Exploring the concept of fault attacks in hardware security, this lecture delves into the various techniques used to compromise systems through non-nominal and nominal channels, as well as the potential risks introduced by trojan horses in the IT supply chain. The discussion includes differential fa

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Characterizing Distributed Systems: Multiple autonomous computers with CPUs, memory, storage, and I/O paths, interconnected geographically, shared state, global invariants. Classifying Distributed Systems: Based on synchrony, communication medium, fault models like crash and Byzantine failures. Comp

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In this technical document, we delve into the calculation of fault current and fault apparent power in symmetrical three-phase short circuit scenarios within power systems. Through detailed equivalent circuit diagrams, reactance calculations, and per unit value derivations, the fault current and app

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Apache Spark, developed by Matei Zaharia and team at UC Berkeley, aims to enhance cluster computing by supporting iterative algorithms, interactive data mining, and programmability through integration with Scala. The motivation behind Spark's Resilient Distributed Datasets (RDDs) is to efficiently r

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Distributed Operating Systems (DOS) manage computer resources and provide users with convenient interfaces. Unlike centralized systems, DOS runs on multiple independent CPUs and prioritizes software over hardware. It ensures transparency and fault tolerance, with a focus on software error handling.

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Byzantine fault tolerance is crucial in ensuring the reliability of distributed systems, especially in the presence of malicious nodes. This concept deals with normal faults, crash faults, and the challenging Byzantine faults, where nodes can exhibit deceptive behaviors. The Byzantine Generals Probl

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This course, led by Assistant Professor Marco Canini, delves into the technical aspects of blockchain technologies, distributed consensus, and secure software engineering. Students will engage in flipped classroom-style classes and paper presentations, critiquing research papers, defending research

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This content discusses the challenges of storing vast amounts of digital data in distributed systems, exploring strategies like duplication, Reed-Solomon codes, and degraded reads for fault tolerance and quick recovery in the face of disk failures. It highlights the importance of efficient data stor

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Explore the essential methods and techniques for fault diagnosis in mechanical and electrical systems in industrial settings. Learn to identify different types of faults, utilize fault-finding aids, and rectify issues promptly to prevent future failures. Discover industry-recognized fault diagnosing

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Autoimmunity is a condition where the body's immune cells mistakenly attack its own tissues, leading to damage. Immunological tolerance helps prevent this by mechanisms like central and peripheral tolerance. Central tolerance involves deleting self-reactive immune cells during maturation in key orga

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Distributed DBMS reliability is crucial for ensuring continuous user request processing despite system failures. This chapter delves into fundamental definitions, fault classifications, and types of faults like hard and soft failures in distributed systems. Understanding reliability concepts helps i

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This guide by British Telecommunications plc provides detailed instructions on raising a Customer Controlled Special Faults Investigation (CCSFI) fault. It covers topics such as Version Control, Best Practices for Knowledge Based Diagnostics (KBD) and CCSFI, logging in, and step-by-step guidance for

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Byzantine Fault Tolerance (BFT) is a critical concept in computer science, addressing faults in distributed systems. This summary covers the types of faults (normal, crash, Byzantine), implications of Byzantine faults, Byzantine Generals Problem, impossibility results, and the complexity of solving

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HDFS (Hadoop Distributed File System) is designed for handling large data sets across commodity hardware. It emphasizes throughput over latency and is well-suited for batch processing applications. The architecture includes components like NameNode (master) and DataNode (participants), focusing on s

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MapReduce is a powerful paradigm that enables distributed processing of large datasets by dividing the workload among multiple machines. It tackles challenges such as scaling, fault tolerance, and parallel processing efficiently. Through a series of operations involving mappers and reducers, MapRedu

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Explore the potential of blockchain and distributed ledger technologies in enhancing IoT systems, focusing on privacy, security, and safety. The workshop discusses the benefits and challenges of implementing DLT, as well as a reference IoT scenario in the manufacturing industry. Discover how DLT ena

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This study delves into Byzantine Fault Tolerance (BFT) protocols in the realm of distributed ledgers, exploring the complexities of achieving consensus in trusted adversarial environments. The research examines the classic problem in computer science where distributed nodes communicate to reach agre

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Economic and technical aspects of Byzantine Fault Tolerance (BFT) protocols for achieving consensus in distributed ledger systems are explored. The discussion delves into the challenges of maintaining trust in adversarial environments and the strategies employed by non-Byzantine nodes to mitigate un

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Raft is a consensus algorithm designed for replicated state machines to ensure fault tolerance and reliable service in distributed systems. It provides leader election, log replication, safety mechanisms, and client interactions for maintaining consistency among servers. The approach simplifies oper

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Raft is a consensus algorithm designed for fault-tolerant replication of logs in distributed systems. It ensures that multiple servers maintain identical states for fault tolerance in various services like file systems, databases, and key-value stores. Raft employs a leader-based approach where one

