Distributed computing



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distcomp

EXERCISE

  • Suppose that the symbol after y is y’ and y’  y.
  • Then can S send y’ as soon as it receives ack to y? (Assume R has a way of knowing that it received y and y’ correctly.)
  • S sends y
  • R sends ack
  • S sends y’
  • R sends ack …
  • y
  • Ack
  • y’
  • Kr y
  • Kr y’; Kr Ks Kr y
  • R
  • S
  • Ks Kr y

ENCODING PROTOCOL IN 0’s and 1’s

  • Protocol Symbol
  • Encoding
  • Blank
  • 11
  • 0
  • 00
  • ack
  • 0
  • 1
  • 01
  • ack3
  • 1
  • ack2
  • 10
  • WHAT IS SENT
  • S
  • R
  • 0
  • 1
  • blank
  • ack2
  • 0
  • 1
  • ack
  • ack3
  • 10
  • 00
  • 01
  • 11
  • WHAT IS SENT

WHAT DO WE WANT FROM AN ENCODING?

  • Unique decidability. If e(x) is received uncorrupted, then recipient knows that it is uncorrupted and is an encoding of x.
  • Corruption detectability. If e(x) is corrupted, the recipient knows that it is.
  • Thus, receiver knows when it receives good data and when it receives a garbled message.

ENCODING FOR DELETIONS AND MUTATIONS

  • Recall that mutation means that a 0 can become a 1 or vice versa.
  • Encoding (b is blank)
  • Protocol Symbol
  • Encoding
  • Blank
  • bbb1
  • 0
  • 1bb b
  • ack
  • 1b
  • 1
  • b1b b
  • ack3
  • b1
  • ack2
  • bb1 b
  • The same extended alphabet protocol will work.
  • Any insertion will result in two non-blank characters. A mutation can only change a 1 to a 0.
  • Note:
  • S
  • S
  • S
  • R
  • R
  • R
  • ack
  • ack2
  • ack3

Exercise for you

  • Suppose we had deletion errors (1 becomes blank or 0 becomes blank) and insertion errors (blank becomes 0 or blank becomes 1), but no mutation errors (so 1 never becomes 0 and 0 never becomes 1).
  • Now try mutation and insertion.

Self-Stabilizing Systems

  • A distributed system is self-stabilizing if, when started from an arbitrary initial configuration, it is guaranteed to reach a legitimate configuration as execution progresses, and once a legitimate configuration is achieved, all subsequent configurations remain legitimate.

Self-Stabilizing Systems (using invariants)

  • There is an invariant I which implies a safety condition S.
  • When failures occur, S is maintained though I may not be.
  • However when the failures go away, I returns.
  • http://theory.lcs.mit.edu/classes/6.895/fall02/papers/Arora/masking.pdf

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