front cover of AIoT Technologies and Applications for Smart Environments
AIoT Technologies and Applications for Smart Environments
Mamoun Alazab
The Institution of Engineering and Technology, 2022
Although some IoT systems are built for simple event control where a sensor signal triggers a corresponding reaction, many events are far more complex, requiring applications to interpret the event using analytical techniques to initiate proper actions. Artificial intelligence of things (AIoT) applies intelligence to the edge and gives devices the ability to understand the data, observe the environment around them, and decide what to do best with minimum human intervention. With the power of AI, AIoT devices are not just messengers feeding information to control centers. They have evolved into intelligent machines capable of performing self-driven analytics and acting independently. A smart environment uses technologies such as wearable devices, IoT, and mobile internet to dynamically access information, connect people, materials and institutions, and then actively manages and responds to the ecosystem's needs in an intelligent manner.
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Big Data and Software Defined Networks
Javid Taheri
The Institution of Engineering and Technology, 2018
Big Data Analytics and Software Defined Networking (SDN) are helping to drive the management of data and usage of the extraordinary increase of computer processing power provided by Cloud Data Centres (CDCs). SDN helps CDCs run their services more efficiently by enabling managers to configure, manage, secure, and optimize the network resources very quickly. Big-Data Analytics in turn has entered CDCs to harvest the massive computing powers and deduct information that was never reachable by conventional methods.
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Big Data Recommender Systems
Algorithms, Architectures, Big Data, Security and Trust, Volume 1
Osman Khalid
The Institution of Engineering and Technology, 2019
First designed to generate personalized recommendations to users in the 90s, recommender systems apply knowledge discovery techniques to users’ data to suggest information, products, and services that best match their preferences. In recent decades, we have seen an exponential increase in the volumes of data, which has introduced many new challenges.
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Big Data Recommender Systems
Application Paradigms, Volume 2
Osman Khalid
The Institution of Engineering and Technology, 2019
First designed to generate personalized recommendations to users in the 90s, recommender systems apply knowledge discovery techniques to users’ data to suggest information, products, and services that best match their preferences. In recent decades, we have seen an exponential increase in the volumes of data, which has introduced many new challenges.
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Big Data Recommender Systems
Recent trends and advances
Osman Khalid
The Institution of Engineering and Technology, 2019
This timely volume combines experimental and theoretical research on big data recommender systems to help computer scientists develop new concepts and methodologies for complex applications. It includes original scientific contributions in the form of theoretical foundations, comparative analysis, surveys, case studies, techniques and tools. The authors give special attention to key topics such as data filtering and cleaning techniques for recommendations, novelty and diversity, privacy issues, security threats and their mitigation, trust, cold start, sparsity, scalability, application domains, and recommender system evaluations.
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Big Data-Enabled Internet of Things
Muhammad Usman Shahid Khan
The Institution of Engineering and Technology, 2020
The fields of Big Data and the Internet of Things (IoT) have seen tremendous advances, developments, and growth in recent years. The IoT is the inter-networking of connected smart devices, buildings, vehicles and other items which are embedded with electronics, software, sensors and actuators, and network connectivity that enable these objects to collect and exchange data. The IoT produces a lot of data. Big data describes very large and complex data sets that traditional data processing application software is inadequate to deal with, and the use of analytical methods to extract value from data. This edited book covers analytical techniques for handling the huge amount of data generated by the Internet of Things, from architectures and platforms to security and privacy issues, applications, and challenges as well as future directions.
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Blockchain and the Law
The Rule of Code
Primavera De Filippi and Aaron Wright
Harvard University Press, 2018

“Blockchains will matter crucially; this book, beautifully and clearly written for a wide audience, powerfully demonstrates how.”
—Lawrence Lessig


“Attempts to do for blockchain what the likes of Lawrence Lessig and Tim Wu did for the Internet and cyberspace—explain how a new technology will upend the current legal and social order… Blockchain and the Law is not just a theoretical guide. It’s also a moral one.”
Fortune


Bitcoin has been hailed as an Internet marvel and decried as the preferred transaction vehicle for criminals. It has left nearly everyone without a computer science degree confused: how do you “mine” money from ones and zeros?

The answer lies in a technology called blockchain. A general-purpose tool for creating secure, decentralized, peer-to-peer applications, blockchain technology has been compared to the Internet in both form and impact. Blockchains are being used to create “smart contracts,” to expedite payments, to make financial instruments, to organize the exchange of data and information, and to facilitate interactions between humans and machines. But by cutting out the middlemen, they run the risk of undermining governmental authorities’ ability to supervise activities in banking, commerce, and the law. As this essential book makes clear, the technology cannot be harnessed productively without new rules and new approaches to legal thinking.

