Analysis of a network's asymptotic behavior via its structure involving its strongly connected components. (1st July 2020)

• Record Type: Journal Article
• Authors: Treur, Jan
• Editors: Cherifi, Hocine; Rocha, Luis M.; Wasserman, Stanley
• Is Part Of: Network science. Volume 8(2020)Supplement 1
• Page Start: S82
• Page End: S109
• Publication Date: 2020-07-01
• Subjects: Hocine Cherifi, -- Luis Rocha, -- Stanley Wasserman; asymptotic network behavior, -- strongly connected components, -- relating network structure and network behavior; Social networks -- Research -- Periodicals; System analysis -- Periodicals; System theory -- Periodicals; Computer science -- Periodicals; 003.72
• DOI: 10.1017/nws.2019.24
• Languages: English
• ISSNs: 2050-1242

Abstract

Abstract: In this paper, it is addressed how network structure can be related to asymptotic network behavior. If such a relation is studied, that usually concerns only strongly connected networks and only linear functions describing the dynamics. In this paper, both conditions are generalized. A couple of general theorems is presented that relates asymptotic behavior of a network to the network's structure characteristics. The network structure characteristics, on the one hand, concern the network's strongly connected components and their mutual connections; this generalizes the condition of being strongly connected to a very general condition. On the other hand, the network structure characteristics considered generalize from linear functions to functions that are normalized, monotonic, and scalar-free, so that many nonlinear functions are also covered. Thus, the contributed theorems generalize the existing theorems on the relation between network structure and asymptotic network behavior addressing only specific cases such as acyclic networks, fully, and strongly connected networks, and theorems addressing only linear functions. This paper was invited as an extended (by more than 45%) version of a Complex Networks'18 conference paper. In the discussion section, the differences are explained in more detail.