• DocumentCode
    1763658
  • Title

    The Generalized Loneliness Detector and Weak System Models for k-Set Agreement

  • Author

    Biely, Martin ; Robinson, Peter ; Schmid, Ulrich

  • Author_Institution
    IC IIF LSR, EPFL, Lausanne, Switzerland
  • Volume
    25
  • Issue
    4
  • fYear
    2014
  • fDate
    41730
  • Firstpage
    1078
  • Lastpage
    1088
  • Abstract
    This paper presents two weak partially synchronous system models Manti(n-k) and Msink(n-k), which are just strong enough for solving k-set agreement: We introduce the generalized (n-k)-loneliness failure detector L(k), which we first prove to be sufficient for solving k-set agreement, and show that L(k) but not L(k-1) can be implemented in both models. Manti(n-k) and Msink(n-k) are hence the first message passing models that lie between models where Ω (and therefore consensus) can be implemented and the purely asynchronous model. We also address k-set agreement in anonymous systems, that is, in systems where (unique) process identifiers are not available. Since our novel k -set agreement algorithm using L(k) also works in anonymous systems, it turns out that the loneliness failure detector L=L(n-1) introduced by Delporte et al. is also the weakest failure detector for set agreement in anonymous systems. Finally, we analyze the relationship between L(k) and other failure detectors suitable for solving k-set agreement.
  • Keywords
    message passing; set theory; generalized loneliness detector; k-set agreement algorithm; loneliness failure detector; message passing model; process identifiers; weak partially synchronous system models; weak system models; Biological system modeling; Computational modeling; Computer crashes; Delays; Detectors; Electronic mail; Message passing; Distributed systems, models of computation;
  • fLanguage
    English
  • Journal_Title
    Parallel and Distributed Systems, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1045-9219
  • Type

    jour

  • DOI
    10.1109/TPDS.2013.77
  • Filename
    6482555