6.824 2021 Lecture 1: Introduction

本文探讨了P2P和分布式的关系,指出分布式系统通过复制实现容错,并强调了在分布式环境中实现一致性、容错性和性能之间的权衡。重点介绍了MapReduce(MR)模型,解释了其工作原理,如数据本地化以减少网络使用,负载均衡策略,以及如何处理故障以确保高可用性和确定性。此外,文章还讨论了MR在处理大规模数据时面临的挑战和局限性,以及它对现代分布式计算的影响。
What is a distributed system?
  multiple cooperating computers
  storage for big web sites, MapReduce, peer-to-peer sharing, &c
  lots of critical infrastructure is distributed

P2P和分布式的关系?因为节点之间都是平等的?

Why do people build distributed systems?
  to increase capacity via parallelism
  to tolerate faults via replication
  to place computing physically close to external entities
  to achieve security via isolation

分布式能处理更多请求,所以增加了容量?

通过replication容错

因为是分布式,所以把一些计算设施放到某些entity附近?

安全,isolation?和分布式的关系是?

But:
  many concurrent parts, complex interactions
  must cope with partial failure
  tricky to realize performance potential

各节点之间需要通信,交互;

可能有partial failure

要实现很好的scale很难

Why take this course?
  interesting -- hard problems, powerful solutions
  used by real systems -- driven by the rise of big Web sites
  active research area -- important unsolved problems
  hands-on -- you'll build real systems in the labs
Course components:
  lectures
  papers
  two exams
  labs
  final project (optional)
Lectures:
  big ideas, paper discussion, and labs
  will be video-taped, available online
Papers:
  research papers, some classic, some new
  problems, ideas, implementation details, evaluation
  many lectures focus on papers
  please read papers before class!
  each paper has a short question for you to answer
  and we ask you to send us a question you have about the paper
  submit question&answer before start of lecture
Labs:
  goal: deeper understanding of some important techniques
  goal: experience with distributed programming
  first lab is due a week from Friday
  one per week after that for a while
Lab 1: MapReduce
Lab 2: replication for fault-tolerance using Raft
Lab 3: fault-tolerant key/value store
Lab 4: sharded key/value store
This is a course about infrastructure for applications.
  * Storage.
  * Communication.
  * Computation.
The big goal: abstractions that hide the complexity of distribution.

infrastructure!存储,通信,计算

目标是屏蔽分布式的技术细节(专注于业务,框架的目的其实都差不多)

Topic: fault tolerance
  1000s of servers, big network -> always something broken
    We'd like to hide these failures from the application.
  We often want:
    Availability -- app can make progress despite failures
    Recoverability -- app will come back to life when failures are repaired
  Big idea: replicated servers.
    If one server crashes, can proceed using the other(s).
    
MATLAB主动噪声和振动控制算法——对较大的次级路径变化具有鲁棒性内容概要:本文主要介绍了一种在MATLAB环境下实现的主动噪声和振动控制算法,该算法针对较大的次级路径变化具有较强的鲁棒性。文中详细阐述了算法的设计原理与实现方法,重点解决了传统控制系统中因次级路径动态变化导致性能下降的问题。通过引入自适应机制和鲁棒控制策略,提升了系统在复杂环境下的稳定性和控制精度,适用于需要高精度噪声与振动抑制的实际工程场景。此外,文档还列举了多个MATLAB仿真实例及相关科研技术服务内容,涵盖信号处理、智能优化、机器学习等多个交叉领域。; 适合人群:具备一定MATLAB编程基础和控制系统理论知识的科研人员及工程技术人员,尤其适合从事噪声与振动控制、信号处理、自动化等相关领域的研究生和工程师。; 使用场景及目标:①应用于汽车、航空航天、精密仪器等对噪声和振动敏感的工业领域;②用于提升现有主动控制系统对参数变化的适应能力;③为相关科研项目提供算法验证与仿真平台支持; 阅读建议:建议读者结合提供的MATLAB代码进行仿真实验,深入理解算法在不同次级路径条件下的响应特性,并可通过调整控制参数进一步探究其鲁棒性边界。同时可参考文档中列出的相关技术案例拓展应用场景。
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