Cover image for Big Data over Networks
Title:
Big Data over Networks
Physical Description:
xx, 438 pages : illustrations (black and white) ; 25 cm.
ISBN:
9781107099005
Abstract:
Utilizing 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

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30000010343577 QA76.9.B45 B55 2016 Open Access Book Book
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Summary

Summary

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.


Table of Contents

Part I Mathematical Foundations
1 Tensor models - solution methods and applicationsShiqian Ma and Bo Jiang and Xiuzhen Huang and Shuzhong Zhang
2 Sparsity-aware distributed learningSymeon Chouvardas and Yannis Kopsinis and Sergios Theodoridis
3 Optimization algorithms for big data with application in wireless networksMingyi Hong and Wei-Cheng Liao and Ruoyu Sun and Zhi-Quan Luo
4 A unified distributed algorithm for non-cooperative gamesJong-Shi Pang and Meisam Razaviyayn
Part II Big Data over Cyber Networks
5 Big data analytics systemsGanesh Ananthanarayanan and Ishai Menache
6 Distributed big data storage in optical wireless networksChen Gong and Zhengyuan Xu and Xiaodong Wang
7 Big data aware wireless communication - challenges and opportunitiesSuzhi Bi and Rui Zhang and Zhi Ding and Shuguang Cui
8 Big data processing for smart grid securityLanchao Liu and Zhu Han and H. Vincent Poor and Shuguang Cui
Part III Big Data over Social Networks
9 Big data: a new perspective on citiesRiccardo Gallotti and Thomas Louail and Rémi Louf and Marc Barthelemy
10 High dimensional network analytics: mapping topic networks in Twitter data during the Arab SpringKathleen M. Carley and Wei Wei and Kenneth Joseph
11 Social influence analysis in the big data era - a reviewJianping Cao and Dongliang Duan and Liuqing Yang and Qingpeng Zhang and Senzhang Wang and Feiyue Wang
Part IV Big Data over Biological Networks
12 Inference of gene regulatory networks - validation and uncertaintyXiaoning Qian and Byung-Jun Yoon and Edward R Dougherty
13 Inference of gene networks associated with the host response to infectious diseaseZhe Gan and Xin Yuan and Ricardo Henao and Ephraim L. Tsalik and Lawrence Carin
14 Gene-set-based inference of biological network topologies from big molecular profiling dataLipi Acharya and Dongxiao Zhu
15 Large scale correlation mining for biomolecular network discoveryAlfred Hero and Bala Rajaratnam