Synchronization

1
Synchronization

• Tanenbaum Chapter 5

2
Synchronization

• Multiple processes sometimes need to agree on
  order of a sequence of events.
• This requires some synchronization, which is more
  elaborate in distributed systems.
• Synchronization may be based on time (absolute or
  relative), leader election
• The aim is to make it global

3
Clock Synchronization
Time

• Execution of Make utility in a distributed
  system The edited local version is created
  later than the object file according to the local
  clocks, although this was because of the
  discrepancy of local clocks.
• When each machine has its own clock, an event
  that occurred after another event may
  nevertheless be assigned an earlier time.

4
Physical Clocks (1)

• Computation of the mean solar day.
• The period of earths rotation is not constant
• Starting 1958 International Atomic Time (TAI) was
  accepted, counting the number transitions of
  Cesium 133 in an average solar second
  (9,192,631,770 transitions1 second), one solar
  second is 1/86400 solar day, which is between to
  sun peak times in the sky. Averaged over 50 labs.
• Solar day length seems to changed because of
  atmospheric drag and tidal friction issues

5
Physical Clocks (2)

• TAI seconds are of constant length, unlike solar
  seconds. However leap seconds are introduced
  when necessary (about 3 msec in a day), to keep
  in phase with the sun, 1 sec in every 800 msec of
  discrepancy. So far, since 1958, 30 leap seconds
  are introduced
• This is known as Universal Coordinated Time or UTC

6
Clock Synchronization Algorithms

• The relation between clock time and UTC when
  clocks tick at different rates.
• In perfect world, C(t)t, where t is the UTC,
  C(t) is value of the local clock, on all
  machines. With modern timer chips, the relative
  error is 10-5.
• Two clocks needs to be synchronized according to
  maximum drift rate for each clock.
• If difference between two clocks is to be limited
  to ?, then a resynchronization is required every
  ?/2? seconds, if the ? is the max drift rate.
  2?, when clocks drifts in opposite direction.

7
Cristian's Algorithm

• Getting the current time from a time server.
• The time should never set to smaller value, as it
  will cause consistency problems. So, a large
  discrepancy should be consumed slowly, by
  adjusting numb of msec to be added per clock
  interrupt.
• (T1-T0-I)/2 is the one way propagation time,
  counting for the servers request (interrupt)
  handling time I. Cristian suggest taking average
  of the delays in the system Note that the time
  server is passive.

8
The Berkeley Algorithm the time server is active
and poling the clients.

• The time daemon sends its time and asks all the
  other machines for their clock discrepancy values
• The answers from the machines is received and an
  average time discrepancy is computed, for each
  computer
• Then, the time daemon tells everyone else how to
  adjust their clock
• The daemonss time need to be set periodically by
  the operator or radio time servers

9
Distributed Clock synchronization

• Cristians and Berkeleys algorithms are
  centralized
• In decentralized distributed algorithms case,
  every machine should periodically broadcast its
  time and collects time from other peers.
• Every peer comes to conclusion about the average
  time, using the same algorithm distributedly,
  taking into account the communication latencies
• In the Internet, a so called Network Time
  Protocol-NTP is used, which is assumed to achieve
  1-50 msec accuracy.

10
Network Time Protocol-NTP

• RFC 1305 defines the NTP
• The recent implementations provide accuracy of
  up to 1 microseconds
• It is designed to execute on top of IP and UDP
• NTP is organized into multiple Tree structures,
  with primary servers at the root the secondary
  servers at the internal nodes
• NTP design goals accurate UTC synchronization,
  Survival despite the losses of connectivity,
  allow frequent resynchronization, protect against
  malicious interference
• NTP communicates clock offset (diff between two
  clocks), round-trip delay, dispersion (max error)
• Statistical technique is used, based on multiple
  comparisons of timing information exchanged
• It may operate in three modes multicast,
  client/server, symmetric
• The SNTP-Simple NTP is also defined in RFC 1769,
  with no fault tolerance

11
Use of Synchronized clocks

• Used in the implementation of at-most-once
  message delivery
• Every message is sent with a connection number
  and a time stamp
• For each connection the recent time stamp is
  recorded
• If any message on any connection is lower than
  the recorded one, the message is discarded.
• To remove old messages,
• The server removes all the messages with old
  time stamps older than
• GCurrentTime-MaxLifeTime-MaxClockSkew
• MaxLifeTime is the max time a message can live
  in the system
• MaxClockSkew is the distance from UTC.
• To recover from a crash, every ?T, G needs to be
  written to the hard disk, to be processed later,
  during the recovery phase.

