A Hierarchy-Based Fault-Local Stabilizing Algorithm for Tracking in Sensor Networks

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In this paper, the authors 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.