Epidemics and Rumours in Complex Networks
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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Epidemics and Rumours in Complex Networks
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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Epidemics and Rumours in Complex Networks

Epidemics and Rumours in Complex Networks

Epidemics and Rumours in Complex Networks

Epidemics and Rumours in Complex Networks

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Overview

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.

Product Details

ISBN-13: 9780521734431
Publisher: Cambridge University Press
Publication date: 12/03/2009
Series: London Mathematical Society Lecture Note Series , #369
Pages: 130
Product dimensions: 5.91(w) x 8.70(h) x 0.39(d)

About the Author

Moez Draief is Assistant Professor in the Department of Electrical and Electronic Engineering at Imperial College, London.

Laurent Massoulié is Senior Researcher at Thomson Corporate Research in Paris. He has been the recipient of several best paper awards including ACM CoNEXT 2007.

Table of Contents

Introduction; Part I. Shapeless Networks: 1. Galton-Watson branching processes; 2. Reed-Frost epidemics and Erdős-Rényi random graphs; 3. Connectivity and Poisson approximation; 4. Diameter of Erdős-Rényi graphs; 5. From microscopic to macroscopic dynamics; Part II. Structured Networks: 6. The small-world phenomenon; 7. Power laws via preferential attachment; 8. Epidemics on general graphs; 9. Viral marketing and optimised epidemics; References; Index.
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