“If you…don’t ‘get’ crypto, this is the book-length treatment for you.”
—Tyler Cowen, Marginal Revolution

“De Filippi and Wright stress that because blockchain is essentially autonomous, it is inflexible, which leaves it vulnerable, once it has been set in motion, to the sort of unforeseen consequences that laws and regulations are best able to address.”
—James Ryerson, New York Times Book Review

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Demystifying Graph Data Science
Graph algorithms, analytics methods, platforms, databases, and use cases
Pethuru Raj
The Institution of Engineering and Technology, 2022
With the growing maturity and stability of digitization and edge technologies, vast numbers of digital entities, connected devices, and microservices interact purposefully to create huge sets of poly-structured digital data. Corporations are continuously seeking fresh ways to use their data to drive business innovations and disruptions to bring in real digital transformation. Data science (DS) is proving to be the one-stop solution for simplifying the process of knowledge discovery and dissemination out of massive amounts of multi-structured data.
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Dynamic Ad Hoc Networks
Habib F. Rashvand
The Institution of Engineering and Technology, 2013
Motivated by the exciting new application paradigm of using amalgamated technologies of the Internet and wireless, the next generation communication networks (also called 'ubiquitous', 'complex' and 'unstructured' networking) are changing the way we develop and apply our future systems and services at home and on local, national and global scales. Whatever the interconnection - a WiMAX enabled networked mobile vehicle, MEMS or nanotechnology enabled distributed sensor systems, Vehicular Ad hoc Networking (VANET) or Mobile Ad hoc Networking (MANET) - all can be classified under new networking structures which can be given the generic title of 'ad hoc' communication networking.
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front cover of Enabling Technologies for Smart Fog Computing
Enabling Technologies for Smart Fog Computing
Kuldeep Singh Kaswan
The Institution of Engineering and Technology, 2024
Fog computing is a decentralized computing infrastructure in which computing resources are located between the data source and the cloud or any other data centers. The word "fog" refers to its cloud-like properties, which are closer to the "ground", using edge devices that carry out locally computation, storage and communication tasks. An additional benefit is that the processed data is likely to be needed by the same devices that generated the data. By processing locally rather than remotely, the latency between input and response are minimized. This technology has countless application domains such as industrial process control, smart cities, transportation, healthcare and agriculture.
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Handbook of Big Data Analytics
Applications in ICT, security and business analytics, Volume 2
Vadlamani Ravi
The Institution of Engineering and Technology, 2021
Big Data analytics is the complex process of examining big data to uncover information such as correlations, hidden patterns, trends and user and customer preferences, to allow organizations and businesses to make more informed decisions. These methods and technologies have become ubiquitous in all fields of science, engineering, business and management due to the rise of data-driven models as well as data engineering developments using parallel and distributed computational analytics frameworks, data and algorithm parallelization, and GPGPU programming. However, there remain potential issues that need to be addressed to enable big data processing and analytics in real time.
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Handbook of Big Data Analytics
Methodologies, Volume 1
Vadlamani Ravi
The Institution of Engineering and Technology, 2021
Big Data analytics is the complex process of examining big data to uncover information such as correlations, hidden patterns, trends and user and customer preferences, to allow organizations and businesses to make more informed decisions. These methods and technologies have become ubiquitous in all fields of science, engineering, business and management due to the rise of data-driven models as well as data engineering developments using parallel and distributed computational analytics frameworks, data and algorithm parallelization, and GPGPU programming. However, there remain potential issues that need to be addressed to enable big data processing and analytics in real time.
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front cover of Intelligent Network Design Driven by Big Data Analytics, IoT, AI and Cloud Computing
Intelligent Network Design Driven by Big Data Analytics, IoT, AI and Cloud Computing
Sunil Kumar
The Institution of Engineering and Technology, 2022
As enterprise access networks evolve with a larger number of mobile users, a wide range of devices and new cloud-based applications, managing user performance on an end-to-end basis has become rather challenging. Recent advances in big data network analytics combined with AI and cloud computing are being leveraged to tackle this growing problem. AI is becoming further integrated with software that manage networks, storage, and can compute.
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Internet Daemons
Digital Communications Possessed
Fenwick McKelvey
University of Minnesota Press, 2018

A complete history and theory of internet daemons brings these little-known—but very consequential—programs into the spotlight


We’re used to talking about how tech giants like Google, Facebook, and Amazon rule the internet, but what about daemons? Ubiquitous programs that have colonized the Net’s infrastructure—as well as the devices we use to access it—daemons are little known. Fenwick McKelvey weaves together history, theory, and policy to give a full account of where daemons come from and how they influence our lives—including their role in hot-button issues like network neutrality.

