Chapter 5 Synchronization

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Chapter 5Synchronization

• PresenterMaria Riaz

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Sequence of Presentation

• Synchronization
• Clock Synchronization
• Logical Clocks
• Global State
• Election Algorithms
• Mutual Exclusion
• Distributed Transactions

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Synchronization Why we need it !

• Stand-alone System
• Exclusive access to shared resources
• Distributes System
• Exclusive access to shared resources
• Ordering of Events
• Each node in a distributed system has separate
  local clock
• Notion of physical time might differ among
  various nodes of the system

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- Clock Synchronization -

• Problem due to different time values at different
  nodes
• When each machine has its own clock, an event
  that occurred after another event may
  nevertheless be assigned an earlier time

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Physical Clocks (1)

• Can all clocks in a distributed system be
  synchronized ?
• If we start all clocks in the system with same
  initial value, will they remain synchronized for
  the rest of their operations ?
• Some terminology
• Skew instantaneous difference between readings
• Drift different rates of counting time
• physical variations of underlying oscillators
• variance with temperature
• even extremely small differences accumulate over
  a large number of oscillations
• Drift Rate difference in reading bet. a clock
  and a nominal perfect clock per unit of time
  measured by the reference clock
• 10-6 seconds/sec for quartz crystals
• 10-7 - 10-8 seconds/sec for high precision quartz
  crystals
• Problem
• How do we synchronize them with real-world clocks
• How do we synchronize the clocks with each other

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Physical Clocks (2)

• Some methods to measure time
• Mean solar second measuring a large numbers of
  day -- taking average -- dividing by 86400
• TAI (International Atomic Time) the mean number
  of ticks of the cesium 133 clocks (since
  1/1/1958) divided by 9,192,631,770
• Very small drift rate 10-13 seconds/second
• UTC broadcast by NIST from Fort Collins,
  Colorado over shortwave radio station WWV.

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Clock Synchronization Algorithms (1)

• The relation between clock time and UTC when
  clocks tick at different rates
• maximum drift rate (?)
• every ?t seconds, the worst case drift between
  two clocks will be at most 2??t
• to guarantee two clocks never differ by more than
  ?, the clocks must re-synchronize every ?/2?
  seconds

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Clock Synchronization Algorithms (2)

• Centralized Algorithms
• Cristians Algorithm (1989)
• Berkeley Algorithm (1989)
• Decentralized Algorithms
• Averaging Algorithms (e.g. NTP)
• Multiple External Time Sources

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Cristians Algorithm

• Assume one machine (the time server) has a WWV
  receiver and all other machines are to stay
  synchronized with it.
• Every ?/2? seconds, each machine sends a message
  to the time server asking for the current time.
• Time server responds with message containing
  current time, CUTC.
• Problem
• time must never run backward

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Berkeley Algorithm

1. The time daemon asks all the other machines for
   their clock values.
2. The machines answer and the time daemon computes
   the average.
3. The time daemon tells everyone how to adjust
   their clock.

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Averaging Algorithms

• At the beginning of each interval, every machine
  broadcasts the current time according to its
  clock
• Then it starts a local timer to collect all other
  broadcasts that arrive during some interval S
• The simplest algorithm is just to average the
  values from all other machines
• A slightly more sophisticated algorithm
  Discard the m highest and m lowest to reduce the
  effect of a set of faulty clocks
• Another improved algorithm Correct each
  message by adding to the received time an
  estimate of the propagation time from the ith
  source
• extra probe messages are needed to use this
  scheme
• One of the most widely used algorithms in the
  Internet is the Network Time Protocol (NTP)

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- Logical Clocks -

• Mostly absolute time is not important rather
  relative time is of significance
• Internal consistency and ordering of events
• If two process dont interact ? no need for
  synchronization between them
• A logical clock is a
• Monotonically increasing SW counters (COULOURIS)
• Clocks on different computers that are somehow
  consistent (LAMPORT)
• Potential Requirements for logical clocks
• Timestamps C(a), C(b)
• If a happens before b in the same process, C(a) lt
  C(b).
• a ? b gt C(a) lt C(b)
• If a and b represent the sending and receiving of
  a message, respectively, C(a) lt C(b).
• For all distinctive events a and b, C(a) ? C(b).
• Two methods for assigning logical timestamps
• Lamports Timestamps
• Vector Timestamps

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Lamports Timestamps (1)

• Lamport defined a relation happens before. a ?
  b a happens before b (1978)
• Each Process has local clock LCi
• with each local event e LCi LCi 1 e
• with each sending of a message by process Pi LCi
  LCi 1 send (LCi,m)
• with each reception of a message (M,LCm) by Pj
  LCj MAX(LCm, LCj ) LCj LCj 1

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Lmaports Timestamps (2)

• Can be used to implement totally ordered
  multicast
• A multicast operation by which all messages are
  delivered in the same order to each receiver

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Vector Timestamps

• Each process Pi has its own vector clock Ci
• Ci n-dimensional vector (n number of
  processes)
• Notation Cij the timestamp of the last event
  in Pj by which Pi has potentially been effected

• Initially
• all ci 0
• Increment Ci
• -Events
• Send msg
• Receive msg

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- Global State -

• Like a distributed snapshot reflecting a state
  in which the system might have been
• represents the last event recorded for each
  process
• Graphically represented by a cut
• Consistent for every received message, the
  sender can be identified
• Cause ? Effect

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Global State (2)

