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Distributed network size estimation and average degree estimation and control in networks isomorphic to directed graphs

Authors: Shames, I.; Charalambous, T.; Hadjicostis, Christoforos N.; Johansson, M.; Shames, I.; Charalambous, T.; Hadjicostis, Christoforos N.; +1 Authors

Distributed network size estimation and average degree estimation and control in networks isomorphic to directed graphs

Abstract

Many properties of interest in graph structures are based on the nodes' average degree (i.e., the average number of edges incident to/from each node). In this work, we present asynchronous distributed algorithms, based on ratio consensus, that can be used to accurately estimate the number of nodes in a multi-component system whose communication topology is described by a directed graph. In addition, we describe an asynchronous distributed algorithm that allows each node to introduce or terminate links in order to reach a target average degree in the network. Such an approach can be useful in many realistic scenarios; for example, for the introduction and removal of renewable energy resources in a power network, while maintaining an average degree that fulfils some structural and dynamical properties and/or optimises some performance indicators of the network. The effectiveness of the proposed algorithms is demonstrated via illustrative examples.

Country
Cyprus
Keywords

Performance indicators, Communication, Asynchronous distributed algorithms, Renewable energy resources, Benchmarking, Distributed networks, Dynamical properties, Communication topologies, Multi-component systems, Realistic scenario, Estimation, Graph structures, Algorithms, Directed graphs

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Powered by OpenAIRE graph
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
40
Top 10%
Top 10%
Top 10%
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