MIST: Distributed Indexing and Querying in Sensor Networks using Statistical Models

Summary: MIST builds an in-network hierarchy of composite Markov/HMM models, avoiding transmission of every sensor model to a base station. Average/extreme aggregates enable bounded range, top-1, and model 1-NN queries with substantially lower communication cost. (summarized by gpt-5.6-luna on Jul 24 2026)

Paper ID: 9826
Venue: VLDB
Year: 2007
Pagerank: 5.093636e-05
Overall Rank: 12,674 | 13.05%
DOI: -

Incoming Non-self Citations Over Time

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Authors

1. Arnab Bhattacharya (University of California Santa Barbara)
2. Anand Meka (University of California Santa Barbara)
3. Ambuj K. Singh (University of California Santa Barbara)

BibTeX Citation

@article{bhattacharya_vldb07,
        title = {{MIST: Distributed Indexing and Querying in Sensor Networks using Statistical Models}},
        author = {Bhattacharya, Arnab and Meka, Anand and Singh, Ambuj K.},
        journal = {PVLDB},
        series = {{VLDB} '07},
        pages = {854--865},
        year = {2007}
}

Incoming Citations (Sorted by Pagerank)

Showing 0 of 0 citing papers.

Rank	Citing Paper	Year	Venue	Pagerank

Outgoing Citations (Sorted by Pagerank)

Showing 6 of 6 cited papers.

Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

Rank	Cited Paper	Year	Venue	Pagerank
2	R-Trees: A Dynamic Index Structure For Spatial Searching	1984	SIGMOD	0.0020210012
56	M-tree: An Efficient Access Method for Similarity Search in Metric Spaces	1997	VLDB	0.00040719947
337	Model-Driven Data Acquisition in Sensor Networks	2004	VLDB	0.00020783399
646	Adaptive Precision Setting for Cached Approximate Values	2001	SIGMOD	0.00015335457
891	Adaptive Stream Resource Management Using Kalman Filters	2004	SIGMOD	0.00013382575
5,260	Energy-Efficient Monitoring of Extreme Values in Sensor Networks	2006	SIGMOD	6.2956086e-05

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