scholarly journals Analysis of Basic Features in Dynamic Network Models

Entropy ◽  
2018 ◽  
Vol 20 (9) ◽  
pp. 681 ◽  
Author(s):  
Pedro Zufiria ◽  
Iker Barriales-Valbuena
Keyword(s):  
Random Network ◽  
Density Ratio ◽  
Dynamic Network ◽  
Network Models ◽  
Clustering Coefficient ◽  
Edge Density ◽  
Mathematical Framework ◽  
Complexity Measures ◽  
Dynamic Network Models ◽  
Link Density

Time evolving Random Network Models are presented as a mathematical framework for modelling and analyzing the evolution of complex networks. This framework allows the analysis over time of several network characterizing features such as link density, clustering coefficient, degree distribution, as well as entropy-based complexity measures, providing new insight on the evolution of random networks. First, some simple dynamic network models, based only on edge density, are analyzed to serve as a baseline reference for assessing more complex models. Then, a model that depends on network structure with the aim of reflecting some characteristics of real networks is also analyzed. Such model shows a more sophisticated behavior with two different regimes, one of them leading to the generation of high clustering coefficient/link density ratio values when compared with the baseline values, as it happens in many real networks. Simulation examples are discussed to illustrate the behavior of the proposed models.

scholarly journals Network Topology Impact on the Identification of Dynamic Network Models with Application to Autonomous Vehicle Platooning

2020 ◽  
Vol 53 (2) ◽  
pp. 1031-1036
Author(s):  
Guilherme A. Pimentel ◽  
Rafael de Vasconcelos ◽  
Aurélio Salton ◽  
Alexandre Bazanella
Keyword(s):  
Network Topology ◽  
Autonomous Vehicle ◽  
Dynamic Network ◽  
Network Models ◽  
Dynamic Network Models ◽  
Vehicle Platooning

scholarly journals A review of dynamic network models with latent variables

2018 ◽  
Vol 12 (0) ◽  
pp. 105-135 ◽  
Author(s):  
Bomin Kim ◽  
Kevin H. Lee ◽  
Lingzhou Xue ◽  
Xiaoyue Niu
Keyword(s):  
Latent Variables ◽  
Dynamic Network ◽  
Network Models ◽  
Dynamic Network Models

Reconstruction of dynamic network models from metabolite measurements

2007 ◽  
pp. 97-127 ◽  
Author(s):  
Matthias Reuss ◽  
Luciano Aguilera-Vázquez ◽  
Klaus Mauch
Keyword(s):  
Dynamic Network ◽  
Network Models ◽  
Dynamic Network Models

scholarly journals The (T, L)-Path Model and Algorithms for Information Dissemination in Dynamic Networks

Information ◽  
2018 ◽  
Vol 9 (9) ◽  
pp. 212
Author(s):  
Zhiwei Yang ◽  
Weigang Wu
Keyword(s):  
Network Topology ◽  
Information Dissemination ◽  
Dynamic Networks ◽  
Dynamic Network ◽  
Network Models ◽  
Point Of View ◽  
Path Model ◽  
Dynamic Network Models ◽  
Topology Changes ◽  
Practical Design

A dynamic network is the abstraction of distributed systems with frequent network topology changes. With such dynamic network models, fundamental distributed computing problems can be formally studied with rigorous correctness. Although quite a number of models have been proposed and studied for dynamic networks, the existing models are usually defined from the point of view of connectivity properties. In this paper, instead, we examine the dynamicity of network topology according to the procedure of changes, i.e., how the topology or links change. Following such an approach, we propose the notion of the “instant path” and define two dynamic network models based on the instant path. Based on these two models, we design distributed algorithms for the problem of information dissemination respectively, one of the fundamental distributing computing problems. The correctness of our algorithms is formally proved and their performance in time cost and communication cost is analyzed. Compared with existing connectivity based dynamic network models and algorithms, our procedure based ones are definitely easier to be instantiated in the practical design and deployment of dynamic networks.

Dynamic network models and driver information systems

1991 ◽  
Vol 25 (5) ◽  
pp. 251-266 ◽  
Author(s):  
Moshe Ben-Akiva ◽  
Andre De Palma ◽  
Kaysi Isam
Keyword(s):  
Information Systems ◽  
Dynamic Network ◽  
Network Models ◽  
Dynamic Network Models

Epilepsy surgery: Evaluating robustness using dynamic network models

2020 ◽  
Vol 30 (11) ◽  
pp. 113106
Author(s):  
Leandro Junges ◽  
Wessel Woldman ◽  
Oscar J. Benjamin ◽  
John R. Terry
Keyword(s):  
Epilepsy Surgery ◽  
Dynamic Network ◽  
Network Models ◽  
Dynamic Network Models
Sign in / Sign up

Export Citation Format

Share Document