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When Big Data and Data Science Prefigured Ambient Intelligence
Published in Kuan-Ching Li, Beniamino DiMartino, Laurence T. Yang, Qingchen Zhang, Smart Data, 2019
Due to the network structure of the Web and the numerous data representations requiring networks and graph structures for modeling and analysis, Network Science, a graph-oriented branch of data science, was defined in 2005 by the National Research Council of the USA [38]. According to the definition, network science is the study of network representations of physical, biological and social phenomena leading to predictive models of these phenomena. Algorithms for transportation in operational research or community discovery in SNAM are parts of network science, with hierarchical graph structures defined for deep learning – e.g., Graph Transformer Network [14].
Graph-Theoretic Algorithms for Energy Saving in IP Networks
Published in F. Richard Yu, Xi Zhang, Victor C. M. Leung, Green Communications and Networking, 2016
Francesca Cuomo, Antonio Cianfrani, Marco Polverini
In network science the graph theory is a key component to represent the network structure and to capture some important characteristics of it. Thanks to this theory we are able to model the topology of a network by a bidirectional graph G = (𝒩, ℰ) where 𝒩 is the set of vertices and ℰ is the set of edges. Let N = |𝒩| and E = |ℰ| be the cardinalities of sets 𝒩 and ℰ, respectively. A vertex models a network node, e.g., a router, and an edge, also named link in the following, models the logical interconnection of two routers.
Network science
Published in Benjamin S. Baumer, Daniel T. Kaplan, Nicholas J. Horton, Modern Data Science with R, 2021
Benjamin S. Baumer, Daniel T. Kaplan, Nicholas J. Horton
Network science is an emerging interdisciplinary field that studies the properties of large and complex networks. Network scientists are interested in both theoretical properties of networks (e.g., mathematical models for degree distribution) and data-based discoveries in real networks (e.g., the distribution of the number of friends on Facebook).
The past, present, and future of network monitoring: A panel discussion
Published in Quality Engineering, 2021
Nathaniel T. Stevens, James D. Wilson
The study of networks, collectively referred to as network science, has made significant contributions to the modeling and understanding of complex systems. A network model contains a collection of vertices and edges, where vertices represent some unit of interest and edges between vertices represent relationships between the units. Simply put, networks are used to model relational, or interconnected data. The mathematical foundations of network analysis is rooted in graph theory, whose origin is widely attributed to Leonhard Euler’s resolution of the Seven Bridges of Königsberg problem in 1735. In his analysis, Euler was the first to represent an observed system as a collection of vertices (land masses) connected by edges (bridges).