1. Consistency and Replication
CSCI 6900/4900

2. Chapter Outline Why replication?
Relations to reliability and scalability
How to maintain consistency of replicated data?
Consistency models
Consistency schemes
How to distributed updates and when to distribute them
Examples
Parallel programming
WWW-based systems

3. Reasons for Replication
Two primary reasons
Improving reliability of system
Improving scalability and performance of system
Reliability
Resilience to failures
Protection against data corruption: Byzantine failures and quorum-based systems

4. Scalability and Performance
Scaling in numbers
Replication can help to scale the distributed system by numbers
If number of processes accessing data increases, it helps to replicate the data
Example: Parallel programs
Geographical scaling
Placing replica close to process using the data, improves the performance
Example: Edge cache networks, browser caches, etc.

5. Problems of Replication
Creating and maintaining replicas is not free
Multiple copies leads to consistency problems
What happens when one of the replicas gets modified?
Modifications have to be carried out at all replicas
How and when determines the cost of replication
WWW-based systems
Browser and client side caches
May lead to stale pages
TTL model, Update/Invalidate model

6. Object Replication Studying replication on objects helps understanding
Objects encapsulate data and related functions
Synchronization in distributed remote objects
Object-level implementation
Server-level implementation
Replicated distributed objects
Object-specific replication protocol
Middleware replication protocol

7. Object Replication (2)
Organization of a distributed remote object shared by two different clients.

8. Object Replication (3)
A remote object capable of handling concurrent invocations on its own.
A remote object for which an object adapter is required to handle concurrent invocations

9. Object Replication (4)
A distributed system for replication-aware distributed objects.
A distributed system responsible for replica management

10. Replication as Scalability Technique
Replication can help to solve geographical scalability problems
Placing replicas closer to clients
Maintaining replicas consistent may place sever overheads
Examples: N accesses and M updates per unit time and N<<M
Problems with multiple copies and tight consistency
Implementing global synchronization
Relaxing consistency requirements is a possible solution

11. Data-Centric Consistency Models
The general organization of a logical data store, physically distributed and replicated across multiple processes.