Many challenging tasks in sensor networks, including sensor calibration, ranking of nodes, monitoring, event region detection, collaborative filtering, collaborative signal processing, etc. can be formulated as a problem of solving a linear system of equations. Several recent works propose different distributed algorithms for solving to these problems, usually by linear iterative numerical methods. In this work, we extend the settings of the above approaches, by adding another dimension to the problem. Specifically, we are interested in self-stabilizing algorithms, that continuously run and converge to a solution from any initial starting state. This aspect of the problem is highly important because of the dynamic nature of the network and the frequent changes in the measured environment. In this paper, we link together algorithms from two different domains. On the one hand, we use the rich linear algebra literature of linear iterative methods for solving systems of linear equations, ...
Ezra N. Hoch, Danny Bickson, Danny Dolev