Decentralized Systems and Distributed Computing


Book Description

This book provides a comprehensive exploration of next-generation internet, distributed systems, and distributed computing, offering valuable insights into their impact on society and the future of technology. The use of distributed systems is a big step forward in IT and computer science. As the number of tasks that depend on each other grows, a single machine can no longer handle all of them. Distributed computing is better than traditional computer settings in several ways. Distributed systems reduce the risks of a single point of failure, making them more reliable and able to handle mistakes. Most modern distributed systems are made to be scalable, which means that processing power can be added on the fly to improve performance. The internet of the future is meant to give us freedom and choices, encourage diversity and decentralization, and make it easier for people to be creative and do research. By making the internet more three-dimensional and immersive, the metaverse could introduce more ways to use it. Some people have expressed negative things about the metaverse, and there is much uncertainty regarding its future. Analysts in the field have pondered if the metaverse will differ much from our current digital experiences, and if so, whether people will be willing to spend hours per day exploring virtual space while wearing a headset. This book will look at the different aspects of the next-generation internet, distributed systems, distributed computing, and their effects on society as a whole.




Decentralized Systems and Distributed Computing


Book Description

This book provides a comprehensive exploration of next-generation internet, distributed systems, and distributed computing, offering valuable insights into their impact on society and the future of technology. The use of distributed systems is a big step forward in IT and computer science. As the number of tasks that depend on each other grows, a single machine can no longer handle all of them. Distributed computing is better than traditional computer settings in several ways. Distributed systems reduce the risks of a single point of failure, making them more reliable and able to handle mistakes. Most modern distributed systems are made to be scalable, which means that processing power can be added on the fly to improve performance. The internet of the future is meant to give us freedom and choices, encourage diversity and decentralization, and make it easier for people to be creative and do research. By making the internet more three-dimensional and immersive, the metaverse could introduce more ways to use it. Some people have expressed negative things about the metaverse, and there is much uncertainty regarding its future. Analysts in the field have pondered if the metaverse will differ much from our current digital experiences, and if so, whether people will be willing to spend hours per day exploring virtual space while wearing a headset. This book will look at the different aspects of the next-generation internet, distributed systems, distributed computing, and their effects on society as a whole.




Decentralized Computing Using Blockchain Technologies and Smart Contracts: Emerging Research and Opportunities


Book Description

Recent innovations have created significant developments in data storage and management. These new technologies now allow for greater security in databases and other applications. Decentralized Computing Using Blockchain Technologies and Smart Contracts: Emerging Research and Opportunities is a concise and informative source of academic research on the latest developments in block chain innovation and their application in contractual agreements. Highlighting pivotal discussions on topics such as cryptography, programming techniques, and decentralized computing, this book is an ideal publication for researchers, academics, professionals, students, and practitioners seeking content on utilizing block chains with smart contracts.




Distributed Systems


Book Description

This second edition of Distributed Systems, Principles & Paradigms, covers the principles, advanced concepts, and technologies of distributed systems in detail, including: communication, replication, fault tolerance, and security. Intended for use in a senior/graduate level distributed systems course or by professionals, this text systematically shows how distributed systems are designed and implemented in real systems.




Distributed Computing to Blockchain


Book Description

Distributed Computing to Blockchain: Architecture, Technology, and Applications provides researchers, computer scientists, and data scientists with a comprehensive and applied reference covering the evolution of distributed systems computing into blockchain and associated systems. Divided into three major sections, the book explores the basic topics in the blockchain space extending from distributed systems architecture, distributed ledger, decentralized web to introductory aspects of cryptoeconomics (cryptography and economics) of decentralized applications. The book further explores advanced concepts such as smart contracts; distributed token mining, initial coin offerings; proof of work; public, private, and other blockchains; cryptography; security; and blockchains. The book goes on to review byzantine fault tolerance, distributed ledgers versus blockchains, and blockchain protocols. The final section covers multiple use cases and applications of distributed computing and the future directions for blockchains. - Presented as a focused reference handbook describing the evolution of distributed systems, blockchain, and consensus algorithms emphasizing the architectural and functional aspects - Integrates the various concepts of cryptography in blockchain and further extends to blockchain forensics - Provides insight and detailed Interpretation of algorithms for consensus in blockchains




Decentralized Estimation and Control for Multisensor Systems


Book Description

Decentralized Estimation and Control for Multisensor Systems explores the problem of developing scalable, decentralized estimation and control algorithms for linear and nonlinear multisensor systems. Such algorithms have extensive applications in modular robotics and complex or large scale systems, including the Mars Rover, the Mir station, and Space Shuttle Columbia. Most existing algorithms use some form of hierarchical or centralized structure for data gathering and processing. In contrast, in a fully decentralized system, all information is processed locally. A decentralized data fusion system includes a network of sensor nodes - each with its own processing facility, which together do not require any central processing or central communication facility. Only node-to-node communication and local system knowledge are permitted. Algorithms for decentralized data fusion systems based on the linear information filter have been developed, obtaining decentrally the same results as those in a conventional centralized data fusion system. However, these algorithms are limited, indicating that existing decentralized data fusion algorithms have limited scalability and are wasteful of communications and computation resources. Decentralized Estimation and Control for Multisensor Systems aims to remove current limitations in decentralized data fusion algorithms and to extend the decentralized principle to problems involving local control and actuation. The text discusses: Generalizing the linear Information filter to the problem of estimation for nonlinear systems Developing a decentralized form of the algorithm Solving the problem of fully connected topologies by using generalized model distribution where the nodal system involves only locally relevant states Reducing computational requirements by using smaller local model sizes Defining internodal communication Developing estima




