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Erschienen in:
2009 | OriginalPaper | Buchkapitel
Fast Self-stabilization for Gradients
verfasst von : Jacob Beal, Jonathan Bachrach, Dan Vickery, Mark Tobenkin
Erschienen in: Distributed Computing in Sensor Systems
Verlag: Springer Berlin Heidelberg
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Gradients are distributed distance estimates used as a building block in many sensor network applications. In large or long-lived deployments, it is important for the estimate to self-stabilize in response to changes in the network or ongoing computations, but existing algorithms may repair very slowly, produce distorted estimates, or suffer large transients. The CRF-Gradient algorithm[1] addresses these shortcomings, and in this paper we prove that it self-stabilizes in
O
(
diameter
) time—more specifically, in 4 ·
diameter
/
c
+
k
seconds, where
k
is a small constant and
c
is the minimum speed of multi-hop message propagation.