Fault-Tolerant Aggregation: Flow-Updating Meets Mass-Distribution

  • Paulo Sérgio Almeida
  • Carlos Baquero
  • Martín Farach-Colton
  • Paulo Jesus
  • Miguel A. Mosteiro
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7109)

Abstract

Flow-Updating (FU) is a fault-tolerant technique that has proved to be efficient in practice for the distributed computation of aggregate functions in communication networks where individual processors do not have access to global information. Previous distributed aggregation protocols, based on repeated sharing of input values (or mass) among processors, sometimes called Mass-Distribution (MD) protocols, are not resilient to communication failures (or message loss) because such failures yield a loss of mass.

In this paper, we present a protocol which we call Mass-Distribution with Flow-Updating (MDFU). We obtain MDFU by applying FU techniques to classic MD. We analyze the convergence time of MDFU showing that stochastic message loss produces low overhead. This is the first convergence proof of an FU-based algorithm. We evaluate MDFU experimentally, comparing it with previous MD and FU protocols, and verifying the behavior predicted by the analysis. Finally, given that MDFU incurs a fixed deviation proportional to the message-loss rate, we adjust the accuracy of MDFU heuristically in a new protocol called MDFU with Linear Prediction (MDFU-LP). The evaluation shows that both MDFU and MDFU-LP behave very well in practice, even under high rates of message loss and even changing the input values dynamically.

Keywords

Aggregate computation Distributed computing Radio networks Communication networks 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Paulo Sérgio Almeida
    • 1
  • Carlos Baquero
    • 1
  • Martín Farach-Colton
    • 2
    • 3
  • Paulo Jesus
    • 1
  • Miguel A. Mosteiro
    • 2
    • 4
  1. 1.Depto. de Informática (CCTC-DI)Universidade do MinhoBragaPortugal
  2. 2.Dept. of Computer ScienceRutgers UniversityPiscatawayUSA
  3. 3.Tokutek, Inc.USA
  4. 4.LADyR, GSyCUniversidad Rey Juan CarlosMadridSpain

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