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Data Cleansing and Selective Query Processing in Sensor Networks

Authors:
Maria Drougka
Theodore Tsiligiridis

Keywords: Data cleansing, selective query, Wireless Sensor Network

Abstract:
Wireless sensor networks have been widely used in numerous monitoring applications and real life phenomena. Due to the low quality of sensors and random effects of the environment, the collected sensor data is subject to several sources of errors. Such errors may seriously impact the answer to any query posed to the sensors and therefore, it is very critical to clean the sensor data before using them to answer queries or conduct data analysis. Well known data cleansing approaches, are used to meet the requirements of both energy efficiency and quick response time in many sensor related applications. Several energy saving methods based on clustering sensors, so that sensors communicate information only to cluster-heads and then the cluster-heads communicate the aggregated information to the processing center are reviewed, and discussed. We focus on the distribution of sink operation among sensor nodes and specify the criteria of selecting effective cluster-heads that enable both balanced and low energy consumption in data query and collection. As a result of the effective selection of cluster-heads, both balanced and decreased energy consumption are superior compared with the conventional retrieval model, which is not using cluster-heads, because their use provide maximum data aggregation among various sensors, and it alleviates the heavy energy consumption near the sink.

Pages: 76 to 81

Copyright: Copyright (c) IARIA, 2012

Publication date: January 30, 2012

Published in: conference

ISSN: 2308-393X

ISBN: 978-1-61208-178-6

Location: Valencia, Spain

Dates: from January 30, 2012 to February 4, 2012