Network Science
Theory and Applications
Ted G. Lewis
- English
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Network Science
Theory and Applications
Ted G. Lewis
Informazioni sul libro
A comprehensive look at the emerging science of networks
Network science helps you design faster, more resilient communication networks; revise infrastructure systems such as electrical power grids, telecommunications networks, and airline routes; model market dynamics; understand synchronization in biological systems; and analyze social interactions among people.
This is the first book to take a comprehensive look at this emerging science. It examines the various kinds of networks (regular, random, small-world, influence, scale-free, and social) and applies network processes and behaviors to emergence, epidemics, synchrony, and risk. The book's uniqueness lies in its integration of concepts across computer science, biology, physics, social network analysis, economics, and marketing.
The book is divided into easy-to-understand topical chapters and the presentation is augmented with clear illustrations, problems and answers, examples, applications, tutorials, and a discussion of related Java software. Chapters cover:
- Origins
- Graphs
- Regular Networks
- Random Networks
- Small-World Networks
- Scale-Free Networks
- Emergence
- Epidemics
- Synchrony
- Influence Networks
- Vulnerability
- Net Gain
- Biology
This book offers a new understanding and interpretation of the field of network science. It is an indispensable resource for researchers, professionals, and technicians in engineering, computing, and biology. It also serves as a valuable textbook for advanced undergraduate and graduate courses in related fields of study.
Domande frequenti
Informazioni
Date | Who | Contribution |
1736 | Euler | Bridges of Königsberg |
1925 | G. Yule | Preferential attachment, Yule–Simon distribution |
1927 | Kermack, McKendrick | First epidemic model |
1951 | Solomonoff, Rappaport | Spread of infection in random networks |
1955 | Simon | Power law observed in word analysis |
1959 | Gilbert | First generative procedure for random graph |
1960 | Erdos, Renyi | Random graphs |
1967 | Milgram | Small-world experiment |
1969 | Bass | Diffusion of innovation in populations—nonnetwork model |
1971 | Fisher, Pry | Diffusion by product substitution—nonnetwork model |
1972 | Bollobas | Complex graphs |
1972 | Bonacich | Idea of influence in social networks leading to influence diagrams |
1973 | Granovetter | Job-seeking networks formed clusters with “weak links” between them |
1978 | Pool, Kochen | First theoretical examination of small worlds |
1984 | Kuramoto | Synchronization of linear systems |
1985 | Bollobas | Publishes book on “random graphs” |
1988 | Waxman | First graph model of the Internet |
1989 | Bristor, Ryan | “Buying networks” = application of network science to model economic system |
1990 | Guare | Coined phrase, “six degrees of separation” = name of his Broadway play |
1995 | Molloy, Reed | Generation of networks with arbitrary degree sequence distribution |
1996 | Kretschmar, Morris | Early application of network science to spread of infectious disease = contagion driven by largest connected component |
1998 | Holland | Introduction of emergence in complex adaptive systems |
1998 | Watts, Strogatz, Faloutsos, Faloutsos | Renewed interest in Milgram’s original work on small worlds, examples of clustering; first generative procedure for small world |
1999 | Faloutsos | Power law observed in Internet |
1999 | Albert, Jeong, Barabasi | Power law observed in WWW |
1999 | Dorogovtsev, Mendes | Small-world properties |
1999 | Barabasi, Albert, | Scale-free network model |
1999 | Dorogovtsev, Mendes, Samukhim, Krapivsky Redner | Exact solution to scale-free network degree sequence |
1999 | Watts | Explanation of “small-world dilemma”: high clustering, low path length |
1999 | Adamic | Distance between .edu sites shown to be small-world |
1999 | Kleinberg, Kumar, Raghavan, Rajagopalan Tomkins | Formalized model of WWW as “Webgraph” |
1999 | Walsh | Difficulty of search in small worlds using local properties |
2000 | Marchiori, Latora, | Harmonic distance replaces path length: works for disconnected networks |
2000 | Broder, Kumar, Maghoul, Raghavan, Rajagopalan Stata, Tomkins, Wiener | Full Webgraph map of the WWW |
2000 | Kleinberg | Shows O(n) search in small world using “Manhattan distance” |
2000 | Albert, Jeong, Barabasi | Scale-free networks are resilient if hubs are protected (Internet’s “Achilles heel”) |
2001 | Yung | Taxonomy of applications of small-world theory to: SNA, collaboration, Internet, business, life sciences |
2001 | Pastor-Satorras, Vespignani | Claim no epidemic threshold in scale-free networks; Internet susceptible to SIS viruses |
2001 | Tadic, Adamic | Use of local information can speed search on scale- free networks |
2002 | Levene, Fenner, Loizou, Wheeldon | Enhanced Webgraph model concluded structure of the WWW couldn’t be explained by preferential attachment alone |
2002 | Kleinfeld, | Claims Milgram experiments not well founded: small- world social network is an “urban myth” |
2002 | Wang, Chen, Barahona, Pecora, Liu, Hong, Choi Kim, Jost, Joy | Sync in small worlds equivalent to stability in coupled system |
2003 | Wang, Chakrabarti, Wang, Faloutsos | Showed spread of epidemics determined by network’s spectral radius, largest eigenvalue of connection matrix |
2003 | Virtanen | Complete survey of network science results up to 2003 |
2003 | Strogatz | Synchronization of crickets, heartbeats |
2005 | NRC | Definition of network science |
2006 | Atay | Synchronization in networks with degree sequence distribution—application to networks |
2007 | Gabbay | Consensus in influence networks—linear and nonlinear models |
Indice dei contenuti
- Cover
- Title page
- Copyright page
- Preface/Foreword
- 1 Origins
- 2 Graphs
- 3 Regular Networks
- 4 Random Networks
- 5 Small-World Networks
- 6 Scale-Free Networks
- 7 Emergence
- 8 Epidemics
- 9 Synchrony
- 10 Influence Networks
- 11 Vulnerability
- 12 NetGain
- 13 Biology
- Bibliography
- About the Author
- Index