Network connectivity analysis via shortest paths

Abstract Complex systems of interacting components often can be modeled by a simple graph $$\mathcal {G}$$ that consists of a set of n nodes and a set of m edges. Such a graph can be represented by an adjacency matrix $$A\in \mathbb {R}^{n\times n}$$ , whose ( ij )th entry is one if there is an edge pointing from node i to node j , and is zero otherwise. The matrix A and its positive integer powers reveal important properties of the graph and allow the construction of the path length matrix L for the graph. The ( ij )th entry of L is the length of the shortest path from node i to node j ; if there is no path between these nodes, then the value of the entry is set to $$\infty$$ . We are interested in how well information flows via shortest paths of the graph. This can be studied with the aid of the path length matrix. The path length matrix allows the definition of several measures of communication in the network defined by the graph such as the global K -efficiency, which considers shortest paths that are made up of at most K edges for some $$K<n$$ , as well as the number of such shortest paths. Novel notions of connectivity introduced in this paper help us understand the importance of specific edges for the flow of information through the graph. This is of interest when seeking to simplify a network by removing selected edges or trying to assess the sensitivity of the flow of information to changes due to exterior causes such as a traffic stoppage on a road network.

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Publication Details

Journal
Numerical Algorithms
Published
2025-10-02
DOI
https://doi.org/10.1007/s11075-025-02225-3
Primary Topic
Complex Network Analysis Techniques
Type
article
Field-Weighted Citation Impact
0.00

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article

Network connectivity analysis via shortest paths

Silvia Noschese, Lothar Reichel
Numerical Algorithms
Complex Network Analysis Techniques
article

Network connectivity analysis via shortest paths

Silvia Noschese, Lothar Reichel
article en

Abstract

Abstract Complex systems of interacting components often can be modeled by a simple graph $$\mathcal {G}$$ that consists of a set of n nodes and a set of m edges. Such a graph can be represented by an adjacency matrix $$A\in \mathbb {R}^{n\times n}$$ , whose ( ij )th entry is one if there is an edge pointing from node i to node j , and is zero otherwise. The matrix A and its positive integer powers reveal important properties of the graph and allow the construction of the path length matrix L for the graph. The ( ij )th entry of L is the length of the shortest path from node i to node j ; if there is no path between these nodes, then the value of the entry is set to $$\infty$$ . We are interested in how well information flows via shortest paths of the graph. This can be studied with the aid of the path length matrix. The path length matrix allows the definition of several measures of communication in the network defined by the graph such as the global K -efficiency, which considers shortest paths that are made up of at most K edges for some $$K<n$$ , as well as the number of such shortest paths. Novel notions of connectivity introduced in this paper help us understand the importance of specific edges for the flow of information through the graph. This is of interest when seeking to simplify a network by removing selected edges or trying to assess the sensitivity of the flow of information to changes due to exterior causes such as a traffic stoppage on a road network.

Numerical Algorithms
Kent State University (US), Sapienza University of Rome (IT)
Istituto Nazionale di Alta Matematica "Francesco Severi", European Commission, Sapienza Università di Roma, Gruppo Nazionale per il Calcolo Scientifico
Openalex Percentile: Top 78%
Complex Network Analysis Techniques
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