Big Data Over Networks

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Big Data and Networks Technologies

Yousef Farhaoui
Big Data and Networks Technologies Book PDF

Author : Yousef Farhaoui
Publisher : Springer
Page : 372 pages
File Size : 41,5 Mb
Release : 2019-07-17
Category : Computers
ISBN : 9783030236724

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Big Data and Networks Technologies by Yousef Farhaoui Pdf

This book reviews the state of the art in big data analysis and networks technologies. It addresses a range of issues that pertain to: signal processing, probability models, machine learning, data mining, databases, data engineering, pattern recognition, visualization, predictive analytics, data warehousing, data compression, computer programming, smart cities, networks technologies, etc. Data is becoming an increasingly decisive resource in modern societies, economies, and governmental organizations. In turn, data science inspires novel techniques and theories drawn from mathematics, statistics, information theory, computer science, and the social sciences. All papers presented here are the product of extensive field research involving applications and techniques related to data analysis in general, and to big data and networks technologies in particular. Given its scope, the book will appeal to advanced undergraduate and graduate students, postdoctoral researchers, lecturers and industrial researchers, as well general readers interested in big data analysis and networks technologies.

Big Data over Networks

Shuguang Cui,Alfred O. Hero, III,Zhi-Quan Luo,José M. F. Moura
Big Data over Networks Book PDF

Author : Shuguang Cui,Alfred O. Hero, III,Zhi-Quan Luo,José M. F. Moura
Publisher : Cambridge University Press
Page : 459 pages
File Size : 45,8 Mb
Release : 2016-01-14
Category : Computers
ISBN : 9781107099005

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Big Data over Networks by Shuguang Cui,Alfred O. Hero, III,Zhi-Quan Luo,José M. F. Moura Pdf

Examines the crucial interaction between big data and communication, social and biological networks using critical mathematical tools and state-of-the-art research.

Big Data in Complex and Social Networks

My T. Thai,Weili Wu,Hui Xiong
Big Data in Complex and Social Networks Book PDF

Author : My T. Thai,Weili Wu,Hui Xiong
Publisher : CRC Press
Page : 253 pages
File Size : 43,6 Mb
Release : 2016-12-01
Category : Business & Economics
ISBN : 9781315396699

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Big Data in Complex and Social Networks by My T. Thai,Weili Wu,Hui Xiong Pdf

This book presents recent developments on the theoretical, algorithmic, and application aspects of Big Data in Complex and Social Networks. The book consists of four parts, covering a wide range of topics. The first part of the book focuses on data storage and data processing. It explores how the efficient storage of data can fundamentally support intensive data access and queries, which enables sophisticated analysis. It also looks at how data processing and visualization help to communicate information clearly and efficiently. The second part of the book is devoted to the extraction of essential information and the prediction of web content. The book shows how Big Data analysis can be used to understand the interests, location, and search history of users and provide more accurate predictions of User Behavior. The latter two parts of the book cover the protection of privacy and security, and emergent applications of big data and social networks. It analyzes how to model rumor diffusion, identify misinformation from massive data, and design intervention strategies. Applications of big data and social networks in multilayer networks and multiparty systems are also covered in-depth.

Big Data Analytics for Sensor-Network Collected Intelligence

Hui-Huang Hsu,Chuan-Yu Chang,Ching-Hsien Hsu
Big Data Analytics for Sensor Network Collected Intelligence Book PDF

Author : Hui-Huang Hsu,Chuan-Yu Chang,Ching-Hsien Hsu
Publisher : Morgan Kaufmann
Page : 326 pages
File Size : 52,7 Mb
Release : 2017-02-02
Category : Computers
ISBN : 9780128096253

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Big Data Analytics for Sensor-Network Collected Intelligence by Hui-Huang Hsu,Chuan-Yu Chang,Ching-Hsien Hsu Pdf

