QUASAR: Quality Aware Sensing Architecture.

Appeared in ACM SIGMOD Record, vol. 33(1), March 2004.


I. Lazaridis, Q. Han, X. Yu, S. Mehrotra, N. Venkatasubramanian, and Dmitri V. Kalashnikov

Computer Science Department
University of California, Irvine

Abstract

Sensor devices are promising to revolutionize our interaction with the physical world by allowing continuous monitoring and reaction to natural and artificial processes at an unprecedented level of spatial and temporal resolution. As sensors become smaller, cheaper and more configurable, systems incorporating large numbers of them become feasible. Besides the technological aspects of sensor design, a critical factor enabling future sensor-driven applications will be the availability of an integrated infrastructure taking care of the onus of data management. Ideally, accessing sensor data should be no difficult or burdensome than using simple SQL. In this paper we investigate some of the issues that such an infrastructure must address. Unlike conventional distributed database systems, a sensor data architecture must handle extremely high data generation rates from a large number of small autonomous components. And, unlike the emerging paradigm of data streams, it is infeasible to think that all this data can be streamed into the query processing site, due to severe bandwidth and energy constraints of battery-operated wireless sensors. Thus, sensing data architectures must become quality-aware, regulating the quality of data at all levels of the distributed system, and supporting user applications' quality requirements in the most efficient manner possible.

Keywords:

Sensor databases, quality-aware querying.


Downloadable files:

Paper: SIGMODR04_dvk.pdf


BibTeX entry:

@article{SIGMODR04::dvk,
   author    = {I. Lazaridis and Q. Han and X. Yu and S. Mehrotra and Nalini Venkatasubramanian
                and Dmitri V. Kalashnikov and W. Yang},
   title     = {{QUASAR}: Quality Aware Sensing Architecture},
   journal   = {ACM SIGMOD Record},
   volume    = 33,
   number    = 1,
   pages     = {26--31}, 
   month     = mar, 
   year      = 2004
}
 

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