The Distributed Averaging Consensus in Large Complex Networks
DEI PhD Student
DEI - Aula 3B
11 novembre 2011
Large complex networks are becoming even more attractive since they have applications in several disciplines such as computer science, social networks, biological systems etc. One of the most important topics to be investigated about large complex networks is the Distributed Averaging Consensus (DAC) problem, as it has many applications, e.g., in measurements-sharing in sensors networks, spread of ideas in human society or diffusion of information between computers. The most common parameter used to investigate the speed of consensus in the DAC problem is the algebraic connectivity of the network. In this work, another factor is considered, namely the Cheeger constant, which is a measure of the strength of connections among subsets of nodes in the network. Starting from this parameter, a new network model is proposed, called Countries model. We compare it, through simulation studies, with the well-known Watts-Strogatz model, where consensus spread is fast as this model shows the small-world property. We find that the two models have comparable behavior with respect to the consensus speed, the algebraic connectivity and the Cheeger constant.
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