0%

[UCSD CSE120]分布式系统-distributed system

本文是我在上UCSD的 CSE 120: Principles of Operating Systems (Winter 2020) 整理的笔记,这一课主要介绍了分布式系统中最基础的一些概念的方法。

Basic

  1. What is a distributed system?

    • Cooperating processes in a computer network
    • Degree of integration

      • Loose: Internet applications, email, web browsing
      • Medium: remote execution, remote file systems
      • Tight: process migration, distributed file systems
    • Advantage

      • Speed: parallelism, less contention
      • Reliability: redundancy, fault tolerance, “NSPF”
      • Scalability: incremental growth, economy of scale
      • Geographic distribution: low latency, reliability
    • Disadvantages

      • Fundamental problems of decentralized control

        • State uncertainty: no shared memory or clock
        • Action uncertainty: matually conflicting decisions
      • Distributed algorithms are complex

  2. Is distribution better?

    • Single fast server with single queue
    • Multiple slower servers with separate queues

      • Typically better than the first one
    • Multiple slower servers, single queue

      • Better than the first two
    • Little’s Law: $N = \lambda W$

      • Use to calculate processing time (assuming stable)

Models used in cooperating system

  1. The Client/Server Model

    • Client

      • Short-lived process that makes requests
      • “User-side” of application
    • Server

      • Exports well-defined requests/response interface
      • Long-lived process that waits for requests
      • Upon receiving request, carries it out (may spawn)
  2. Peer-to-Peer

    • A peer talks directly with another peer

      • No intermediary (e.g., central servel) involved
      • Symmetric (unlike asymmetric client/server)
    • In actuality, may be dynamic client/server

      • A requests file from B; A acts as client, B as server
      • C can now request file from A; A acts as server

Distributed Algorithms

  1. Event ordering

    • Order events given no shared clock/memory
    • Happened-before relations: $\rightarrow$

      • A, B events in same process and A before B: $A\rightarrow B$
      • A is a send event, B is a receive event: $A\rightarrow B$
      • If $A\rightarrow B$ and $B\rightarrow C$, then $A\rightarrow C$
    • Implementation

      • Timestamp all events based on local clock
      • Upon receiving a message, advance local clock
      • Resolve ties by ordering machines
    • Example

      • Example 1 (When timing conflicting, follow rules above):

      • Example 2:

  2. Leader election

    • Many distributed algorithms rely on leader
    • Need to determine if leader exists; if not elect
    • Bully algorithm (elect leader L)

      • Every process is numbered (priority): P1, P2, …
      • $P_j$ sends request to L, no reply; tries to elect itself
      • $Pj$ sends “Can I be leader?” to all $P{k>j}$
      • No replies, $Pj$ sends to all $P{i<j}$, “I am leader”, done
      • If some $P_{k>j}$ replies, $P_j$ let $P_k$ try to elect itself
      • If no message from $P_k$, $P_j$ tries to elect itself again
  3. Mutual exclusion

    • Centralized approach

      • Single process acts as coordinator server
      • Request, reply (to allow entrance), release
    • Distributed approach

      • Process sends time-stamped request to all others
      • Waits until it receives replies from all (ok to other)
      • Enter critical section (may get requests, defers)
      • Upon exiting, responds (to release) to all deferred
      • Use timestamps to order “simultaneous” requests