COLR-Tree: Communication-Efficient Spatio-Temporal Indexing for a Sensor Data Web Portal
Y. Ahmad, and S. Nath. Proceedings of the 24th International Conference on Data Engineering, page 784-793. Cancún, Mexico, IEEE Computer Society Press, (April 2008)
Abstract
We present COLR-Tree, an abstraction layer designed to support efficient spatio-temporal queries on live data gathered from a large collection of sensors. We use COLR-Tree in a publicly-available sensor web portal to separate the concerns of sensor data management from the web portal application. COLR-Tree uses two techniques to optimize end-to-end latencies of users' queries by minimizing expensive data collection from sensors. First, it uses a novel technique to effectively cache aggregate results computed over sensor data with different expiry times. Second, it incorporates an efficient one-pass sampling algorithm with its range lookup to utilize cached data and compensate for occasional unavailability of sensors. We evaluate our implementation of COLR-Tree on SQL Server 2005 with a real, large workload from Windows Live Local. Our experiments demonstrate that COLR-Tree significantly improves both the end-to-end query performance and the number of sensors accessed compared to existing techniques.
%0 Conference Paper
%1 ahm08
%A Ahmad, Yanif
%A Nath, Suman
%B Proceedings of the 24th International Conference on Data Engineering
%C Cancún, Mexico
%D 2008
%I IEEE Computer Society Press
%K imported
%P 784-793
%T COLR-Tree: Communication-Efficient Spatio-Temporal Indexing for a Sensor Data Web Portal
%X We present COLR-Tree, an abstraction layer designed to support efficient spatio-temporal queries on live data gathered from a large collection of sensors. We use COLR-Tree in a publicly-available sensor web portal to separate the concerns of sensor data management from the web portal application. COLR-Tree uses two techniques to optimize end-to-end latencies of users' queries by minimizing expensive data collection from sensors. First, it uses a novel technique to effectively cache aggregate results computed over sensor data with different expiry times. Second, it incorporates an efficient one-pass sampling algorithm with its range lookup to utilize cached data and compensate for occasional unavailability of sensors. We evaluate our implementation of COLR-Tree on SQL Server 2005 with a real, large workload from Windows Live Local. Our experiments demonstrate that COLR-Tree significantly improves both the end-to-end query performance and the number of sensors accessed compared to existing techniques.
@inproceedings{ahm08,
abstract = {We present COLR-Tree, an abstraction layer designed to support efficient spatio-temporal queries on live data gathered from a large collection of sensors. We use COLR-Tree in a publicly-available sensor web portal to separate the concerns of sensor data management from the web portal application. COLR-Tree uses two techniques to optimize end-to-end latencies of users' queries by minimizing expensive data collection from sensors. First, it uses a novel technique to effectively cache aggregate results computed over sensor data with different expiry times. Second, it incorporates an efficient one-pass sampling algorithm with its range lookup to utilize cached data and compensate for occasional unavailability of sensors. We evaluate our implementation of COLR-Tree on SQL Server 2005 with a real, large workload from Windows Live Local. Our experiments demonstrate that COLR-Tree significantly improves both the end-to-end query performance and the number of sensors accessed compared to existing techniques.},
added-at = {2009-01-14T00:43:43.000+0100},
address = {Canc\'un, Mexico},
author = {Ahmad, Yanif and Nath, Suman},
biburl = {https://www.bibsonomy.org/bibtex/26a826a6c2ababcf839bdc0029159e657/dret},
booktitle = {Proceedings of the 24th International Conference on Data Engineering},
crossref = {icde2008},
description = {dret'd bibliography},
index = {ICDE 2008},
interhash = {c5ffd27414cb449efbc7aea5c904ffcb},
intrahash = {6a826a6c2ababcf839bdc0029159e657},
key = {Proceedings of the 24th International Conference on Data Engineering},
keywords = {imported},
month = {April},
pages = {784-793},
publisher = {IEEE Computer Society Press},
timestamp = {2009-01-14T00:43:51.000+0100},
title = {COLR-Tree: Communication-Efficient Spatio-Temporal Indexing for a Sensor Data Web Portal},
uri = {http://ieeexplore.ieee.org/search/wrapper.jsp?arnumber=4497487},
year = 2008
}