Distributed Navigation Algorithms for Sensor Networks

TL;DR

This paper introduces efficient distributed algorithms for sensor network navigation that use a skeleton graph to find approximate safe paths with significantly reduced communication costs, supported by theoretical guarantees and simulations.

Contribution

It presents a novel skeleton graph approach for low-cost distributed navigation in sensor networks with proven approximation quality.

Findings

Reduced communication cost using skeleton graphs.

Theoretical bounds on path approximation quality.

Simulation results demonstrating algorithm effectiveness.

Abstract

We propose efficient distributed algorithms to aid navigation of a user through a geographic area covered by sensors. The sensors sense the level of danger at their locations and we use this information to find a safe path for the user through the sensor field. Traditional distributed navigation algorithms rely upon flooding the whole network with packets to find an optimal safe path. To reduce the communication expense, we introduce the concept of a skeleton graph which is a sparse subset of the true sensor network communication graph. Using skeleton graphs we show that it is possible to find approximate safe paths with much lower communication cost. We give tight theoretical guarantees on the quality of our approximation and by simulation, show the effectiveness of our algorithms in realistic sensor network situations.