Going back to Victorian times and the popular thought experiment Maxwell’s Demon, McKelvey charts how daemons evolved from concept to reality, eventually blossoming into the pandaemonium of code-based creatures that today orchestrates our internet. Digging into real-life examples like sluggish connection speeds, Comcast’s efforts to control peer-to-peer networking, and Pirate Bay’s attempts to elude daemonic control (and skirt copyright), McKelvey shows how daemons have been central to the internet, greatly influencing everyday users.

Internet Daemons asks important questions about how much control is being handed over to these automated, autonomous programs, and the consequences for transparency and oversight.

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front cover of Machine Learning, Blockchain Technologies and Big Data Analytics for IoTs
Machine Learning, Blockchain Technologies and Big Data Analytics for IoTs
Methods, technologies and applications
Amit Kumar Tyagi
The Institution of Engineering and Technology, 2022
Internet of Things (IoTs) are now being integrated at a large scale in fast-developing applications such as healthcare, transportation, education, finance, insurance and retail. The next generation of automated applications will command machines to do tasks better and more efficiently. Both industry and academic researchers are looking at transforming applications using machine learning and deep learning to build better models and by taking advantage of the decentralized nature of Blockchain. But the advent of these new technologies also brings very high expectations to industries, organisations and users. The decrease of computing costs, the improvement of data integrity in Blockchain, and the verification of transactions using Machine Learning are becoming essential goals.
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Managing Internet of Things Applications across Edge and Cloud Data Centres
Rajiv Ranjan
The Institution of Engineering and Technology, 2024
Cloud computing has been a game changer for internet-based applications such as content delivery networks, social networking and multi-tier enterprise applications. However, the requirements for low-latency data access, security, bandwidth, mobility, and cost have challenged centralized data center-based cloud computing models, which is driving the need for the novel computing paradigms of edge and fog computing. The internet of things (IoT) focuses on discovery, aggregation, management, and acting on data originating from internet-connected devices via programmable sensors, actuators, mobile phones, surveillance cameras, routers, gateways and switches. But the aggregation of this data is expensive and can be time consuming.
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front cover of Modeling and Simulation of Complex Communication Networks
Modeling and Simulation of Complex Communication Networks
Muaz A. Niazi
The Institution of Engineering and Technology, 2019
Modern network systems such as Internet of Things, Smart Grid, VoIP traffic, Peer-to-Peer protocol, and social networks, are inherently complex. They require powerful and realistic models and tools not only for analysis and simulation but also for prediction.
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front cover of Network Classification for Traffic Management
Network Classification for Traffic Management
Anomaly detection, feature selection, clustering and classification
Zahir Tari
The Institution of Engineering and Technology, 2020
With the massive increase of data and traffic on the Internet within the 5G, IoT and smart cities frameworks, current network classification and analysis techniques are falling short. Novel approaches using machine learning algorithms are needed to cope with and manage real-world network traffic, including supervised, semi-supervised, and unsupervised classification techniques. Accurate and effective classification of network traffic will lead to better quality of service and more secure and manageable networks.
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Networking
Communicating with Bodies and Machines in the Nineteenth Century
Laura Otis
University of Michigan Press, 2011
This compelling new interdisciplinary study investigates the scientific and cultural roots of contemporary conceptions of the network, including computer information systems, the human nervous system, and communications technology. Laura Otis, neuroscientist, literary scholar, and recent recipient of a MacArthur Fellowship, demonstrates that the image of the network is centuries old; it is by no means a modern notion. Placing current comparisons of nerve and computer networks in perspective, Otis explores early analogies linking nerves and telegraphs and demonstrates the influence that nineteenth-century neurobiologists, engineers, and fiction writers influenced each other's ideas about communication.
The interdisciplinary sweep of this book is impressive. Otis focuses simultaneously on literary works by such authors as George Eliot, Bram Stoker, Henry James, and Mark Twain and on the scientific and technological achievements of such pioneers as Luigi Galvani, Hermann von Helmholtz, Charles Babbage, Samuel Morse, and Werner von Siemens.
This unique juxtaposition of physiology, engineering, and literature reveals the common thoughts shared by writers in widely diverse fields and suggests that our current comparisons of nerve and computer networks may not only enhance but shape our understanding of both neurobiology and technology.
Highly accessible and jargon-free, Networking will appeal to general readers as well as to scholars in the fields of interdisciplinary studies, nineteenth-century literature, and the history of science and technology.
Laura Otis is Associate Professor of English, Hofstra University. In 2000, she was awarded a MacArthur Foundation Fellowship for her interdisciplinary studies of literature and science. Her previous books include Membranes: Metaphors of Invasion in Nineteenth-Century Literature, Science, and Politics and Organic Memory: History and the Body in the Late Nineteenth and Early Twentieth Centuries.
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front cover of Networking the World, 1794-2000
Networking the World, 1794-2000
Armand Mattelart
University of Minnesota Press, 2000

front cover of Prometheus Wired
Prometheus Wired
The Hope for Democracy in the Age of Network Technology
Darin Barney
University of Chicago Press, 2000
From all sides, we hear that computer technology, with its undeniable power to disseminate information and connect individuals, holds enormous potential for a reinvigoration of political life. But will the Internet really spark a democratic revolution? And will the changes it brings be so profound that past political thought will be of little use in helping us to understand them?

