PSRA: A Data Model for Managing Data in Sensor Networks

Authors:
Haiyang Liu;Jaideep Srivastava;San-Yih Hwang
Affiliations:
University of Minnesota, US;University of Minnesota, US;National Sun Yat-Sen Univeristy, Taiwan
Venue:
SUTC '06 Proceedings of the IEEE International Conference on Sensor Networks, Ubiquitous, and Trustworthy Computing -Vol 1 (SUTC'06) - Volume 01
Year:
2006

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Abstract

Sensor data streams exhibit unique characteristics such as inherent information uncertainty, intrinsic data sample correlations (both within and across streams) and resource constraints. In this paper, we introduce a new data model, called Probabilistic Stream Relational Algebra (PSRA), that extends conventional relational model to capture these new characteristics faced in managing data in sensor networks. New data types, new operations and essential strategies are incorporated into PSRA to facilitate flexible data modeling and resource-efficient operations. We show that operators in PSRA are non-blocking and more expressive than conventional relational model and existing deterministic data stream processing models. A demonstrating application implementing key operations in PSRA is provided to show the advantages of utilizing PSRA in managing data in sensor networks.