Chapter 3. Synchronization

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Chapter 3. Synchronization
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Synchronization in Distributed Systems

• Synchronization in a single machine
• Same clock
• Shared data for synchronization
• Semaphore for mutual exclusion
• Synchronization in distributed system
• Difficult to handle it
• No same physical clock
• No shared data for synchronization

Machine 1
Machine 2
Semaphore
Remote Access Delay and Error
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Clock

• In distributed systems
• Multiple Physical Clocks No Centralized Clock
• Logical Clock rather than a Global Physical Clock

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Global Clock and Logical Clock

• Global Clock
• TAI (Temps Atomique International) at Paris
• Time Server
• Broadcasting from Satellite
• Granularity
• Logical Clock
• Not absolute time but for ordering
• Lamport Algorithm
• Correction of Clock
• T(A, tx) lt T(B, rx)

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Logical Clock

• Logical Clock
• Not absolute time but for ordering
• Lamport Algorithm
• Correction of Clock
• C(A, tx) lt C(B, rx)

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Global Clock and Time Server

• Global Clock
• TAI (Temps Atomique International) at Paris
• Time Server
• Broadcasting from Satellite
• Granularity
• Global Clock Server
• Adjust local clock
• Cristians Algorithm
• Berkeley Algorithm
• Time never runsbackward

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Global State

• Global State
• States of each local system
• Messages in transit
• Very important to determine the status of
  distributed system
• Example Deadlock Detection
• Distributed Snapshot State of distributed
  systems in a given time

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Mutual Exclusion Monitor (Coordinator)

• In a single system Easy to implement by
  semaphore
• In distributed systems No shared data for
  semaphore
• A Centralized Algorithm
• Simple
• But single point of failure

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Mutual Exclusion Distributed Algorithm

• No central coordinator
• Rule When a system receive a request
• Not in CS or Not to enter OK to requester
• In CS No reply
• To enter compare Timestamp and one with lower
  TS wins

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Mutual Exclusion Token Ring

• One with token can enter CS
• If a system wants to enter CS
• wait Token and process it
• Otherwise, pass token to the next

Wait until it gets the token
Token
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Mutual Exclusion Comparison
of messagesper request delay per request Problem
Monitor 3 2 Crash of monitor
DistributedAlgorithm 2(n-1) 2(n-1) n points of Crash
Token Ring 0 to n-1 0 to n-1 Token lost
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Election Bully Algorithm

• When it is found that a coordinator is required

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Election Ring Algorithm

• When it is found that the coordinator has
  crashed,
• Circulate message with priority

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Distributed Transaction

• Transaction
• Example Flight Reservation

Consistent State
Consistent State
Set of operations
BEGIN_TRANSACTION reserve WP -gt JFK reserve JFK -gt Nairobi reserve Nairobi -gt MalindiEND_TRANSACTION (a) BEGIN_TRANSACTION reserve WP -gt JFK reserve JFK -gt Nairobi reserve Nairobi -gt Malindi full gtABORT_TRANSACTION (b)
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ACID Properties Atomicity and Consistency

• Atomicity.
• All or Nothing
• Not Partially Done
• Example Failure in Flight Reservation
• Consistency.
• Execution of a transaction preserves the
  consistency of the database.

State 1
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Transaction States
PartiallyCommitted
Committed
the initial state the transaction stays in this
state while it is executing
ALL
Active
NOTHING
Failed
Aborted
after the discovery that normal execution can no
longer proceed.
after the transaction has been rolled back and
the database restored to its state prior to the
start of the transaction. - restart the
transaction or - kill the transaction
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ACID Properties Isolation and Durability

• Isolation.
• Although multiple transactions may execute
  concurrently, each transaction must be unaware of
  other concurrently executing transactions.
• Intermediate transaction results must be hidden
  from other concurrently executed transactions.
• Durability.
• After a transaction completes successfully, the
  changes it has made to the database persist, even
  if there are system failures.

DB
Transaction 1
Transaction 2
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Example

• Transaction Transfer 50 from account A to
  account B
• 1. read(A)
• 2. A A 50
• 3. write(A)
• 4. read(B)
• 5. B B 50
• 6. write(B)
• Consistency requirement
• the sum of A and B is unchanged after the
  transaction.
• Atomicity requirement
• Durability
• Isolation

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Example Concurrent Execution

• Two Transactions
• T1 transfer 50 from A to B,
• T2 transfer 10 of the balance from A to B

Serial Schedule
Concurrent Schedule
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Serializability

• What happens after these transactions ?
• Serial Schedule
• Always Correct
• T1? T2 and T2? T1
• Concurrent Schedule
• Serializable if
• Result (T1T2) Result(T1? T2) or
• Result(T2? T1)

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Transaction Atomicity

• Failure during transaction
• Abort the partial execution
• How to discard incomplete transaction
• Deferred updates
• Immediate updates
• Safe transaction
• Decrease failure probability
• Rollback
• Recovery
• Return to initial state
• Without minimum cost

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Safe Transaction

• Decrease the possibility of failure
• Two Phase Commit
• Wedding Ceremony Protocol
• 1st Phase send ready message
• 2nd Phase execute only when OK messages are
  received from all

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Log

• Log
• History of operations
• Used for rollback
• (Transaction, Pre-state, Post-state)
• (Trans, DataItem, OldValue, NewValue)

System
Transaction
operation1
operation2
operation3
log
log
log
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Deferred Updates

• Reflect Logs after Commit
• Shadowing
• If the transaction fails, then discard logs

Transaction
Begin
Write or update operations
operation1
. . .
System
operationn
Commit
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Deferred Updates Recovery
Log File
(T1, begin) (T1, A, 20, 30) (T2, begin) (T1, B,
30, 40) (T2, B, 40, 50) (T1, commit) (T3,
begin) (T2, C, 100, 50) (T2, commit) (T3, D, 10,
20)
1. Transaction with commit OK2. Transaction
with begin but without commit Delete log
records
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Immediate Updates

• Execute operation immediately
• If the transaction fails, undo operations

Transaction
Begin
System
operation1
operation2
operation3
Commit
log
log
log
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Which one is better ?
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Transaction Serializability

• Serialization
• Exchange non-conflict operation
• Conflict operation
• Result(T1.Op,T2.Op) ? Result(T2.Op,T1.Op)
• Time-stamping
• Two Phase Locking

r(a)
w(a)
r(b)
w(b)
Trans 1
Time
r(a)
w(a)
r(b)
w(b)
Trans 2
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Time Stamping

• If conflict occurs, then abort
• For read(T,x), ts(T) lt tsWR(x), then abort T
• For write(T,x), ts(T) lt tsWR(x) or ts(T) lt
  tsRD(x), then abort T

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Two Phase Locking
2PL
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Implementation of Concurrency Control in
Distributed Systems

• Three Managers
• TM (Transaction Manager) Ensure the Atomicity
• Scheduler Main Responsibility for Concurrency
  Control
• DM (Data Manager) Simple Read/Write

In distributed systems
In a single machine