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This book pioneers the synergy between state-of-the-art edge computing technologies and the power of operations research. It comprehensively explores real-world applications, demonstrating how various operations' research techniques enhance edge computing's efficiency, reliability and resource allocation. Innovative solutions for dynamic task scheduling, load balancing and data management, all tailored to the unique challenges of edge environments, are displayed. Starting with operation research methodologies with foundations, applications and research challenges in edge computing and an overview of digital education, this book continues with an exploration of applications in the health sector using IoT, intelligent payment procedures and performance measurement of edge computing, using edge computing and operation research. Smart or AI-based applications are also explored further on and the book ends with insight into ultralightweight and security protocols with solutions for IoT using blockchain.
Blockchain: Principles and Applications in IoT covers all the aspects of Blockchain and its application in IOT. The book focuses on Blockchain, its features, and the core technologies that are used to build the Blockchain network. The gradual flow of chapters traces the history of blockchain from cryptocurrencies to blockchain technology platforms and applications that are adopted by mainstream financial and industrial domains worldwide due to their ease of use, increased security and transparency. Focuses on application of Blockchain on IoT domain Focuses on Blockchain as a data repository Most books on Blockchain cover bitcoins and crypto currency. This book will also cover blockchain in other areas like healthcare, supply chain management, etc Covers consensus algorithms like PAROX, RAFT etc. and its applicationsThis book is primarily aimed at graduates and researchers in computer science and IT.
CONVERGENCE OF DEEP LEARNING IN CYBER-IOT SYSTEMS AND SECURITY In-depth analysis of Deep Learning-based cyber-IoT systems and security which will be the industry leader for the next ten years. The main goal of this book is to bring to the fore unconventional cryptographic methods to provide cyber security, including cyber-physical system security and IoT security through deep learning techniques and analytics with the study of all these systems. This book provides innovative solutions and implementation of deep learning-based models in cyber-IoT systems, as well as the exposed security issues in these systems. The 20 chapters are organized into four parts. Part I gives the various approaches that have evolved from machine learning to deep learning. Part II presents many innovative solutions, algorithms, models, and implementations based on deep learning. Part III covers security and safety aspects with deep learning. Part IV details cyber-physical systems as well as a discussion on the security and threats in cyber-physical systems with probable solutions. Audience Researchers and industry engineers in computer science, information technology, electronics and communication, cybersecurity and cryptography.
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