12
Coordinator or Leader Election Algorithms

• Bully Algorithm
• A process holds an election for the coordinator,
  if it thinks coordinator is failed
• Send an election message to all the processes
  with higher id numbers,
• If no one responds process declares itself as
  coordinator
• If on of the higher-ups answer, it withdraws from
  the contest
• Ring Algorithm
• The process are logically or physically ordered
• Process detecting the missing coordinators sends
  a message down the ring, if message comes back
  to the sender, then it declares itself as the
  coordinator

13
The Bully Algorithm (1)

• The bully election algorithm
• Process 4 holds an election
• Process 5 and 6 respond, telling 4 to stop
• Now 5 and 6 each hold an election

14
The Bully Algorithm (2)

• Process 6 tells 5 to stop
• Process 6 wins and tells everyone

15
A Ring Algorithm

• Election algorithm using a ring. Both 5 and 2
  decide on failure of the coordinator, about the
  same time. Both messages make a full trip round
  the network.

16
Mutual Exclusion

• Mutual exclusion involves execution of critical
  sections, one at a time, in mutual exclusion.
• In centralized systems this is achieved using
  semaphores, monitors, and similar constructs
• How to establish mutual exclusion in distributed
  systems
• Centralized approach
• Distributed approach

17
Mutual Exclusion A Centralized Algorithm

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

18
MXA Distributed Algorithm

• Two processes want to enter the same critical
  region at the same moment. Processes 0 and 2
  contend for the CR, so they send a time stamped
  MX access to the resource message to every one
  else.
• Process 0 has the lowest timestamp, so it wins.
• When process 0 is done, it sends an OK also, so 2
  can now enter the critical region.

19
MXA Token Ring Algorithm

• An unordered group of processes on a network,
  logically numbered.
• A logical ring constructed in software, where a
  token is released by one of the nodes, initially
  0.
• Token loss must be handled properly, with token
  generation algorithm.
• Node failure must be handled too

20
Comparisonnumber of messages per process to
enter/exit a critical region

• A comparison of three mutual exclusion algorithms
  for n odes, regarding complexity and failure or
  loss situation.

21
The Transaction Model

• Transaction model is all or nothing model.
• Analogy can be made with a discussion process
  going on for a project towards signing a
  contract. Unless the contract is signed, any
  party can withdraw with no harm.
• Programming with tx requires special primitives
  supplied by the OS, language, or a middleware.
  The exact list of primitives may be different for
  different application or system environments.

22
The Transaction Model (1)

• Updating a daily master inventory tape is fault
  tolerant. If something goes wrong, every thing is
  redone from the beginning, ie. rewind the tapes
  to the beginning and restart the process- all or
  nothing.

23
The Transaction Model (2)

• Typical examples of primitives for transactions.
  Either all nothing between the begin and end is
  executed.

24
The Transaction Model (3)reservation flight seat
from NY to Malindi in Kenya, capitol city Nairobi.

• Transaction to reserve three flights commits, as
  three different operations
• Transaction aborts when third flight is
  unavailable, during the same booking, as if
  nothing has happened

25
The Transaction Model (4)Transaction properties

• Atomicity-indivisibility of the tx
• Consistency-no violation of the invariants
• Isolated-no interference between concurrent txs
• Durable- changes are made permanent once
  committed
• ACID property of txs

26
Classification of Txs

• Flat Txs- Txs of ACID properties discussed so
  far not practical for most distributed tx
  applications
• Nested Txs- a number of logically related
  complementing sub-transactions form one nested
  tx. One problem is the level of ACID, top level
  parent aborts very every done child must be
  undone every childs universe becomarees the
  universe for the parent
• Distributed Txs- flat indivisible tx that
  operates on data that are distributed across
  multiple computers.

