1. Linearizability
Linearizability is a correctness criterion for concurrent object (Herlihy & Wing ACM TOPLAS 1990). It provides the illusion that each operation on the object takes effect in zero time, and the results are “equivalent to” some legal sequential computation.

2. Linearizability W (x:=0) R (x=1) W (x:=0) R(x=1) W (x:=1)
A trace is in a read-write system is consistent, when every read returns the latest value written into the shared variable preceding that read operation. A trace is linearizable, when (1) it is consistent, and (2) the temporal ordering among the reads and writes is respected.
W (x:=0)
R (x=1)
W (x:=0)
R(x=1)
W (x:=1)
(Initially x=y=0)
Is it a linearizable trace?

3. Sequential consistency
Some interleaving of the local temporal order of events at the different replicas is a consistent trace.
W(x:=100)
W(x:=99]
R(x=100)
R(x=99)

4. Sequential consistency
Is sequential consistency satisfied here? Assume that initially x=y=0.
W(x:=10)
W(x:=8]
R(x:=10)
W(x=20)
R(x=20)
R(x=10)

5. Causal consistency
All writes that are causally related must be seen by every process in the same order.
W(x:=10)
W(x:=20)
R(x=10)
R(x=20)
R(x=10)
R(x=20)

6. Implementing consistency models
Why are there so many consistency models?
Each model has a use in some application.
The cost of implementation (as measured by message complexity) decreases as the models become “weaker”.

7. Implementing linearizability
W (x:=20)
Read x
W(x:=10)
Read x
Needs total order multicast of all reads and writes

8. Implementing linearizability
The total order broadcast forces every process to accept and handle all reads and writes in the same temporal order.
The peers update their copies in response to a write, but only send acknowledgements for reads. After this, the local copy is returned

9. Implementing sequential consistency
Use total order broadcast all writes only,
but for reads, immediately return local copies.

10. Exercise Let x, y be two shared variables Process P Process Q
{initially x=0} {initially y=0}
x :=1; y:=1;
if y=0  x:=2 fi; if x=0  y:=2 fi;
Print x Print y
If sequential consistency is preserved, then what are the possible values of the printouts? List all of them.

11. Client centric consistency model

12. Client centric consistency model
Read-after-read
If read from A is followed by read from B then the second read should return a data that is as least as old the previous read. A B
Iowa City
San Francisco

13. Client centric consistency model
Read-after-write
Each process must be able to see its own updates.
Consider updating a webpage. If the editor and the browser are not integrated, the editor will send the updated HTML page to the server, but the browser may return an old copy of the page when you view it
To implement this consistency model, the editor must invalidate the cached copy, forcing the browser to fetch the recently uploaded version from the server.
edit
browse
Server

14. Client centric consistency model
Write-after-read
Each write operation following a read should take effect on the previously read copy, or a more recent version of it.
x:=0
x:=20
Alice then went to
San Francisco
x:= x+5
x=5 or 25?
Write should
take effect on
x=20
San Francisco
Iowa city

15. Quorum-based protocols
A quorum system engages only a designated minimum number of the replicas for every read or write operation – this number is called the read or write quorum. When the quorum is not met, the operation (read or write) is not performed.

16. Quorum-based protocols
N = no of replicas.
Ver 3
Ver 2
Write quorum
Thomas rule
To write, update > N/2 of them, and tag it with new version number.
To read, access > N/2 replicas with version numbers. Otherwise abandon the read
Read quorum

17. Rationale N = no of replicas. Ver 3 Ver 2
If different replicas store different version numbers for an item,
the state associated with a larger version number is more recent
than the state associated with a smaller version number.
We require that R+W > N, i.e., read quorums always intersect with
write quorums. This will ensure that read results always reflect the
result of the most recent write (because the read quorum will include
at least one replica that was involved in the most recent write).

18. How it works N = no of replicas.
1. Send a write request containing the state and new version number to all the replicas and waits to receive acknowledgements from a write quorum. At that point the write operation is complete.
2. Send a read request for the version number to all the replicas, and wait for replies from a read quorum.

19. Quorum-based protocols
After a partition, only the larger segment runs the consensus protocol. The smaller segment contains stale data, until the network is repaired.
Ver.1
Ver.0

20. Quorum-based protocols
No partition satisfies the read or write quorum

21. Quorum-based protocols
Asymmetric quorum:
W + R > N
W > N/2
No two writes overlap
No read overlaps with a write.
R = read quorum W = write quorum