Distributed systems - PowerPoint PPT Presentation


Overview of Distributed Systems: Characteristics, Classification, Computation, Communication, and Fault Models

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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Overview of Distributed Operating Systems

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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Understanding CS 394B: Blockchain Systems and Distributed Consensus

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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Understanding Distributed Mutual Exclusion in Operating Systems

In distributed systems, the problem of mutual exclusion arises when multiple sites/processes need to access shared resources concurrently. Unlike in single-computer systems, distributed systems lack shared memory, leading to the need for communication-based approaches rather than shared variables li

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Understanding Parallel and Distributed Computing Systems

In parallel computing, processing elements collaborate to solve problems, while distributed systems appear as a single coherent system to users, made up of independent computers. Contemporary computing systems like mobile devices, IoT devices, and high-end gaming computers incorporate parallel and d

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Designing Distributed and Internet Systems

Learn about the design considerations for distributed and internet systems, including file server versus client/server environments, cloud computing trends, internet standards, and system development life cycle. Explore designing systems for local area networks (LANs) and the process of creating dis

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Understanding Remote Method Invocation (RMI) in Distributed Systems

A distributed system involves software components on different computers communicating through message passing to achieve common goals. Organized with middleware like RMI, it allows for interactions across heterogeneous networks. RMI facilitates building distributed Java systems by enabling method i

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Understanding Remote Method Invocation (RMI) in Distributed Systems

A distributed system involves components on different computers communicating to achieve a common goal. Middleware, like RMI, helps organize these systems. RMI allows Java objects to invoke methods on remote objects, facilitating distributed Java systems. It differs from RPC by focusing on object-or

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Understanding Parallel and Distributed Systems in Computing

A parallel computer is a collection of processing elements that collaborate to solve problems, while a distributed system comprises independent computers appearing as a single system. Contemporary computing systems, like mobile devices and cloud platforms, utilize parallel and distributed architectu

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Understanding Message Passing in Distributed Systems

Explore the key concepts of message passing in distributed systems, covering inter-process communication, desirable features like simplicity, efficiency, and reliability, different methods for information sharing, and the importance of synchronization and buffering. Dive into the intricacies of enco

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Distributed DBMS Reliability Concepts and Measures

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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Understanding Causal Consistency in Distributed Systems

This content covers the concept of causal consistency in computing systems, exploring consistency models such as Causal Linearizability and Eventual Sequential. It explains the importance of logical clocks like Lamport and vector clocks, and how they ensure order in distributed systems. The concept

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Enhancing IoT Systems with Blockchain and Distributed Ledger Technologies

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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Overview of Mutual Exclusion and Memory Models in Distributed Systems

Discussion on fast, randomized mutual exclusion techniques by George Giakkoupis and Philipp Woelfel. Exploring asynchronous shared memory systems with atomic operations. Understanding mutual exclusion principles as outlined by Dijkstra in 1965 and measuring time efficiency in critical sections. Delv

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Economic Models of Consensus on Distributed Ledgers in Blockchain Technology

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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Distributed Algorithms for Leader Election in Anonymous Systems

Distributed algorithms play a crucial role in leader election within anonymous systems where nodes lack unique identifiers. The content discusses the challenges and impossibility results of deterministic leader election in such systems. It explains synchronous and asynchronous distributed algorithms

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Challenges of Time Synchronization in Distributed Systems

Distributed systems face challenges in synchronizing physical time due to varying network paths and clock drifts. While physical time synchronization is useful for tasks like file timestamps, it involves complexities such as estimating communication latency and improving time estimation algorithms l

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Overview of Distributed Systems, RAID, Lustre, MogileFS, and HDFS

Distributed systems encompass a range of technologies aimed at improving storage efficiency and reliability. This includes RAID (Redundant Array of Inexpensive Disks) strategies such as RAID levels, Lustre Linux Cluster for high-performance clusters, MogileFS for fast content delivery, and HDFS (Had

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Distributed Software Engineering Overview

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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Understanding Paxos and Consensus in Distributed Systems

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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Challenges in Detecting and Characterizing Failures in Distributed Web Applications

The final examination presented by Fahad A. Arshad at Purdue University in 2014 delves into the complexities of failure characterization and error detection in distributed web applications. The presentation highlights the reasons behind failures, such as limited testing and high developer turnover r

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Google Spanner: A Distributed Multiversion Database Overview

Represented at OSDI 2012 by Wilson Hsieh, Google Spanner is a globally distributed database system that offers general-purpose transactions and SQL query support. It features lock-free distributed read transactions, ensuring external consistency of distributed transactions. Spanner enables property

