Distributed algorithms to determine eigenvectors of matrices on spatially distributed networks

2020/11/23 by Nazar Emirov, Emirov, Nazar, Cheng Cheng +5
Computer Science · Physics and Astronomy · #Complex Network Analysis Techniques #Distributed #FOS: Computer and information sciences #Information Theory (cs.IT) #Opinion Dynamics and Social Influence #Parallel #Topological and Geometric Data Analysis #and Cluster Computing (cs.DC)

paper · pdf · doi:10.48550/arxiv.2011.11223

openalex publication_date 2020/11/23 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

Eigenvectors of matrices on a network have been used for understanding spectral clustering and influence of a vertex. For matrices with small geodesic-width, we propose a distributed iterative algorithm in this letter to find eigenvectors associated with their given eigenvalues. We also consider the implementation of the proposed algorithm at the vertex/agent level in a spatially distributed network.

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