Detecting Separation in Robotic and Sensor Networks
Abstract
In this paper we consider the problem of monitoring detecting separation of agents from a base station in robotic and sensor networks. Such separation can be caused by mobility and/or failure of the agents. While separation/cut detection may be performed by passing messages between a node and the base in static networks, such a solution is impractical for networks with high mobility, since routes are constantly changing. We propose a distributed algorithm to detect separation from the base station. The algorithm consists of an averaging scheme in which every node updates a scalar state by communicating with its current neighbors. We prove that if a node is permanently disconnected from the base station, its state converges to . If a node is connected to the base station in an average sense, even if not connected in any instant, then we show that the expected value of its state converges to a positive number. Therefore, a node can detect if it has been separated from the base station by monitoring its state. The effectiveness of the proposed algorithm is demonstrated through simulations, a real system implementation and experiments involving both static as well as mobile networks.
Cite
@article{arxiv.1102.3396,
title = {Detecting Separation in Robotic and Sensor Networks},
author = {Chenda Liao and Harshavardhan Chenji and Prabir Barooah and Radu Stoleru and Tamás Kalmár-Nagy},
journal= {arXiv preprint arXiv:1102.3396},
year = {2011}
}