Big Data Analytics for Sensor-Network Collected Intelligence explores state-of-the-art methods for using advanced ICT technologies to perform intelligent analysis on sensor collected data. The book shows how to develop systems that automatically detect natural and human-made events, how to examine people’s behaviors, and how to unobtrusively provide better services. It begins by exploring big data architecture and platforms, covering the cloud computing infrastructure and how data is stored and visualized. The book then explores how big data is processed and managed, the key security and privacy issues involved, and the approaches used to ensure data quality. In addition, readers will find a thorough examination of big data analytics, analyzing statistical methods for data analytics and data mining, along with a detailed look at big data intelligence, ubiquitous and mobile computing, and designing intelligence system based on context and situation. Indexing: The books of this series are submitted to EI-Compendex and SCOPUS Contains contributions from noted scholars in computer science and electrical engineering from around the globe Provides a broad overview of recent developments in sensor collected intelligence Edited by a team comprised of leading thinkers in big data analytics

INTRODUCTION TO BIG DATA: INFRASTRUCTURE AND NETWORKING CONSIDERATIONS

Shoban Babu Sriramoju
INTRODUCTION TO BIG DATA INFRASTRUCTURE AND NETWORKING CONSIDERATIONS Book PDF

Author : Shoban Babu Sriramoju
Publisher : Horizon Books ( A Division of Ignited Minds Edutech P Ltd)
Page : 197 pages
File Size : 41,7 Mb
Release : 2017-12-01
Category : Electronic
ISBN : 9789386369574

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INTRODUCTION TO BIG DATA: INFRASTRUCTURE AND NETWORKING CONSIDERATIONS by Shoban Babu Sriramoju Pdf

Big data is certainly one of the biggest buzz phrases in IT today. Combined with virtualization and cloud computing, big data is a technological capability that will force data centers to significantly transform and evolve within the next five years. Similar to virtualization, big data infrastructure is unique and can create an architectural upheaval in the way systems, storage, and software infrastructure are connected and managed. Unlike previous business analytics solutions, the real-time capability of new big data solutions can provide mission critical business intelligence that can change the shape and speed of enterprise decision making forever. Hence, the way in which IT infrastructure is connected and distributed warrants a fresh and critical analysis.

Cloud Computing Enabled Big-Data Analytics in Wireless Ad-hoc Networks

Sanjoy Das,Ram Shringar Rao,Indrani Das,Vishal Jain,Nanhay Singh
Cloud Computing Enabled Big Data Analytics in Wireless Ad hoc Networks Book PDF

Author : Sanjoy Das,Ram Shringar Rao,Indrani Das,Vishal Jain,Nanhay Singh
Publisher : CRC Press
Page : 300 pages
File Size : 44,6 Mb
Release : 2022-03-21
Category : Technology & Engineering
ISBN : 9781000539493

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Cloud Computing Enabled Big-Data Analytics in Wireless Ad-hoc Networks by Sanjoy Das,Ram Shringar Rao,Indrani Das,Vishal Jain,Nanhay Singh Pdf

This book discusses intelligent computing through the Internet of Things (IoT) and Big-Data in vehicular environments in a single volume. It covers important topics, such as topology-based routing protocols, heterogeneous wireless networks, security risks, software-defined vehicular ad-hoc networks, vehicular delay tolerant networks, and energy harvesting for WSNs using rectenna. FEATURES Covers applications of IoT in Vehicular Ad-hoc Networks (VANETs) Discusses use of machine learning and other computing techniques for enhancing performance of networks Explains game theory-based vertical handoffs in heterogeneous wireless networks Examines monitoring and surveillance of vehicles through the vehicular sensor network Investigates theoretical approaches on software-defined VANET The book is aimed at graduate students and academic researchers in the fields of electrical engineering, electronics and communication engineering, computer science, and engineering.

Deep Learning: Convergence to Big Data Analytics

Murad Khan,Bilal Jan,Haleem Farman
Deep Learning Convergence to Big Data Analytics Book PDF

Author : Murad Khan,Bilal Jan,Haleem Farman
Publisher : Springer
Page : 79 pages
File Size : 48,7 Mb
Release : 2018-12-30
Category : Computers
ISBN : 9789811334597

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Deep Learning: Convergence to Big Data Analytics by Murad Khan,Bilal Jan,Haleem Farman Pdf

