Distributed Estimation and Control of Algebraic Connectivity Over Random Graphs

DOI10.1109/TSP.2014.2355778zbMATH Open1394.94972DBLPjournals/tsp/LorenzoB14arXiv1309.3200WikidataQ59009799 ScholiaQ59009799MaRDI QIDQ4579540

Sergio Barbarossa, Paolo Di Lorenzo

Publication date: 22 August 2018

Published in: IEEE Transactions on Signal Processing (Search for Journal in Brave)

Abstract: In this paper we propose a distributed algorithm for the estimation and control of the connectivity of ad-hoc networks in the presence of a random topology. First, given a generic random graph, we introduce a novel stochastic power iteration method that allows each node to estimate and track the algebraic connectivity of the underlying expected graph. Using results from stochastic approximation theory, we prove that the proposed method converges almost surely (a.s.) to the desired value of connectivity even in the presence of imperfect communication scenarios. The estimation strategy is then used as a basic tool to adapt the power transmitted by each node of a wireless network, in order to maximize the network connectivity in the presence of realistic Medium Access Control (MAC) protocols or simply to drive the connectivity toward a desired target value. Numerical results corroborate our theoretical findings, thus illustrating the main features of the algorithm and its robustness to fluctuations of the network graph due to the presence of random link failures.

Full work available at URL: https://arxiv.org/abs/1309.3200

Mathematics Subject Classification ID

Applications of graph theory (05C90) Random graphs (graph-theoretic aspects) (05C80) Applications of graph theory to circuits and networks (94C15)