Time Complexity of Distributed Topological Self-stabilization: The Case of Graph Linearization

Time Complexity of Distributed Topological Self-stabilization: The Case of Graph Linearization

Abstract

Topological self-stabilization is an important concept to build robust open distributed systems (such as peer-to-peer systems) where nodes can organize themselves into meaningful network topologies. The goal is to devise distributed algorithms that converge quickly to such a desirable topology, independently of the initial network state. This paper proposes a new model to study the parallel convergence time. Our model sheds light on the achievable parallelism by avoiding bottlenecks of existing models that can yield a distorted picture. As a case study, we consider local graph linearization—i.e., how to build a sorted list of the nodes of a connected graph in a distributed and self-stabilizing manner. We propose two variants of a simple algorithm, and provide an extensive formal analysis of their worst-case and best-case parallel time complexities, as well as their performance under a greedy selection of the actions to be executed.

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Authors
  • Gall, Dominik
  • Jacob, Riko
  • Richa, Andrea
  • Scheideler, Christian
  • Schmid, Stefan
  • Täubig, Hanjo
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Supplemental Material
Shortfacts
Category
Paper in Conference Proceedings or in Workshop Proceedings (Paper)
Event Title
9th Latin American Theoretical Informatics Symposium (LATIN)
Divisions
Communication Technologies
Subjects
Informatik Allgemeines
Event Location
Oaxaca, Mexico
Event Type
Conference
Event Dates
April 2010
Date
2010
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