In Prometheus Wired, Darin Barney debunks claims that a networked society will provide the infrastructure for a political revolution and shows that the resources we need for understanding and making sound judgments about this new technology are surprisingly close at hand. By looking to thinkers who grappled with the relationship of society and technology, such as Plato, Aristotle, Marx, and Heidegger, Barney critically examines such assertions about the character of digital networks.

Along the way, Barney offers an eye-opening history of digital networks and then explores a wide range of contemporary issues, such as electronic commerce, telecommuting, privacy, virtual community, digital surveillance, and the possibility of sovereign governance in an age of global networks. Ultimately, Barney argues that instead of placing power back in the hands of the public, a networked economy seems to exacerbate the worst features of industrial capitalism, and, in terms of the surveillance and control it exerts, reduces our political freedom.

Of vital interest to politicians, communicators, and anyone concerned about the future of democracy in the digital age, Prometheus Wired adds a provocative new voice to the debate swirling around "the Net" and the ways in which it will, or will not, change our political lives.
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front cover of Pull
Pull
Networking and Success since Benjamin Franklin
Pamela Walker Laird
Harvard University Press, 2006

Redefining the way we view business success, Pamela Laird demolishes the popular American self-made story as she exposes the social dynamics that navigate some people toward opportunity and steer others away. Who gets invited into the networks of business opportunity? What does an unacceptable candidate lack? The answer is social capital—all those social assets that attract respect, generate confidence, evoke affection, and invite loyalty.

In retelling success stories from Benjamin Franklin to Andrew Carnegie to Bill Gates, Laird goes beyond personality, upbringing, and social skills to reveal the critical common key—access to circles that control and distribute opportunity and information. She explains how civil rights activism and feminism in the 1960s and 1970s helped demonstrate that personnel practices violated principles of equal opportunity. She evaluates what social privilege actually contributes to business success, and analyzes the balance between individual characteristics—effort, innovation, talent—and social factors such as race, gender, class, and connections.

In contrasting how Americans have prospered—or not—with how we have talked about prospering, Laird offers rich insights into how business really operates and where its workings fit within American culture. From new perspectives on entrepreneurial achievement to the role of affirmative action and the operation of modern corporate personnel systems, Pull shows that business is a profoundly social process, and that no one can succeed alone.

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front cover of Streaming Analytics
Streaming Analytics
Concepts, architectures, platforms, use cases and applications
Pethuru Raj
The Institution of Engineering and Technology, 2022
When digitized entities, connected devices and microservices interact purposefully, we end up with a massive amount of multi-structured streaming (real-time) data that is continuously generated by different sources at high speed. Streaming analytics allows the management, monitoring, and real-time analytics of live streaming data. The topic has grown in importance due to the emergence of online analytics and edge and IoT platforms. A real digital transformation is being achieved across industry verticals through meticulous data collection, cleansing and crunching in real time. Capturing and subjecting those value-adding events is considered to be the prime task for achieving trustworthy and timely insights.
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Studying Social Networks
A Guide to Empirical Research
Marina Hennig, Ulrik Brandes, Jürgen Pfeffer, and Ines Mergel
Campus Verlag, 2012
Studying Social Networks provides a concise, comprehensive introduction to the process of empirical network research. Students and practitioners new to social research will find easily understandable learning goals, numerous examples, and helpful exercises all in one compact volume. The authors have integrated  different disciplinary perspectives, while stressing the importance of substance-specific orientation while studying networks. Scholars will find Studying Social Networks a helpful tool not only for teaching, but also as a guide for their own empirical research.

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front cover of Trustworthy Autonomic Computing
Trustworthy Autonomic Computing
Thaddeus Eze
The Institution of Engineering and Technology, 2022
The concept of autonomic computing seeks to reduce the complexity of pervasively ubiquitous system management and maintenance by shifting the responsibility for low-level tasks from humans to the system while allowing humans to concentrate on high-level tasks. This is achieved by building self-managing systems that are generally capable of self-configuring, self-healing, self-optimising, and self-protecting.
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