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Understanding the CAP Theorem in Distributed Systems

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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Understanding Distributed Hash Table (DHT) in Distributed Systems

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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Overview of Peer-to-Peer Systems and Distributed Hash Tables

The lecture discusses Peer-to-Peer (P2P) systems and Distributed Hash Tables, exploring their architecture, benefits, adoption in various areas, and examples such as BitTorrent. It covers the decentralized nature of P2P systems, the challenges they address, and the advantages they offer including hi

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Distributed Database Management and Transactions Overview

Explore the world of distributed database management and transactions with a focus on topics such as geo-distributed nature, replication, isolation among transactions, transaction recovery, and low-latency maintenance. Understand concepts like serializability, hops, and sequence number vectors in ma

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Understanding Client-Server Paradigm in Distributed Systems

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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Understanding Strong Consistency and CAP Theorem in Distributed Systems

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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Distributed Computing Systems Project: Distributed Shell Implementation

Explore the concept of a Distributed Shell in the realm of distributed computing systems, where commands can be executed on remote machines with results returned to users. The project involves building a client-server setup for a Distributed Shell, incorporating functionalities like authentication,

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TrInc: Small Trusted Hardware for Large Distributed Systems

TrInc is a system designed to provide trusted hardware for large distributed systems, aiming to prevent equivocation, ensure trust in distributed systems, and enhance security through various applications and features. Developed by Jacob R. Lorch and team, TrInc offers solutions such as BFT with few

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Understanding Naming Systems in Distributed Systems

Entities in distributed systems are uniquely identified using names, addresses, and identifiers. Naming systems assist in name resolution and can be categorized into flat, structured, and attribute-based naming. Flat naming uses random strings as identifiers, and various mechanisms such as broadcast

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Understanding Peer-to-Peer Systems and Distributed Hash Tables

Explore the concept of Peer-to-Peer (P2P) systems and Distributed Hash Tables (DHTs) through lectures covering topics like Napster, Gnutella, BitTorrent, Chord Lookup Service, and more. Understand the advantages and adoption of P2P systems, with examples like BitTorrent and the lookup problem in a d

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Understanding Computer Networking Basics and Distributed Systems

Computer networks facilitate the sharing of devices and resources like servers, clients, and data, while distributed systems involve components located on different networked computers communicating to achieve common goals. Types of computer networks include LAN, PAN, MAN, and WAN. Distributed syste

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Overview of Ceph Distributed File System

Ceph is a scalable, high-performance distributed file system designed for excellent performance, reliability, and scalability in very large systems. It employs innovative strategies like distributed dynamic metadata management, pseudo-random data distribution, and decoupling data and metadata tasks

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Overview of Ceph: A Scalable Distributed File System

Ceph is a high-performance distributed file system known for its excellent performance, reliability, and scalability. It decouples metadata and data operations, leverages OSD intelligence for complexity distribution, and utilizes adaptive metadata cluster architecture. Ceph ensures the separation of

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Distributed Transaction Management in CSCI 5533 Course

Exploring transaction concepts and models in distributed systems, Team 5 comprising Dedeepya, Dodla, Ehtheshamuddin, and Hari Kishore under the guidance of Dr. Andrew Yang delve into the intricacies of distributed transaction management in CSCI 5533 Distributed Information Systems.

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Concurrency Control and Coordinator Election in Distributed Systems

This content delves into the key concepts of concurrency control and coordinator election in distributed systems. It covers classical concurrency control mechanisms like Semaphores, Mutexes, and Monitors, and explores the challenges and goals of distributed mutual exclusion. Various approaches such

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Quantum Distributed Proofs for Replicated Data

This research explores Quantum Distributed Computing protocols for tasks like leader election, Byzantine agreement, and more. It introduces Quantum dMA protocols for verifying equality of replicated data on a network without shared randomness. The study discusses the need for efficient protocols wit

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Distributed Systems: Remote Procedure Calls and Communication Paradigms

Explore the fundamentals of distributed systems, focusing on remote procedure calls, communication paradigms, and middleware layers. Learn how entities communicate in distributed systems, classification of communication paradigms, and the role of middleware in facilitating communication between appl

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Understanding Consistency Models in Distributed Systems

Consistency models in distributed systems define guarantees about how operations are executed across replicas. Linearizability, a key model, ensures that all replicas execute operations in a total order based on real-time ordering. This principle eliminates stale reads and enforces wall-clock orderi

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