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سند علمی

Modeling Scalability in Distributed Self-Stabilization: The Case of Graph Linearization

Dominik Gall, Riko Jacob, Andrea Richa, Christian Scheideler, Stefan Schmid, Hanjo Täubig

چکیده

This paper investigates how to efficiently and locally linearize graphs—i.e., how to build a sorted list of the nodes of a connected graph—in a distributed and self-stabilizing manner. This problem has many interesting application domains; for instance, self-stabilizing algorithms for graph linearization can serve as a building block to construct robust peer-to-peer overlays. A foremost question addressed in this paper is how to measure the efficiency of a given algorithm. We introduce a new model that takes into account the parallel complexity of a protocol. Our model avoids the scalability problems and bottlenecks of existing frameworks. We also propose two variants of a simple, local linearization algorithm. For each of these variants, we present extensive formal analyses 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. In particular, we show that one of the proposed algorithms achieves near-optimal parallel time complexity under such a greedy selection. We validate the behavior of these algorithms by experiments which confirm our formal findings and indicate that the runtimes may in fact be better in practice.

اسناد مشابه

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