Consistency and Replication CSCI 6900/4900

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

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

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.

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

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

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

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

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

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

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