Distributed Computing by Mobile Entities


Book Description

Distributed Computing by Mobile Entities is concerned with the study of the computational and complexity issues arising in systems of decentralized computational entities operating in a spatial universe Encompassing and modeling a large variety of application environments and systems, from robotic swarms to networks of mobile sensors, from software mobile agents in communication networks to crawlers and viruses on the web, the theoretical research in this area intersects distributed computing with the fields of computational geometry (especially for continuous spaces), control theory, graph theory and combinatorics (especially for discrete spaces). The research focus is on determining what tasks can be performed by the entities, under what conditions, and at what cost. In particular, the central question is to determine what minimal hypotheses allow a given problem to be solved. This book is based on the lectures and tutorial presented at the research meeting on “Moving and Computing" (mac) held at La Maddalena Island in June 2017. Greatly expanded, revised and updated, each of the lectures forms an individual Chapter. Together, they provide a map of the current knowledge about the boundaries of distributed computing by mobile entities.




Distributed Algorithms


Book Description

A comprehensive guide to distributed algorithms that emphasizes examples and exercises rather than mathematical argumentation.




Decentralized Spatial Computing


Book Description

Computing increasingly happens somewhere, with that geographic location important to the computational process itself. Many new and evolving spatial technologies, such as geosensor networks and smartphones, embody this trend. Conventional approaches to spatial computing are centralized, and do not account for the inherently decentralized nature of "computing somewhere": the limited, local knowledge of individual system components, and the interaction between those components at different locations. On the other hand, despite being an established topic in distributed systems, decentralized computing is not concerned with geographical constraints to the generation and movement of information. In this context, of (centralized) spatial computing and decentralized (non-spatial) computing, the key question becomes: "What makes decentralized spatial computing special?" In Part I of the book the author covers the foundational concepts, structures, and design techniques for decentralized computing with spatial and spatiotemporal information. In Part II he applies those concepts and techniques to the development of algorithms for decentralized spatial computing, stepping through a suite of increasingly sophisticated algorithms: from algorithms with minimal spatial information about their neighborhoods; to algorithms with access to more detailed spatial information, such as direction, distance, or coordinate location; to truly spatiotemporal algorithms that monitor environments that are dynamic, even using networks that are mobile or volatile. Finally, in Part III the author shows how decentralized spatial and spatiotemporal algorithms designed using the techniques explored in Part II can be simulated and tested. In particular, he investigates empirically the important properties of a decentralized spatial algorithm: its computational efficiency and its robustness to unavoidable uncertainty. Part III concludes with a survey of the opportunities for connecting decentralized spatial computing to ongoing research and emerging hot topics in related fields, such as biologically inspired computing, geovisualization, and stream computing. The book is written for students and researchers of computer science and geographic information science. Throughout the book the author's style is characterized by a focus on the broader message, explaining the process of decentralized spatial algorithm design rather than the technical details. Each chapter ends with review questions designed to test the reader's understanding of the material and to point to further work or research. The book includes short appendices on discrete mathematics and SQL. Simulation models written in NetLogo and associated source code for all the algorithms presented in the book can be found on the author's accompanying website.




Mastering Distributed Computing


Book Description

Uncover the Art of Seamless Distributed Computing with "Mastering Distributed Computing" In the dynamic realm of modern computing, the ability to harness the power of distributed systems is paramount. "Mastering Distributed Computing" is your definitive guide to mastering the art of seamlessly orchestrating distributed resources for optimal performance and scalability. Whether you're an experienced software engineer or a newcomer to the world of distributed computing, this book equips you with the knowledge and skills needed to navigate the intricacies of distributed systems. About the Book: "Mastering Distributed Computing" takes you on an enlightening journey through the intricacies of distributed computing, from foundational concepts to advanced techniques. From distributed architectures to consensus algorithms, this book covers it all. Each chapter is meticulously designed to provide both a deep understanding of the concepts and practical applications in real-world scenarios. Key Features: · Foundational Principles: Build a strong foundation by understanding the core principles of distributed systems, including scalability, fault tolerance, and data consistency. · Distributed Architectures: Explore a range of distributed architectures, including client-server, peer-to-peer, microservices, and serverless, understanding their strengths and applications. · Consistency and Replication: Dive into the complexities of data consistency and replication strategies, including eventual consistency, strong consistency, and distributed databases. · Distributed Algorithms: Master fundamental distributed algorithms, such as leader election, distributed locking, and distributed transactions, for coordinating actions across nodes. · Scaling Strategies: Discover strategies for scaling distributed systems horizontally and vertically, ensuring optimal performance as workloads grow. · Fault Tolerance: Understand mechanisms for building fault-tolerant systems, including redundancy, replication, and failure detection and recovery. · Real-World Use Cases: Gain insights from real-world examples spanning industries, from finance and e-commerce to social media and beyond. · Cloud and Edge Computing: Explore the role of distributed computing in cloud environments and edge computing scenarios, and their impact on modern applications. · Security and Privacy: Explore best practices for securing distributed systems, data encryption, access control, and compliance. Who This Book Is For: "Mastering Distributed Computing" is designed for software engineers, architects, developers, and anyone passionate about effective distributed system design. Whether you're seeking to enhance your skills or embark on a journey toward becoming a distributed computing expert, this book provides the insights and tools to navigate the complexities of distributed systems. © 2023 Cybellium Ltd. All rights reserved. www.cybellium.com