Mumbai University > Information Technology > Sem 6 > Distributed System

Marks: 10Marks

Client –centric Consistency model-many Inconsistencies can be hidden in cheap way.

The client-centric consistency models arm at providing a consistent view on a database.

An important assumption is that concurrent process may be simultaneously updating provide consistency in the face of such concurrency.

client-centric consistency models are described using the following notations.

Let xi[t] denote the version of data item x at Li at time t.

version xi[t] is the result of series of write operations of Li that took place since initialization; we denote this set as WS(xi[t]).

If operations in WS(xi[t1]) have also been performed at local Lj at later time t2, we write WS(xi[t1];xj[t2]).

The Client-Centric consistency models are:

1) Monotonic Reads

2) Monotonic Writes

3) Read your Writes

4) Writes follow Reads

5) Eventual Consistency

Monotonic reads :

A data store is said to provide monotonic read consistency if the following conditions helds.

If a process reads the value of a algorithm x by what process will always return that same value or more recent value.

In other words, monotonic read consistency guarantees that if a process has seen a value of x at a more time t, it will never see an older version of x at a later time.

Monotonic writes: in a monotonic write consistent store, the following conditions holds:

A write operation by a process on a data item x is completed before any successive write operation on x by the same process.

Read your writes:

A database is said to provide read your write consistency, if the following condition holds:

The effect of a write operation by a process on data item x will always be seen by a successive read operation on x by the same process.

Write your reads:

A data store is said to provide writes follows reads consistency, if the following conditions holds:

A write operation by a process on a data item x following a previous read operation on x by the same process is generated to take place on the same or a more recent value of x that was read.

Eventual Consistency:

Data stores there are eventually consistent have properly that in absence of updates, all replicas coverage toward identical copies of each other.

Eventual consistency essentially requires only that updates are guaranteed to propagate to all replicas.