27
Nested and Distributed Transactions

• A nested transaction
• A distributed transaction

28
Implementation

• How to implement nothing or all principle in
  case of Dist Txs?
• Private workspace implemented so that individual
  updates can be undone without effecting the
  original data, defending on commit/abort
• Writeahead log log of changes is created
  throughout execution, so that commit/abort can be
  taken care of

29
Private Workspace

• The file index and disk blocks for a three-block
  file
• The situation after a transaction has modified
  block 0 and appended block 3
• After committing

30
Writeahead Log

• a) N example transaction that changes x and y
• b) d) The log before each statement is
  executed. First value is before the change,
  second value is after the change

31
Concurrency Control (1)

• General organization of managers for handling
  transactions. Top level ensures atomicity, middle
  level ensures consistency, bottom level ensures
  execution

32
Concurrency Control (2)

• General organization of managers for handling
  distributed transactions.

33
SerializabilityFinal result of concurrent tx
exec should be same for different runs, as if the
txs are sequentially executed Concurrency
control algs should synchronize tex executions
(d)

• a) c) Three transactions T1, T2, and T3
• d) Possible schedules

34
Concurrency Control Methods

• Two-phase locking
• Pessimistic time-stamp ordering
• Optimistic time-stamp ordering

35
Two-phase locking-2PL-1

• Rcquire all the locks during the growing phase,
  release them during the shrinking phase.
• On conflict operation is delayed
• A lock is never released before the operation on
  the data for which the lock is set is complete
• Once a lock is released on behalf of a
  transaction no other lock can b granted to the
  same transaction
• In strict 2PL, all the acquired resource are
  released at the same timeThis avoids cascaded
  aborts deadlocks
• 2PL can easily cause deadlocks to happen
• Centralized and versions of distributed 2PL are
  possible

36
Two-Phase Locking (2)

• Two-phase locking.

37
Two-Phase Locking (3)

• Strict two-phase locking.

38
Pessimistic time-stamp ordering-1

• Every operation of a Tx is time stamped as ts by
  an appropriate algorithm (Lamports algorithm)
• Every data item in the system is time-stamped for
  the last read (tsR) and last write (tsW)
  transaction operations
• If two operations on a data item x conflict, the
  data manager grant the operation to the Tx with
  earlier ts

39
Pessimistic time-stamp ordering-2

• Read operation of a Tx with time-stamp ts
• If ts lttsW abort the Tx
• If tsgttsW allow execution and set tsR to
  max(ts,tsR)
• Write operation of a Tx with time-stamp ts
• If ts lttsR abort the Tx
• If tsgttsR allow execution and set tsW to
  max(ts,tsW)

40
Pessimistic Timestamp Ordering-3

• Concurrency control using timestamps.

41
Optimistic time-stamp ordering

• Go ahead do whatever you want, if there is
  conflict during the commit handle it then If
  conflicts are rare, most of the time commits take
  place without any problem
• This requires recording of all read and write ts
  on the data items, to check if any of the items
  have been changed during decision a commit
• Abort, if a changed is detected, commit otherwise
• This scheme has not been much research for
  distributed systems

42
Snapshot Protocols

• Snapshot Protocol 2
• Process p0 sends take snapshot at ? to all
  process and than sets its clock to ?
• when its LC reaches ?, pi
• records its ?i and immediately
• sends an empty message along each outgoing
  channel.
• Start recording messages received over each of
  its incoming channels
• Pi stops recording messages first time a message
  with TSgt ? is received from pj pi declares
  messages received from pj as ?ji
• Instead of using a message take snapshot at ? a
  process can record its state first time it
  receive a special empty message serving as a tag
  message.
• This is protocol 3

43
Supplementary for Mullenders book

• Snapshot Protocol 2
• Already covered!!!!

44
Snapshot Protocols

• Snapshot Protocol 2
• Process p0 sends take snapshot at ? to all
  process and than sets its clock to ?
• when its LC reaches ?, pi
• records its ?i and immediately
• sends an empty message along each outgoing
  channel.
• Start recording messages received over each of
  its incoming channels
• Pi stops recording messages first time a message
  with TSgt ? is received from pj pi declares
  messages received from pj as ?ji
• Instead of using a message take snapshot at ? a
  process can record its state first time it
  receive a special empty message serving as a tag
  message.
• This is protocol 3

45
Properties of Snapshots

• Any state constructed by distributed snapshot
  algorithm is guaranteed to be consistent.
  However, the actual run may not pass through the
  constructed states,
• yet constructed states are, but the relation
  related to the constructed state holds in in
  general
• Order of two events in a run can be swapped to
  put in pre-recording post-recording order.

46
Properties of Global Predicates

• Once a predicate became true it remains to be
  true is Stability criteria for the predicate
  (figure 4.16).