Medians and beyond: new aggregation techniques for sensor networks

Wireless sensor networks offer the potential to span and monitor large geographical areas inexpensively. Sensors, however, have significant power constraint (battery life), making communication very expensive. Another important issue in the context of sensorbased information systems is that individual sensor readings are inherently unreliable. In order to address these two aspects, sensor database systems like TinyDB and Cougar enable in-network data aggregation to reduce the communication cost and improve reliability. The existing data aggregation techniques, however, are limited to relatively simple types of queries such as SUM, COUNT, AVG, and MIN/MAX. In this paper we propose a data aggregation scheme that significantly extends the class of queries that can be answered using sensor networks. These queries include (approximate) quantiles, such as the median, the most frequent data values, such as the consensus value, a histogram of the data distribution, as well as range queries....

• Type: Conference
• Year: 2004
• Where: SENSYS
• Authors: Nisheeth Shrivastava, Chiranjeeb Buragohain, Divyakant Agrawal, Subhash Suri
• Keywords: Data Aggregation, Sensor, Sensor Networks, SENSYS 2004