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Stably Computable Properties of Network Graphs

  • Dana Angluin
  • James Aspnes
  • Melody Chan
  • Michael J. Fischer
  • Hong Jiang
  • René Peralta
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3560)

Abstract

We consider a scenario in which anonymous, finite-state sensing devices are deployed in an ad-hoc communication network of arbitrary size and unknown topology, and explore what properties of the network graph can be stably computed by the devices. We show that they can detect whether the network has degree bounded by a constant d, and, if so, organize a computation that achieves asymptotically optimal linear memory use. We define a model of stabilizing inputs to such devices and show that a large class of predicates of the multiset of final input values are stably computable in any weakly-connected network. We also show that nondeterminism in the transition function does not increase the class of stably computable predicates.

Keywords

Span Tree Network Graph Graph Property Directed Cycle Leader Election 
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 2005

Authors and Affiliations

  • Dana Angluin
    • 1
  • James Aspnes
    • 1
  • Melody Chan
    • 1
  • Michael J. Fischer
    • 1
  • Hong Jiang
    • 1
  • René Peralta
    • 1
  1. 1.Yale University 

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