Random Networks for Communication: From Statistical Physics to Information Systems (Cambridge Series in Statistical and Probabilistic Mathematics)


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When is a random network (almost) connected? How much information can it carry? How can you find a particular destination within the network? And how do you approach these questions - and others - when the network is random? The analysis of communication networks requires a fascinating synthesis of random graph theory, stochastic geometry and percolation theory to provide models for both structure and information flow. This book is the first comprehensive introduction for graduate students and scientists to techniques and problems in the field of spatial random networks. The selection of material is driven by applications arising in engineering, and the treatment is both readable and mathematically rigorous. Though mainly concerned with information-flow-related questions motivated by wireless data networks, the models developed are also of interest in a broader context, ranging from engineering to social networks, biology, and physics.Random Networks for Communication: From Statistical Physics to Information Systems (Cambridge Series in Statistical and Probabilistic Mathematics) Review
It is more realistic to consider the graphs describing computer networks to be pseudorandom rather than random. In other words, they have an underlying deterministic structure but the outward appearance is one of randomness. Computers on a network will wink on and off depending on power outages, scheduled maintenance and their current load. As information passes from node to node in a network, the movement of the data can be modeled using percolation theory, which is an area of random graphs. Therefore, the modern creator or manager of a large network must possess some knowledge of random graphs. This book provides that essential knowledge.The reader must have prior knowledge of calculus, probability and Poisson distributions in order to understand the demonstrations and theorems and the material is presented in a very clear and understandable manner. A small set of exercises appears at the end of each chapter but solutions are not included.
The chapter headings are:
*) Phase transitions in finite networks
*) Connectivity of finite networks
*) More on phase transitions
*) Information flow in random networks
*) Navigation in random networks
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