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Fast and accurate fault detection and location are crucial in power grid management, especially in smart grids with bidirectional power flow. This study explores various fault location methods including impedance-based and travelling waves-based approaches. It also discusses the use of Intelligent E

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The Fault Localization (Pinpoint) project proposal aims to pinpoint the exact source of failures within a cloud NFV networking environment by utilizing a set of algorithms and APIs. The proposal includes an overview of the fault localization process, an example scenario highlighting the need for fau

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The research discusses the challenges faced by traditional RAID systems in maintaining data reliability and proposes a solution using High-Parity GPU-Based RAID. It highlights the limitations of current technologies in fault tolerance, the inaccuracies in disk failure statistics, and the significanc

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RAID 5 is a popular technology for managing multiple storage devices within a single array, providing fault tolerance through data striping and parity blocks. This article discusses the principles of fault tolerance in RAID 5, the calculation of parity blocks, handling degraded mode in case of disk

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Distributed software engineering plays a crucial role in modern enterprise computing systems where large computer-based systems are distributed over multiple computers for improved performance, fault tolerance, and scalability. This involves resource sharing, openness, concurrency, and fault toleran

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PSync is a language designed by Cezara Drăgoi, Thomas A. Henzinger, and Damien Zufferey to simplify the implementation and reasoning of fault-tolerant distributed algorithms. It introduces a DSL with key elements like communication-closed rounds, an adversary environment model, and efficient runtim

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This lecture covers the concept of Paxos and achieving consensus in distributed systems. It discusses the availability of P/B-based RSM, RSM via consensus, the context for today's lecture, and desirable properties of solutions. The analogy of the US Senate passing laws is used to explain the need fo

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Consensus algorithms play a vital role in distributed systems like Paxos. Paxos is a protocol that aims to achieve consensus among a majority of participants. It defines roles for nodes like proposers, acceptors, and learners, each serving a specific purpose in reaching agreement on a single value.

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The CAP Theorem, as discussed by Seth Gilbert and Nancy A. Lynch, highlights the tradeoffs between Consistency, Availability, and Partition Tolerance in distributed systems. It explains how a distributed service cannot provide all three aspects simultaneously, leading to practical compromises and re

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In this lecture, Mohammad Hammoud discusses the concept of Distributed Hash Tables (DHT) in distributed systems, focusing on key aspects such as classes of naming, Chord DHT, node entities, key resolution algorithms, and the key resolution process in Chord. The session covers various components of D

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The discussion revolves around achieving consensus in the presence of dense Byzantine faults on an unknown torus. Various challenges and impossibility theorems are explored, highlighting the complexities of reaching an agreement in such fault-prone environments. The content delves into the limitatio

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Erasure coding is a fault-tolerance technique used in modern data centers to minimize data redundancy and increase reliability. This paper explores practical updates in erasure coding, highlighting the challenges of high update penalties and proposing cross-rack-aware strategies to mitigate cross-ra

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Client-server paradigm in distributed systems involves structuring systems as collaborating processes where clients request services from servers. The model follows a request/reply protocol, with servers providing centralized control of shared resources. Advantages include security and simplicity, w

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Distributed Ledger Technology (DLT) involves core concepts like assets, ledgers, transactions, states, conditions, and inferences. It also includes distributed ledgers, cryptographic hash functions, construction of a blockchain, consensus mechanisms like proof of work, and examples of applications s

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Raft is a consensus algorithm designed by Diego Ongaro and John Ousterhout at Stanford University for practical systems. It simplifies understanding through leader-follower structure and terms for leader election. Nodes transition between Follower, Leader, and Candidate states, initiating elections

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This document provides an insightful introduction to consensus with the Raft algorithm, explaining its key concepts, including distributed system availability versus consistency, the importance of eliminating single points of failure, the need for consensus in building consistent storage systems, an

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Consensus in distributed systems involves getting multiple servers to agree on a state. The Raft Consensus Algorithm, designed by Diego Ongaro and John Ousterhout from Stanford University, aims to make achieving consensus easier compared to other algorithms like Paxos. Raft utilizes a leader-based a

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The Raft Consensus Protocol, introduced by Prof. Smruti R. Sarangi, offers a more understandable and easier-to-implement alternative to Paxos for reaching agreement in distributed systems. Key concepts include replicated state machine model, leader election, and safety properties ensuring data consi

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Addressing challenges in distributed systems, this study proposes a novel approach by combining PBFT and Raft consensus mechanisms to enhance scalability and fault tolerance. The research highlights the importance of secure data storage and identifies new attack mechanisms in today's digital landsca

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Strong consistency and the CAP theorem play a crucial role in the design and implementation of distributed systems. This content explores different consistency models such as 2PC, consensus, eventual consistency, Paxos, and Raft, highlighting the importance of maintaining ordering and fault-toleranc

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