1. Synchronization

2. Clock Synchronization In a centralized system time is unambiguous
Clock Synchronization In a centralized system time is unambiguous. In a distributed system agreement on time is not obvious.
When each machine has its own clock, an event that occurred after another event may be assigned an earlier time.

3. Physical clocks Computer Clock ≡ Timer
Oscillating crystal (under tension)
2 register: counter and holding register
Interrupt ( clock tick) when counter gets to zero
N clocks n rates (clock skew)
UTC (Universal Coordinated Time) is the current universal time
standard
Radio pulse to synchronize (±10 msec)
Satellite (± 0.5 msec)

4. Clock Synchronization Algorithms
If – r < dC/dt < 1 + r r maximum drift rate
If 2 clock drift from UTC in the opposite directions, after Δt,
ε = 2r Dt
Resynchronization interval d/2r d maximum time difference
The relation between clock time and UTC when clocks tick at different rates.

5. Cristian's Algorithm synchronization with a time server Periodically (T < d/2r s) synchronization request to time server
Time must never run backward gradual changes
Non zero message propagation time (estimate value = (T1-T0-I) /2 )

6. The Berkeley Algorithm synchronization without time server
The time daemon asks all the other machines for their clock value discrepancies
The machines answer
The time daemon tells everyone how to adjust their clock to the average
no Universal Coordinated Time available

7. Logical clocks Centralized algorithms have disadvantages.
Decentralized algorithms can use averaging methods.
NTP (Network Time Protocol) provides an accuracy of 1-50 msec using advanced algorithms.
For many purposes it is sufficient that all machines agree on the same time.
Logical clocks
Often processes need to agree on the order in which events occur.

8. Lamport Timestamps If a b C(a) < C(b)
happens before
If a b C(a) < C(b)
If a snd., b rcv C(a) < C(b)
C(a)  C(b)
If C(b) < C(a) C(b) = C(a)+1
We obtain a total ordering of all events in the system
but Lamport timestamps don’t capture causality
Vector timestamps
each process Pi has a vector Vi so that:
Vi[i] is the number of events occurred so far at Pi
If Vi[j]=k Pi knows k events occurred at Pj

9. Global State It is the local state of each process, together with the messages currently in transit in a distributed system A distributed snapshot reflects a consistent global state

10. Any process P may initiate the algorithm recording its local state.
Global State
Knowledge of the state in which a distributed system currently is, is useful
Any process P may initiate the algorithm recording its local state. P
Organization of a process and channels for a distributed snapshot
A process P sends a marker along each of its outgoing channels

11. Global State
Process Q receives a marker for the first time, records its local state and send a marker along each outgoing channel
Q records all incoming message
Q receives a marker for its incoming channel and finishes recording the state of the incoming channel
A process has finished its part of the algorithm when it has received a marker
along each of its incoming channels, and processed each one. Then its state is collected
Many snapshots may be in progress at the same time.

12. Election Algorithms The Bully Algorithm (1/2)
Selecting a coordinator
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

13. The Bully Algorithm (2/2)
Process 6 tells 5 to stop
Process 6 wins and tells everyone

14. Election algorithm using a ring (without token).
A Ring Algorithm
Each process knows who its successor is.
Election algorithm using a ring (without token).

15. Mutual Exclusion: critical regions in distributed systems A Centralized Algorithm (to simulate a single processor system, needs a coordinator)
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, which then replies to 2

16. A Distributed Algorithm requires a total ordering of all events in the system A message contains the critical region name, the process number and the current time
Two processes (0,2) want to enter the same critical region at the same moment.
Process 0 has the lowest timestamp, so it wins and enters the critical region.
When process 0 is done, it sends an OK also, so 2 can now enter the critical region.
This algorithm is worse than the centralized one (n points of failure, scaling, multiple messages…)

17. A Token Ring Algorithm when the process acquires the token, it accesses the critical region (if needed)
start
An unordered group of processes on a network.
A logical, ordered, ring constructed in software. Each process knows who
is the next in line

18. Messages per entry/exit Delay before entry * (in message times)
Mutual Exclusion
Algorithm
Messages per entry/exit
Delay before entry * (in message times)
Problems
Centralized 3 2
Coordinator crash
Distributed
2 ( n – 1 )
Crash of any process
Token ring
1 to 
0 to n – 1
Lost token, process crash
A comparison of three mutual exclusion algorithms.
* With dependence on the mechanism

19. Examples of primitives for transactions.
The Transaction Model A transaction permits that a whole set of related instructions would be successfully completed or none would be completed. Special primitives are requested ( supplied by system or language)
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.

20. The Transaction Model Transactions are ACID:
Atomic : to outside, they happen indivisibly
Consistent : they don’t violate system invariants
Isolated : concurrent transactions don’t interfere
Durable : the changes are permanent
These flat transactions have some limitations...
No partial result is permitted
In a large system they can take a lot of time

21. Nested and Distributed Transactions
A nested transaction: it follows a logical (hierarchical) division of the work
A distributed transaction: it is logically flat and operates on distributed data

22. How to implement transactions? Private Workspace
Copying everything in a private workspace is prohibitive…
Example: dealing with a file system:
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

23. 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)
[y = 0/2]
(c)
[x = 1/4]
(d)
rollback
Files are actually modified in place, but a record is written to log all the changes
a) A transaction
b) – d) The log before each statement is executed
In distributed systems each machine keeps its own log of changes to its local file system

24. General (layered) organization of managers for handling transactions.
Concurrency Control allows several transaction to be executed simultaneously, leaving data in a consistent way. Transactions access data in a specific order
General (layered) organization of managers for handling transactions.

25. Concurrency Control
General organization of managers for handling distributed transactions.

26. Serializability a) – c) Three transactions T1, T2, and T3
BEGIN_TRANSACTION x = 0; x = x + 1; END_TRANSACTION
(a)
BEGIN_TRANSACTION x = 0; x = x + 2; END_TRANSACTION
(b)
BEGIN_TRANSACTION x = 0; x = x + 3; END_TRANSACTION
(c)
Schedule 1
x = 0; x = x + 1; x = 0; x = x + 2; x = 0; x = x + 3
Legal
Schedule 2
x = 0; x = 0; x = x + 1; x = x + 2; x = 0; x = x + 3;
Schedule 3
x = 0; x = 0; x = x + 1; x = 0; x = x + 2; x = x + 3;
Illegal
(d)
a) – c) Three transactions T1, T2, and T3
Legal serialized result : x= 1,2,3 depending upon which one runs last
d) Possible schedules
Synchronization can be achieved or with mutex or with explicit timestamp and following pessimistic or optimistic approach.