types in object-relational databases , 1998, The VLDB Journal.

[7]  Randy H. Katz,et al.  Next century challenges: mobile networking for “Smart Dust” , 1999, MobiCom.

[8]  Tomasz Imielinski,et al.  DataSpace: querying and monitoring deeply networked collections in physical space , 2000, IEEE Wirel. Commun..

[9]  Praveen Seshadri,et al.  Client-site query extensions , 1999, SIGMOD '99.

[10]  Philippe Bonnet,et al.  Querying the physical world , 2000, IEEE Wirel. Commun..

[11]  Stefan Saroiu,et al.  Self-organizing data sharing communities with SAGRES , 2000, SIGMOD '00.

[12]  Joseph M. Hellerstein,et al.  Eddies: continuously adaptive query processing , 2000, SIGMOD '00.

[13]  Stephen M. McGarry,et al.  Declarative ad-hoc sensor networking , 2000, SPIE Optics + Photonics.

[14]  Stefan Saroiu,et al.  Self-organizing data sharing communities with SAGRES , 2000, SIGMOD '00.

[15]  Deborah Estrin,et al.  Directed diffusion: a scalable and robust communication paradigm for sensor networks , 2000, MobiCom '00.

[16]  Philippe Bonnet,et al.  Device Database Systems , 2000, Proceedings of 16th International Conference on Data Engineering (Cat. No.00CB37073).

[17]  Deborah Estrin,et al.  Embedding the Internet: introduction , 2000, Commun. ACM.

[18]  Dieter Pfoser,et al.  Novel Approaches in Query Processing for Moving Object Trajectories , 2000, VLDB 2000.

[19]  Deborah Estrin,et al.  Embedding the Internet , 2000 .

[20]  David L. Tennenhouse,et al.  Proactive computing , 2000, Commun. ACM.

[21]  Gregory J. Pottie,et al.  Wireless integrated network sensors , 2000, Commun. ACM.