In-network execution of monitoring queries in sensor networks

Sensor networks are widely used in many applications for collecting information from the physical environment. In these applications, it is usually necessary to track the relationships between sensor data readings within a time window to detect events of interest. However, it is difficult to detect such events by using the common aggregate or selection queries. We address the problem of processing window self-join in order to detect events of interest. Self-joins are useful in tracking correlations between different sensor readings, which can indicate an event of interest. We propose the Two-Phase Self-Join (TPSJ) scheme to efficiently evaluate self-join queries for event detection in sensor networks. Our TPSJ scheme takes advantage of the properties of the events and carries out data filtering during in-network processing. We discuss TPSJ execution with one window and we extend it for continuous event monitoring. Our experimental evaluation results indicate that the TPSJ scheme is ef...

• Type: Conference
• Year: 2007
• Where: SIGMOD
• Authors: Xiaoyan Yang, Hock-Beng Lim, M. Tamer Özsu, Kian-Lee Tan
• Keywords: Database, Keywords Sensor Networks, Scheme Takes Advantage, Sensor Data Readings, SIGMOD 2007