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).
    
【直流微电网】径向直流微电网的状态空间建模与线性化:一种耦合DC-DC变换器状态空间平均模型的方法 (Matlab代码实现)内容概要:本文介绍了径向直流微电网的状态空间建模与线性化方法,重点提出了一种基于耦合DC-DC变换器状态空间平均模型的建模策略。该方法通过对系统中多个相互耦合的DC-DC变换器进行统一建模,构建出整个微电网的集中状态空间模型,并在此基础上实施线性化处理,便于后续的小信号分析与稳定性研究。文中详细阐述了建模过程中的关键步骤,包括电路拓扑分析、状态变量选取、平均化处理以及雅可比矩阵的推导,最终通过Matlab代码实现模型仿真验证,展示了该方法在动态响应分析和控制器设计中的有效性。; 适合人群:具备电力电子、自动控制理论基础,熟悉Matlab/Simulink仿真工具,从事微电网、新能源系统建模与控制研究的研究生、科研人员及工程技术人员。; 使用场景及目标:①掌握直流微电网中多变换器系统的统一建模方法;②理解状态空间平均法在非线性电力电子系统中的应用;③实现系统线性化并用于稳定性分析与控制器设计;④通过Matlab代码复现和扩展模型,服务于科研仿真与教学实践。; 阅读建议:建议读者结合Matlab代码逐步理解建模流程,重点关注状态变量的选择与平均化处理的数学推导,同时可尝试修改系统参数或拓扑结构以加深对模型通用性和适应性的理解。
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