Hierarchical In-Network Data Aggregation with Quality Guarantees

  • Antonios Deligiannakis
  • Yannis Kotidis
  • Nick Roussopoulos
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2992)


Earlier work has demonstrated the effectiveness of in-network data aggregation in order to minimize the amount of messages exchanged during continuous queries in large sensor networks. The key idea is to build an aggregation tree, in which parent nodes aggregate the values received from their children. Nevertheless, for large sensor networks with severe energy constraints the reduction obtained through the aggregation tree might not be sufficient. In this paper we extend prior work on in-network data aggregation to support approximate evaluation of queries to further reduce the number of exchanged messages among the nodes and extend the longevity of the network. A key ingredient to our framework is the notion of the residual mode of operation that is used to eliminate messages from sibling nodes when their cumulative change is small. We introduce a new algorithm, based on potential gains, which adaptively redistributes the error thresholds to those nodes that benefit the most and tries to minimize the total number of transmitted messages in the network. Our experiments demonstrate that our techniques significantly outperform previous approaches and reduce the network traffic by exploiting the super-imposed tree hierarchy.


Sensor Network Sensor Node Root Node Active Node Transmitted Message 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2004

Authors and Affiliations

  • Antonios Deligiannakis
    • 1
  • Yannis Kotidis
    • 2
  • Nick Roussopoulos
    • 1
  1. 1.University of MarylandCollege ParkUSA
  2. 2.AT&T Labs-ResearchFlorham ParkUSA

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