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Epidemics and Rumours in Complex Networks / Moez Draief, Laurent Massoulié.

By: Contributor(s): Material type: TextTextSeries: London Mathematical Society Lecture Note Series ; no. 369 | London Mathematical Society Lecture Note Series ; no. 369.Publisher: Cambridge : Cambridge University Press, 2009Description: 1 online resource (130 pages) : digital, PDF file(s)Content type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9780511806018 (ebook)
Other title:
  • Epidemics & Rumours in Complex Networks
Additional physical formats: Print version: : No titleDDC classification:
  • 614.4011 22
Online resources: Summary: Information propagation through peer-to-peer systems, online social systems, wireless mobile ad hoc networks and other modern structures can be modelled as an epidemic on a network of contacts. Understanding how epidemic processes interact with network topology allows us to predict ultimate course, understand phase transitions and develop strategies to control and optimise dissemination. This book is a concise introduction for applied mathematicians and computer scientists to basic models, analytical tools and mathematical and algorithmic results. Mathematical tools introduced include coupling methods, Poisson approximation (the Stein–Chen method), concentration inequalities (Chernoff bounds and Azuma–Hoeffding inequality) and branching processes. The authors examine the small-world phenomenon, preferential attachment, as well as classical epidemics. Each chapter ends with pointers to the wider literature. An ideal accompaniment for graduate courses, this book is also for researchers (statistical physicists, biologists, social scientists) who need an efficient guide to modern approaches to epidemic modelling on networks.
Item type: E-BOOKS
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Title from publisher's bibliographic system (viewed on 16 Oct 2015).

Information propagation through peer-to-peer systems, online social systems, wireless mobile ad hoc networks and other modern structures can be modelled as an epidemic on a network of contacts. Understanding how epidemic processes interact with network topology allows us to predict ultimate course, understand phase transitions and develop strategies to control and optimise dissemination. This book is a concise introduction for applied mathematicians and computer scientists to basic models, analytical tools and mathematical and algorithmic results. Mathematical tools introduced include coupling methods, Poisson approximation (the Stein–Chen method), concentration inequalities (Chernoff bounds and Azuma–Hoeffding inequality) and branching processes. The authors examine the small-world phenomenon, preferential attachment, as well as classical epidemics. Each chapter ends with pointers to the wider literature. An ideal accompaniment for graduate courses, this book is also for researchers (statistical physicists, biologists, social scientists) who need an efficient guide to modern approaches to epidemic modelling on networks.

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The Institute of Mathematical Sciences, Chennai, India