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Introduction to Distributed Computing: Models, Algorithms, and Systems

This lecture provides an introduction to distributed computing, covering topics such as distributed computation models, synchronous and asynchronous network algorithms, fault-tolerant algorithms, and more.

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Introduction to Distributed Computing: Models, Algorithms, and Systems

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  1. Lecture 7: Introduction to Distributed Computing

  2. Distribute Systems and Distributed Computing Wei Chen, Professor Tennessee State University Contents • Introduction of Distributed Systems • Distributed Computation Models • Synchronous Network Algorithms • Asynchronous Network Algorithms • Clock in Asynchronous Distributed Systems and Snapshot algorithms • Fault-Tolerant Algorithms

  3. network Construction of Distributed Systems Units of A Distributed System: • Units/Nodes (Computers, sensors, … ) • Network • Software

  4. What Is Distribute Systems? There is no unique definition for distributed systems. Similar terms are • Networked system • parallel systems • Concurrent systems • Decentralized systems Enslow’s Definition Distributed System = Distributed hardware + Distributed control + Distributed data

  5. Physically shared memory Physically distributed memory processor processor processor processor processor processor memory memory memory Network Network memory Distributed Hardware Physically shared/distributed memory and logically shared/distributed memory

  6. Distributed System Software • Cooperating the actions of units (computers, sensors, …) • Supporting system resources (hard ware and software) sharing. • Supporting data sharing.

  7. Distributed Control • Master/Slave (fixed/dynamic) • Multi control points (homogenous/heterogeneous) Distributed Data • Copies: Processors hold data copies. • Divided data: Data are divided and distributed to processors.

  8. Features of Distributed Systems • Resource sharing: hardware, software, data • Openness: openness of main interface of the system, scalability of the current system • Concurrency: concurrent execution of the processes, high performance, nice rate of price and performance (PC cluster = poor man’s supercomputer ) • Fault tolerance: ability to tolerate the fault of system units, availability( using potential redundancy to overcome the system fault). • Transparency: a distributed system can be looked as one computer (access transparency, position transparency, parallel transparency,….)

  9. Communication link Computer process Distributed Computational models • Processes: never mind in which unit they are. • Communicating links: communication channels

  10. Process • Generalized RAM (Random Access Machine) CPU with program Infinite memory Message changeable with adjacent processes • Each process has a distinct ID. • Without fault (it will be considered in the model with fault).

  11. Receiving in order of A,B,C Sending in order of A,B,C Communication Links • Bidirectional • Asynchronous • Infinite FIFO queue • Without fault (no massage losing, alteration)

  12. Synchronism • Running speed of each process • Transmission delay • Speed of the local clock in each process: constant upper and lower bounds

  13. Real clock Local clock Real time Local Clock of Synchronous Distribute Systems p(t): the value of the local clock of process p at moment t Typical synchronous distributed model: Round Model • Processes execute each round synchronously Each round consists of message receiving, computation, and message sending • Processes accept the message sent from the previous round.

  14. Complete asynchronous model • No assumption for the speed of processes. • No assumption for the transmission delay of communication links. • No assumption for the speed of local clocks.

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