Optimizing parallel itineraries for KNN query processing in wireless sensor networks

Tao Young Fu, Wen Chih Peng, Wang-chien Lee

Research output: Chapter in Book/Report/Conference proceedingConference contribution

8 Citations (Scopus)

Abstract

Spatial queries for extracting data from wireless sensor networks are important for many applications, such as environmental monitoring and military surveillance. One such query is K Nearest Neighbor (KNN) query that facilitates sampling of monitored sensor data in correspondence with a given query location. Recently, itinerary-based KNN query processing techniques, that propagate queries and collect data along a pre-determined itinerary, have been developed concurrently [12][14]. These research works demonstrate that itinerary-based KNN query processing algorithms are able to achieve better energy efficiency than other existing algorithms. However, how to derive itineraries based on different performance requirements remains a challenging problem. In this paper, we propose a new itinerary-based KNN query processing technique, called PCIKNN, that derives different itineraries aiming at optimizing two performance criteria, response latency and energy consumption.The performance of PCIKNN is analyzed mathematically and evaluated through extensive experiments. Experimental results show that PCIKNN has better performance and scalability than the state-of-the-art.

Original languageEnglish (US)
Title of host publicationCIKM 2007 - Proceedings of the 16th ACM Conference on Information and Knowledge Management
Pages391-400
Number of pages10
DOIs
StatePublished - Dec 1 2007
Event16th ACM Conference on Information and Knowledge Management, CIKM 2007 - Lisboa, Portugal
Duration: Nov 6 2007Nov 9 2007

Publication series

NameInternational Conference on Information and Knowledge Management, Proceedings

Other

Other16th ACM Conference on Information and Knowledge Management, CIKM 2007
CountryPortugal
CityLisboa
Period11/6/0711/9/07

Fingerprint

Query processing
Query
K-nearest neighbor
Wireless sensor networks
Sensor
Sampling
Energy consumption
Monitoring
Surveillance
Military
Latency
Energy efficiency
Research work
Performance criteria
Experiment
Scalability

All Science Journal Classification (ASJC) codes

  • Decision Sciences(all)
  • Business, Management and Accounting(all)

Cite this

Fu, T. Y., Peng, W. C., & Lee, W. (2007). Optimizing parallel itineraries for KNN query processing in wireless sensor networks. In CIKM 2007 - Proceedings of the 16th ACM Conference on Information and Knowledge Management (pp. 391-400). (International Conference on Information and Knowledge Management, Proceedings). https://doi.org/10.1145/1321440.1321496
Fu, Tao Young ; Peng, Wen Chih ; Lee, Wang-chien. / Optimizing parallel itineraries for KNN query processing in wireless sensor networks. CIKM 2007 - Proceedings of the 16th ACM Conference on Information and Knowledge Management. 2007. pp. 391-400 (International Conference on Information and Knowledge Management, Proceedings).
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Fu, TY, Peng, WC & Lee, W 2007, Optimizing parallel itineraries for KNN query processing in wireless sensor networks. in CIKM 2007 - Proceedings of the 16th ACM Conference on Information and Knowledge Management. International Conference on Information and Knowledge Management, Proceedings, pp. 391-400, 16th ACM Conference on Information and Knowledge Management, CIKM 2007, Lisboa, Portugal, 11/6/07. https://doi.org/10.1145/1321440.1321496

Optimizing parallel itineraries for KNN query processing in wireless sensor networks. / Fu, Tao Young; Peng, Wen Chih; Lee, Wang-chien.

CIKM 2007 - Proceedings of the 16th ACM Conference on Information and Knowledge Management. 2007. p. 391-400 (International Conference on Information and Knowledge Management, Proceedings).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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Fu TY, Peng WC, Lee W. Optimizing parallel itineraries for KNN query processing in wireless sensor networks. In CIKM 2007 - Proceedings of the 16th ACM Conference on Information and Knowledge Management. 2007. p. 391-400. (International Conference on Information and Knowledge Management, Proceedings). https://doi.org/10.1145/1321440.1321496