| QUASAR: quality aware sensing architecture |
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ACM SIGMOD Record
archive
Volume 33 , Issue 1 (March 2004)
table of contents
SPECIAL ISSUE: Special section on sensor network technology & sensor data management (Part II)
table of contents
Pages: 26 - 31
Year of Publication: 2004
ISSN:0163-5808
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Downloads (6 Weeks): 6, Downloads (12 Months): 28, Citation Count: 4
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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 inconvenient 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.
REFERENCES
Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.
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[doi> 10.1145/543613.543615]
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Chris Olston , Boon Thau Loo , Jennifer Widom, Adaptive precision setting for cached approximate values, Proceedings of the 2001 ACM SIGMOD international conference on Management of data, p.355-366, May 21-24, 2001, Santa Barbara, California, United States
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UC Irvine, http://www-db.ics.uci.edu/pages/research/quasar/index.shtml. QUASAR Project.
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X. Yu, S. Mehrotra, N. Venkatasubramanian, and W. Yang. Approximate monitoring by aggregation-oriented clustering inwireless sensor networks. (under submission), 2003.
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X. Yu, K. Niyogi, S. Mehrotra, and N. Venkatasubramanian. Adaptive middleware for distributed sensor environments. IEEE DS Online, 4(5), May 2003.
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CITED BY 4
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Nesime Tatbul , Mark Buller , Reed Hoyt , Steve Mullen , Stan Zdonik, Confidence-based data management for personal area sensor networks, Proceeedings of the 1st international workshop on Data management for sensor networks: in conjunction with VLDB 2004, August 30-30, 2004, Toronto, Canada
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