Fault-Tolerant Aggregation by Flow Updating

  • Paulo Jesus
  • Carlos Baquero
  • Paulo Sérgio Almeida
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5523)


Data aggregation plays an important role in the design of scalable systems, allowing the determination of meaningful system-wide properties to direct the execution of distributed applications. In the particular case of wireless sensor networks, data collection is often only practicable if aggregation is performed. Several aggregation algorithms have been proposed in the last few years, exhibiting different properties in terms of accuracy, speed and communication tradeoffs. Nonetheless, existing approaches are found lacking in terms of fault tolerance. In this paper, we introduce a novel fault-tolerant averaging based data aggregation algorithm. It tolerates substantial message loss (link failures), while competing algorithms in the same class can be affected by a single lost message. The algorithm is based on manipulating flows (in the graph theoretical sense), that are updated using idempotent messages, providing it with unique robustness capabilities. Furthermore, evaluation results obtained by comparing it with other averaging approaches have revealed that it outperforms them in terms of time and message complexity.


Wireless Sensor Network Overlay Network Aggregation Function Link Failure Node Failure 
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

© IFIP International Federation for Information Processing 2009

Authors and Affiliations

  • Paulo Jesus
    • 1
  • Carlos Baquero
    • 1
  • Paulo Sérgio Almeida
    • 1
  1. 1.University of Minho (CCTC-DI)BragaPortugal

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