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
What did you think of this review?
Fun to Read
About the reviewer
Charles Ashbacher (CharlesAshbacher)
Charlie Ashbacher is a compulsive reader and writer about many subjects. His prime areas of expertise are in mathematics and computers where he has taught every course in the mathematics and computer … more
Consider the Source
Use Trust Points to see how much you can rely on this review.
"The book is a clear, readable and highly intuitive introduction to the properties and applications of random network models that also provides all the rigorous details or invites the read to fill them in, in the exercises section. ... The balance between intuition and rigor is ideal, in my opinion, and reading the book is an enjoyable and highly rewarding endeavor." - Yannis C. Stamatiou, Mathematical Reviews