@article{3028495,
    title = "Building efficient aggregation trees for sensor network event-monitoring queries",
    author = "Deligiannakis, A. and Kotidis, Y. and Stoumpos, V. and Delis, A.",
    journal = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
    year = "2009",
    volume = "5659 LNCS",
    pages = "63-76",
    doi = "10.1007/978-3-642-02903-5_7",
    keywords = "Data aggregation;  Energy consumption;  Event monitoring;  Large class;  Monitoring applications;  Query results, Agglomeration;  Data processing;  Monitoring;  Sensor networks;  Sensor nodes;  Telecommunication equipment;  Wireless telecommunication systems, Wireless sensor networks",
    abstract = "In this paper we present algorithms for building and maintaining efficient aggregation trees that provide the conduit to disseminate data required for processing monitoring queries in a wireless sensor network. While prior techniques base their operation on the assumption that the sensor nodes that collect data relevant to a specified query need to include their measurements in the query result at every query epoch, in many event monitoring applications such an assumption is not valid. We introduce and formalize the notion of event monitoring queries and demonstrate that they can capture a large class of monitoring applications. We then show techniques which, using a small set of intuitive statistics, can compute aggregation trees that minimize important resources such as the number of messages exchanged among the nodes or the overall energy consumption. Our experiments demonstrate that our techniques can organize the data aggregation process while utilizing significantly lower resources than prior approaches. © 2009 Springer Berlin Heidelberg."
}