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DIST: a distributed spatio-temporal index structure for sensor networks
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Source Conference on Information and Knowledge Management archive
Proceedings of the 14th ACM international conference on Information and knowledge management table of contents
Bremen, Germany
SESSION: Paper session KM-2 (knowledge management): index structures table of contents
Pages: 139 - 146  
Year of Publication: 2005
ISBN:1-59593-140-6
Authors
Anand Meka  University of California, Santa Barbara, Santa Barbara, CA
Ambuj Singh  University of California, Santa Barbara, Santa Barbara, CA
Sponsors
ACM: Association for Computing Machinery
SIGIR: ACM Special Interest Group on Information Retrieval
Publisher
ACM  New York, NY, USA
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ABSTRACT

We consider the general problem of tracking moving objects in sensor networks. The specific application we consider is that of tracking a chemical plume moving over a large infrastructure network. We present a distributed index structure DIST that stores and updates distributed summaries as the plume moves. We present algorithms for range queries on the history of the plume. DIST localizes information with respect to time and space using a hierarchy that scales with the plume size. The highlight of our work is an analytical model to predict the cost of query algorithms based on the query location, query size, and plume's spatio-temporal distribution. Using this model, our adaptive scheme chooses the optimal scheme. Experimental results show that DIST outperforms alternative techniques in query, update, and storage costs, and scales well with the number of plumes.


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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