Distributed and Parallel Databases

, Volume 29, Issue 1, pp 151-183

First online:

Stream engines meet wireless sensor networks: cost-based planning and processing of complex queries in AnduIN

  • Daniel KlanAffiliated withDatabases and Information Systems Group, Ilmenau University of Technology Email author 
  • , Marcel KarnstedtAffiliated withDERI, NUI Galway
  • , Katja HoseAffiliated withMax-Planck-Institut für Informatik
  • , Liz Ribe-BaumannAffiliated withDatabases and Information Systems Group, Ilmenau University of Technology
  • , Kai-Uwe SattlerAffiliated withDatabases and Information Systems Group, Ilmenau University of Technology

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Wireless sensor networks are powerful, distributed, self-organizing systems used for event and environmental monitoring. In-network query processors like TinyDB offer a user friendly SQL-like application development. Due to the sensor nodes’ resource limitations, monolithic approaches often support only a restricted number of operators. For this reason, complex processing is typically outsourced to the base station. Nevertheless, previous work has shown that complete or partial in-network processing can be more efficient than the base station approach. In this paper, we introduce AnduIN, a system for developing, deploying, and running complex in-network processing tasks. In particular, we present the query planning and execution strategies used in AnduIN, a system combining sensor-local in-network processing and a data stream engine. Query planning employs a multi-dimensional cost model taking energy consumption into account and decides autonomously which query parts will be processed within the sensor network and which parts will be processed at the central instance.


Sensor networks Data streams Power awareness Distributed computation In-network query processing Query planning