Publication | Closed Access
Distributed Finite-Time Computation of Digraph Parameters: Left-Eigenvector, Out-Degree and Spectrum
93
Citations
35
References
2015
Year
Spectral TheoryCluster ComputingGraph SparsityDirected GraphEngineeringDistributed AlgorithmsNetwork ParametersNetwork AnalysisComputational ComplexityDistributed Ai SystemDigraph ParametersDynamic NetworkStructural Graph TheoryParallel ComputingDistributed ModelGlobal ParametersComputer EngineeringComputer ScienceGraph AlgorithmDistributed ComputationDistributed ProcessingNetwork ScienceGraph TheorySpectral AnalysisParallel ProgrammingLarge-scale Network
Many of the algorithms that have been proposed in the field of distributed computation rely on assumptions that require nodes to be aware of some global parameters. In this paper, we propose algorithms to compute some network parameters in a distributed fashion and in a finite number of steps. More specifically, given an arbitrary strongly connected network of interconnected nodes, by adapting a distributed finite-time approach, we develop distributed strategies that enable nodes to compute the following network parameters: the left-eigenvector, the out-degree, and the spectrum of weighted adjacency matrices.
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