This book presents deep learning techniques, concepts, and algorithms to classify and analyze big data. Further, it offers an introductory level understanding of the new programming languages and tools used to analyze big data in real-time, such as Hadoop, SPARK, and GRAPHX. Big data analytics using traditional techniques face various challenges, such as fast, accurate and efficient processing of big data in real-time. In addition, the Internet of Things is progressively increasing in various fields, like smart cities, smart homes, and e-health. As the enormous number of connected devices generate huge amounts of data every day, we need sophisticated algorithms to deal, organize, and classify this data in less processing time and space. Similarly, existing techniques and algorithms for deep learning in big data field have several advantages thanks to the two main branches of the deep learning, i.e. convolution and deep belief networks. This book offers insights into these techniques and applications based on these two types of deep learning. Further, it helps students, researchers, and newcomers understand big data analytics based on deep learning approaches. It also discusses various machine learning techniques in concatenation with the deep learning paradigm to support high-end data processing, data classifications, and real-time data processing issues. The classification and presentation are kept quite simple to help the readers and students grasp the basics concepts of various deep learning paradigms and frameworks. It mainly focuses on theory rather than the mathematical background of the deep learning concepts. The book consists of 5 chapters, beginning with an introductory explanation of big data and deep learning techniques, followed by integration of big data and deep learning techniques and lastly the future directions.

Big Data Analytics

Mrutyunjaya Panda,Ajith Abraham,Aboul Ella Hassanien
Big Data Analytics Book PDF

Author : Mrutyunjaya Panda,Ajith Abraham,Aboul Ella Hassanien
Publisher : CRC Press
Page : 255 pages
File Size : 45,5 Mb
Release : 2018-12-12
Category : Business & Economics
ISBN : 9781351622585

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Big Data Analytics by Mrutyunjaya Panda,Ajith Abraham,Aboul Ella Hassanien Pdf

Social networking has increased drastically in recent years, resulting in an increased amount of data being created daily. Furthermore, diversity of issues and complexity of the social networks pose a challenge in social network mining. Traditional algorithm software cannot deal with such complex and vast amounts of data, necessitating the development of novel analytic approaches and tools. This reference work deals with social network aspects of big data analytics. It covers theory, practices and challenges in social networking. The book spans numerous disciplines like neural networking, deep learning, artificial intelligence, visualization, e-learning in higher education, e-healthcare, security and intrusion detection.

Big Data and Computational Intelligence in Networking

Yulei Wu,Fei Hu,Geyong Min,Albert Y. Zomaya
Big Data and Computational Intelligence in Networking Book PDF

Author : Yulei Wu,Fei Hu,Geyong Min,Albert Y. Zomaya
Publisher : CRC Press
Page : 530 pages
File Size : 49,9 Mb
Release : 2017-12-14
Category : Computers
ISBN : 9781498784870

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Big Data and Computational Intelligence in Networking by Yulei Wu,Fei Hu,Geyong Min,Albert Y. Zomaya Pdf

This book presents state-of-the-art solutions to the theoretical and practical challenges stemming from the leverage of big data and its computational intelligence in supporting smart network operation, management, and optimization. In particular, the technical focus covers the comprehensive understanding of network big data, efficient collection and management of network big data, distributed and scalable online analytics for network big data, and emerging applications of network big data for computational intelligence.

Network Data Analytics

K. G. Srinivasa,Siddesh G. M.,Srinidhi H.
Network Data Analytics Book PDF

Author : K. G. Srinivasa,Siddesh G. M.,Srinidhi H.
Publisher : Springer
Page : 398 pages
File Size : 44,7 Mb
Release : 2018-04-26
Category : Computers
ISBN : 9783319778006

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Network Data Analytics by K. G. Srinivasa,Siddesh G. M.,Srinidhi H. Pdf

In order to carry out data analytics, we need powerful and flexible computing software. However the software available for data analytics is often proprietary and can be expensive. This book reviews Apache tools, which are open source and easy to use. After providing an overview of the background of data analytics, covering the different types of analysis and the basics of using Hadoop as a tool, it focuses on different Hadoop ecosystem tools, like Apache Flume, Apache Spark, Apache Storm, Apache Hive, R, and Python, which can be used for different types of analysis. It then examines the different machine learning techniques that are useful for data analytics, and how to visualize data with different graphs and charts. Presenting data analytics from a practice-oriented viewpoint, the book discusses useful tools and approaches for data analytics, supported by concrete code examples. The book is a valuable reference resource for graduate students and professionals in related fields, and is also of interest to general readers with an understanding of data analytics.

