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Summary: A Hierarchy-based Fault-local Stabilizing Algorithm
for Tracking in Sensor Networks
Murat Demirbas Anish Arora
Computer Science & Engineering
The Ohio State University
Columbus, OH 43210, USA
{demirbas, anish}@cis.ohio-state.edu
Tina Nolte Nancy Lynch
MIT Computer Science &
Artificial Intelligence Laboratory
Cambridge, MA 02139, USA
{tnolte, lynch}@theory.csail.mit.edu
Abstract
In this paper, we introduce the concept of hierarchy-based fault-local stabilization and a novel
self-healing/fault-containment technique and apply them in Stalk. Stalk is an algorithm for
tracking in sensor networks that maintains a data structure on top of an underlying hierarchical
partitioning of the network. Starting from an arbitrarily corrupted state, Stalk satisfies its
specification within time and communication cost proportional to the size of the faulty region,
defined in terms of levels of the hierarchy where faults have occurred. This local stabilization is
achieved by slowing propagation of information as the levels of the hierarchy underlying Stalk
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