Results 1 to 10 of about 1,009,188 (24)

Optimization of robustness based on reinforced nodes in a modular network [PDF]

, 2021
Many systems such as critical infrastructure exhibit a modular structure with many links within the modules and few links between them. One approach to increase the robustness of these systems is to reinforce a fraction of the nodes in each module, so that the reinforced nodes provide additional needed sources for themselves as well as for their nearby
arxiv   +1 more source

Value of peripheral nodes in controlling multilayer networks [PDF]

Phys. Rev. E 93, 012309 (2016), 2015
We analyze the controllability of a two-layer network, where driver nodes can be chosen randomly only from one layer. Each layer contains a scale-free network with directed links and the node dynamics depends on the incoming links from other nodes.
arxiv   +1 more source

Growing network with j-redirection [PDF]

Eur. Phys. Lett. 77 (2007) 58002, 2006
A model for growing information networks is introduced where nodes receive new links through j-redirection, i.e. the probability for a node to receive a link depends on the number of paths of length j arriving at this node. In detail, when a new node enters the network, it either connects to a randomly selected node, or to the j -ancestor of this ...
arxiv   +1 more source

Neighborhood-based Bridge Node Centrality Tuple for Preferential Vaccination of Nodes [PDF]

arXiv, 2023
We investigate the use of a recently proposed centrality tuple called the Neighborhood-based Bridge Node Centrality (NBNC) tuple to choose nodes for preferential vaccination so that such vaccinated nodes could provide herd immunity and reduce the spreading rate of infections in a complex real-world network.
arxiv  

Network Representation Learning: From Preprocessing, Feature Extraction to Node Embedding [PDF]

arXiv, 2021
Network representation learning (NRL) advances the conventional graph mining of social networks, knowledge graphs, and complex biomedical and physics information networks. Over dozens of network representation learning algorithms have been reported in the literature.
arxiv  

Network Growth From Global and Local Influential Nodes [PDF]

arXiv, 2021
In graph theory and network analysis, node degree is defined as a simple but powerful centrality to measure the local influence of node in a complex network. Preferential attachment based on node degree has been widely adopted for modeling network growth.
arxiv  

Using Spectral Radius Ratio for Node Degree to Analyze the Evolution of Scale Free Networks and Small World Networks [PDF]

, 2015
In this paper, we show the evaluation of the spectral radius for node degree as the basis to analyze the variation in the node degrees during the evolution of scale-free networks and small-world networks. Spectral radius is the principal eigenvalue of the adjacency matrix of a network graph and spectral radius ratio for node degree is the ratio of the ...
arxiv   +1 more source

Algorithms for Influence Maximization in Socio-Physical Networks [PDF]

arXiv, 2020
Given a directed graph (representing a social network), the influence maximization problem is to find k nodes which, when influenced (or activated), would maximize the number of remaining nodes that get activated. In this paper, we consider a more general version of the problem that includes an additional set of nodes, termed as physical nodes, such ...
arxiv  

A Vibrational Approach to Node Centrality and Vulnerability in Complex Networks [PDF]

Physica A 389 (2010) 3648-3660, 2009
We propose a new measure of vulnerability of a node in a complex network. The measure is based on the analogy in which the nodes of the network are represented by balls and the links are identified with springs. We define the measure as the node displacement, or the amplitude of vibration of each node, under fluctuation due to the thermal bath in which
arxiv   +1 more source

A Tunable Mechanism for Identifying Trusted Nodes in Large Scale Distributed Networks [PDF]

, 2012
In this paper, we propose a simple randomized protocol for identifying trusted nodes based on personalized trust in large scale distributed networks. The problem of identifying trusted nodes, based on personalized trust, in a large network setting stems from the huge computation and message overhead involved in exhaustively calculating and propagating ...
arxiv   +1 more source