Big Data Analytics in Fog-Enabled IoT Networks

Govind P. Gupta,Rakesh Tripathi,Brij B. Gupta,Kwok Tai Chui
Big Data Analytics in Fog Enabled IoT Networks Book PDF

Author : Govind P. Gupta,Rakesh Tripathi,Brij B. Gupta,Kwok Tai Chui
Publisher : CRC Press
Page : 235 pages
File Size : 46,8 Mb
Release : 2023-04-19
Category : Computers
ISBN : 9781000861860

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Big Data Analytics in Fog-Enabled IoT Networks by Govind P. Gupta,Rakesh Tripathi,Brij B. Gupta,Kwok Tai Chui Pdf

The integration of fog computing with the resource-limited Internet of Things (IoT) network formulates the concept of the fog-enabled IoT system. Due to a large number of IoT devices, the IoT is a main source of Big Data. A large volume of sensing data is generated by IoT systems such as smart cities and smart-grid applications. A fundamental research issue is how to provide a fast and efficient data analytics solution for fog-enabled IoT systems. Big Data Analytics in Fog-Enabled IoT Networks: Towards a Privacy and Security Perspective focuses on Big Data analytics in a fog-enabled-IoT system and provides a comprehensive collection of chapters that touch on different issues related to healthcare systems, cyber-threat detection, malware detection, and the security and privacy of IoT Big Data and IoT networks. This book also emphasizes and facilitates a greater understanding of various security and privacy approaches using advanced artificial intelligence and Big Data technologies such as machine and deep learning, federated learning, blockchain, and edge computing, as well as the countermeasures to overcome the vulnerabilities of the fog-enabled IoT system.

Big Data of Complex Networks

Matthias Dehmer,Frank Emmert-Streib,Stefan Pickl,Andreas Holzinger
Big Data of Complex Networks Book PDF

Author : Matthias Dehmer,Frank Emmert-Streib,Stefan Pickl,Andreas Holzinger
Publisher : CRC Press
Page : 290 pages
File Size : 40,6 Mb
Release : 2016-08-19
Category : Computers
ISBN : 9781315353593

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Big Data of Complex Networks by Matthias Dehmer,Frank Emmert-Streib,Stefan Pickl,Andreas Holzinger Pdf

Big Data of Complex Networks presents and explains the methods from the study of big data that can be used in analysing massive structural data sets, including both very large networks and sets of graphs. As well as applying statistical analysis techniques like sampling and bootstrapping in an interdisciplinary manner to produce novel techniques for analyzing massive amounts of data, this book also explores the possibilities offered by the special aspects such as computer memory in investigating large sets of complex networks. Intended for computer scientists, statisticians and mathematicians interested in the big data and networks, Big Data of Complex Networks is also a valuable tool for researchers in the fields of visualization, data analysis, computer vision and bioinformatics. Key features: Provides a complete discussion of both the hardware and software used to organize big data Describes a wide range of useful applications for managing big data and resultant data sets Maintains a firm focus on massive data and large networks Unveils innovative techniques to help readers handle big data Matthias Dehmer received his PhD in computer science from the Darmstadt University of Technology, Germany. Currently, he is Professor at UMIT – The Health and Life Sciences University, Austria, and the Universität der Bundeswehr München. His research interests are in graph theory, data science, complex networks, complexity, statistics and information theory. Frank Emmert-Streib received his PhD in theoretical physics from the University of Bremen, and is currently Associate professor at Tampere University of Technology, Finland. His research interests are in the field of computational biology, machine learning and network medicine. Stefan Pickl holds a PhD in mathematics from the Darmstadt University of Technology, and is currently a Professor at Bundeswehr Universität München. His research interests are in operations research, systems biology, graph theory and discrete optimization. Andreas Holzinger received his PhD in cognitive science from Graz University and his habilitation (second PhD) in computer science from Graz University of Technology. He is head of the Holzinger Group HCI-KDD at the Medical University Graz and Visiting Professor for Machine Learning in Health Informatics Vienna University of Technology.

