A clustering method that uses lossy aggregation of data

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A clustering method that uses lossy aggregation of data

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Conference On Embedded Networked Sensor Systems archive
Proceedings of the 2nd international conference on Embedded networked sensor systems table of contents

Baltimore, MD, USA

POSTER SESSION: Posters table of contents

Pages: 269 - 270

Year of Publication: 2004

ISBN:1-58113-879-2

Authors

Apoorva Jindal	University of Southern California, Los Angeles, CA
Konstantinos Psounis	University of Southern California, Los Angeles, CA

Sponsors

SIGARCH: ACM Special Interest Group on Computer Architecture
SIGBED: ACM Special Interest Group on Embedded Systems
ACM: Association for Computing Machinery
SIGMOBILE: ACM Special Interest Group on Mobility of Systems, Users, Data and Computing
SIGCOMM: ACM Special Interest Group on Data Communication
SIGMETRICS: ACM Special Interest Group on Measurement and Evaluation
SIGOPS: ACM Special Interest Group on Operating Systems

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ACM New York, NY, USA

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ABSTRACT

Wireless sensor networks are characterized by dense deployment of sensor nodes which collectively communicate sensed data to the sink. However, due to the spatial correlation between sensor observations, it is not necessary for every node to transmit its data. We propose a clustering method which exploits the above observation. We do not make any assumption on the nature of data, and hence the algorithm will be valid for a broad range of conditions. The paper shows how to calculate the optimal cluster size. We also discuss the structure of the complete architecture which is still under development.

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.

	1	A. Jindal and K. Psounis. Modelling Spatially-Correlated Sensor Network Data. In Technical Report, CENG-2004-10, USC, 2004.
	2	O. Younis and S. Fahmy. Distributed Clustering in Ad-hoc Sensor Networks: A Hybrid, Energy-Efficient Approach. In Proceedings of IEEE Infocom'04, Mar. 2004.
	3	S. Bandyopadhyay and E. Coyle. An Energy-Efficient Hierarchical Clustering Algorithm for Wireless Sensor Networks. In Proceedings of IEEE Infocom'03, Apr. 2003.
	4	W. Heinzelman and A. Chandrakasan and H. Balakrishnan. An Application-Specific Protocol Architecture for Wireless Microsensor Networks. IEEE Transactions on Wireless Communications 1:660--670, Oct. 2002.
	5	M. C. Vuran and I. F. Akyildiz. Spatial Correlation-based Collaborative Medium Access Control in Wireless Sensor Networks. submitted for publication, 2004
	6	C.F. Chiasserini and I. Chlamtac and P. Monti and A. Nucci. Energy Efficient design of Wireless Ad Hoc Networks. In Proceedings of European Wireless, feb. 2002