• Organization of a process and channels for a
  distributed snapshot
• Process Q receives a marker (start) for the first
  time and records its local state
• Q records all incoming message
• Q receives a marker (end) for its incoming
  channel and finishes recording the state of the
  incoming channel
• final recorded state

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- Election Algorithms -

• Election algorithms
• algorithms for electing a coordinator (using this
  as a generic name for the special process)
• attempt to locate the process with the highest
  process number and designate it as coordinator
• Bully Algorithm
• Ring Algorithm
• Goal
• ensure that when an election starts, it concludes
  with all processes agreeing on who the new
  coordinator is to be

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Bully Algorithm

• A process P detects failure of coordinator and
  holds an election to be the coordinator
• All process with ID gt P response
• If P receives such a response, it will step back
• Processes having ID gt P can hold electionsand
  repeat same procedure
• If no response from any process with higher ID,
  election holder becomes the new coordinator
• Example
• Process 4 holds election
• Process 5 and 6 respond, telling 4 to stop
• Now 5 and 6 each hold an election
• Process 6 tells 5 to stop
• Process 6 wins and tells everyone

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Ring Algorithm

• Process detects failure of coordinator
• Send message to neighbor with its ID
• Neighbor adds its ID and pass along
• When all process have added their ID, the one
  with highest ID becomes the coordinator
• The message is rotated once again so everyone
  knows

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- Mutual Exclusion -

• To control access to a critical section
• Centralized Algorithm
• Distributed Algorithm
• Token Ring Algorithm

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Centralized Algorithm

1. Process 1 asks the coordinator for permission to
   enter a critical region. Permission is granted
2. Process 2 then asks permission to enter the same
   critical region. The coordinator does not reply
3. When process 1 exits the critical region, it
   tells the coordinator, when then replies to 2

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Distributed Algorithm

1. Two processes want to enter the same critical
   region at the same moment
2. Process 0 has the lowest timestamp, so it wins
3. When process 0 is done, it sends an OK also, so 2
   can now enter the critical region

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Token Ring Algorithm

• unordered group of processes on a network
• logical ring constructed in software
• A token is passed along the ring to allow access
  to the critical section

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Comparison
Algorithm Messages per entry/exit Delay before entry (in message times) Problems
Centralized 3 2 Coordinator crash
Distributed 2 ( n 1 ) 2 ( n 1 ) Crash of any process Group communication
Token ring 1 to ? 0 to n 1 Lost token, process crash

• A comparison of three mutual exclusion algorithms

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- Distributed Transactions -

• Basic (Flat) Transactions Limitations
• Alternatives
• Distributed Transactions
• Nested Transactions
• Problems
• Concurrency Control
• Synchronization

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The Transaction Model (1)

• Updating a master tape is fault tolerant

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The Transaction Model (2)
Primitive Description
BEGIN_TRANSACTION Make the start of a transaction
END_TRANSACTION Terminate the transaction and try to commit
ABORT_TRANSACTION Kill the transaction and restore the old values
READ Read data from a file, a table, or otherwise
WRITE Write data to a file, a table, or otherwise

• Examples of primitives for transactions

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ACID - Four Characteristics

• Atomic to the outside world, the transaction
  happens indivisibly
• Consistent the transaction does not violate
  system invariants
• Isolated concurrent transactions do not
  interfere with each other
• Durable once a transaction commits, the changes
  are permanent

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Limitations of Flat Transactions

• Main limitation do not allow partial results to
  be committed or aborted
• updating all of the hyperlinks to a webpage W,
  which moved to a new location

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 gt ABORT_TRANSACTION (b)
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Classification of Transactions

1. A nested transaction
2. A distributed transaction

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Private Workspace

• Make a copy of the original workspace and perform
  all operation in the copied private space
  before committing
• read only ? no need for private copy

a) The file index and disk blocks for a
three-block file b) The situation after a
transaction has modified block 0 and appended
block 3 b) After committing
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Write-Ahead Log
x 0 y 0 BEGIN_TRANSACTION x x 1 y y 2 x y y END_TRANSACTION (a) Log x 0 / 1 (b) Log x 0 / 1 y 0/2 (c) Log x 0 / 1 y 0/2 x 1/4 (d)

• a) A transaction
• b) d) The log before each statement is executed

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Concurrency Control (1)

• General organization of managers for handling
  transactions

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Concurrency Control (2)

• General organization of managers for handling
  distributed transactions

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Synchronization

• Two operations are serializable if the order of
  operations does not change the outcome i.e., the
  operations do not conflict
• properly schedule conflicting operations (two
  read operations never conflict)
• Mechanism for synchronization
• Mutual Exclusion mechanisms on shared data (i.e
  locking)
• Two-Phase Locking
• Strict Two-Phase Locking
• Explicitly ordering operations using timestamps
• Pessimistic Timestamp Ordering

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Two-phase locking

• A transaction T is granted a lock if there is no
  conflict
• The scheduler will never release a lock for data
  item x, until the data manager acknowledges it
  has performed the operation for which the lock
  was set
• Once the scheduler has released a lock on behalf
  of a transaction T, it will never grant another
  lock on behalf of T

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Strict two-phase locking

• In centralized 2PL a single site is responsible
  for granting and releasing locks
• In primary 2PL each data item is assigned a
  primary copy
• In distributed 2PL the schedulers on each
  machine not only take care that locks are granted
  and released, but also that the operation is
  forwarded to the (local) data manager

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Pessimistic Timestamp Ordering

• Concurrency control using Timestamps

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Thank you !

• Questions ?