Deep Learning Techniques and Optimization Strategies in Big Data Analytics

Thomas, J. Joshua,Karagoz, Pinar,Ahamed, B. Bazeer,Vasant, Pandian
Deep Learning Techniques and Optimization Strategies in Big Data Analytics Book PDF

Author : Thomas, J. Joshua,Karagoz, Pinar,Ahamed, B. Bazeer,Vasant, Pandian
Publisher : IGI Global
Page : 355 pages
File Size : 51,9 Mb
Release : 2019-11-29
Category : Computers
ISBN : 9781799811947

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Deep Learning Techniques and Optimization Strategies in Big Data Analytics by Thomas, J. Joshua,Karagoz, Pinar,Ahamed, B. Bazeer,Vasant, Pandian Pdf

Many approaches have sprouted from artificial intelligence (AI) and produced major breakthroughs in the computer science and engineering industries. Deep learning is a method that is transforming the world of data and analytics. Optimization of this new approach is still unclear, however, and there’s a need for research on the various applications and techniques of deep learning in the field of computing. Deep Learning Techniques and Optimization Strategies in Big Data Analytics is a collection of innovative research on the methods and applications of deep learning strategies in the fields of computer science and information systems. While highlighting topics including data integration, computational modeling, and scheduling systems, this book is ideally designed for engineers, IT specialists, data analysts, data scientists, engineers, researchers, academicians, and students seeking current research on deep learning methods and its application in the digital industry.

Integration of Cloud Computing with Internet of Things

Monika Mangla,Suneeta Satpathy,Bhagirathi Nayak,Sachi Nandan Mohanty
Integration of Cloud Computing with Internet of Things Book PDF

Author : Monika Mangla,Suneeta Satpathy,Bhagirathi Nayak,Sachi Nandan Mohanty
Publisher : John Wiley & Sons
Page : 384 pages
File Size : 51,8 Mb
Release : 2021-03-08
Category : Computers
ISBN : 9781119769309

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Integration of Cloud Computing with Internet of Things by Monika Mangla,Suneeta Satpathy,Bhagirathi Nayak,Sachi Nandan Mohanty Pdf

The book aims to integrate the aspects of IoT, Cloud computing and data analytics from diversified perspectives. The book also plans to discuss the recent research trends and advanced topics in the field which will be of interest to academicians and researchers working in this area. Thus, the book intends to help its readers to understand and explore the spectrum of applications of IoT, cloud computing and data analytics. Here, it is also worth mentioning that the book is believed to draw attention on the applications of said technology in various disciplines in order to obtain enhanced understanding of the readers. Also, this book focuses on the researches and challenges in the domain of IoT, Cloud computing and Data analytics from perspectives of various stakeholders.

Big Data Analytics in Cybersecurity

Onur Savas,Julia Deng
Big Data Analytics in Cybersecurity Book PDF

Author : Onur Savas,Julia Deng
Publisher : CRC Press
Page : 452 pages
File Size : 48,6 Mb
Release : 2017-09-18
Category : Business & Economics
ISBN : 9781351650410

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Big Data Analytics in Cybersecurity by Onur Savas,Julia Deng Pdf

Big data is presenting challenges to cybersecurity. For an example, the Internet of Things (IoT) will reportedly soon generate a staggering 400 zettabytes (ZB) of data a year. Self-driving cars are predicted to churn out 4000 GB of data per hour of driving. Big data analytics, as an emerging analytical technology, offers the capability to collect, store, process, and visualize these vast amounts of data. Big Data Analytics in Cybersecurity examines security challenges surrounding big data and provides actionable insights that can be used to improve the current practices of network operators and administrators. Applying big data analytics in cybersecurity is critical. By exploiting data from the networks and computers, analysts can discover useful network information from data. Decision makers can make more informative decisions by using this analysis, including what actions need to be performed, and improvement recommendations to policies, guidelines, procedures, tools, and other aspects of the network processes. Bringing together experts from academia, government laboratories, and industry, the book provides insight to both new and more experienced security professionals, as well as data analytics professionals who have varying levels of cybersecurity expertise. It covers a wide range of topics in cybersecurity, which include: Network forensics Threat analysis Vulnerability assessment Visualization Cyber training. In addition, emerging security domains such as the IoT, cloud computing, fog computing, mobile computing, and cyber-social networks are examined. The book first focuses on how big data analytics can be used in different aspects of cybersecurity including network forensics, root-cause analysis, and security training. Next it discusses big data challenges and solutions in such emerging cybersecurity domains as fog computing, IoT, and mobile app security. The book concludes by presenting the tools and datasets for future cybersecurity research.