Fault-tolerant aggregation: Flow-Updating meets Mass-Distribution

Paulo Sérgio Almeida, Carlos Baquero, Martín Farach-Colton, Paulo Jesus, Miguel A. Mosteiro

    Research output: Contribution to journalArticlepeer-review


    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.

    Original languageEnglish (US)
    Pages (from-to)281-291
    Number of pages11
    JournalDistributed Computing
    Issue number4
    StatePublished - Aug 1 2017


    • Aggregate computation
    • Communication networks
    • Distributed computing
    • Radio networks

    ASJC Scopus subject areas

    • Theoretical Computer Science
    • Hardware and Architecture
    • Computer Networks and Communications
    • Computational Theory and Mathematics


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