Big Data over Networks

Description

Utilising both key mathematical tools and state-of-the-art research results, this text explores the principles underpinning large-scale information processing over networks and examines the crucial interaction between big data and its associated communication, social and biological networks. Written by experts in the diverse fields of machine learning, optimisation, statistics, signal processing, networking, communications, sociology and biology, this book employs two complementary approaches: first analysing how the underlying network constrains the upper-layer of collaborative big data processing, and second, examining how big data processing may boost performance in various networks. Unifying the broad scope of the book is the rigorous mathematical treatment of the subjects, which is enriched by in-depth discussion of future directions and numerous open-ended problems that conclude each chapter. Readers will be able to master the fundamental principles for dealing with big data over large systems, making it essential reading for graduate students, scientific researchers and industry practitioners alike.

Shuguang (Robert) Cui is an Associate Professor at Texas A&M University. His is a Fellow of IEEE and was selected as a Highly Cited Researcher by Thomson Reuters in 2014. Alfred O. Hero, III is R. Jamison and Betty Williams Professor of Engineering at the University of Michigan, Ann Arbor, with appointments in the Departments of Electrical Engineering and Computer Science, Biomedical Engineering and Statistics. He is a Fellow of the IEEE. Zhi-Quan (Tom) Luo is a Professor at the University of Minnesota. He has served as the Editor-in-Chief of IEEE Transactions on Signal Processing and is a Fellow of the IEEE, SIAM, and the Royal Society of Canada. Jose M. F. Moura is Philip L. and Marsha Dowd University Professor at Carnegie Mellon University, with appointments in the Departments of Electrical and Computer Engineering and, by courtesy, of Biomedical Engineering. He is a Fellow of IEEE and AAAS, a corresponding member of the Academy of Sciences of Portugal, and a member of the US NAE.