Lec9 - ECE151 Lecture 9 Chapter 6 Consistency and...

Info iconThis preview shows pages 1–9. Sign up to view the full content.

View Full Document Right Arrow Icon
ECE151 – Lecture 9 1 ECE151 – Lecture 9 Chapter 6 Consistency and Replication
Background image of page 1

Info iconThis preview has intentionally blurred sections. Sign up to view the full version.

View Full DocumentRight Arrow Icon
ECE151 – Lecture 9 2 Consistency & Replication Introduction Data-centric consistency Client-centric consistency Distribution protocols Consistency protocols Examples
Background image of page 2
ECE151 – Lecture 9 3 Object Replication Organization of a distributed remote object shared by two different clients. Problem: If objects (or data) are shared, we need to do something about concurrent accesses to guarantee state consistency.
Background image of page 3

Info iconThis preview has intentionally blurred sections. Sign up to view the full version.

View Full DocumentRight Arrow Icon
ECE151 – Lecture 9 4 Object Replication a) A remote object capable of handling concurrent invocations on its own. b) A remote object for which an object adapter is required to handle concurrent invocations Problem: Is the remote object already thread- safe or not?
Background image of page 4
ECE151 – Lecture 9 5 Object Replication a) A distributed system for replication-aware distributed objects. b) A distributed system responsible for replica management Problem: Should we seek for object-specific solutions, or generally applicable ones? Question: Why would we want object-specific replication protocols?
Background image of page 5

Info iconThis preview has intentionally blurred sections. Sign up to view the full version.

View Full DocumentRight Arrow Icon
ECE151 – Lecture 9 6 Performance and Scalability Main issue: To keep replicas consistent, we generally need to ensure that all conflicting operations are done in the the same order everywhere Conflicting operations: From the world of transactions: Read–write conflict: a read operation and a write operation act concurrently Write–write conflicts: two concurrent write operations Guaranteeing global ordering on conflicting operations may be a costly operation, downgrading scalability Solution: weaken consistency requirements so that hopefully global synchronization can be avoided
Background image of page 6
ECE151 – Lecture 9 7 Data-Centric Consistency Models The general organization of a logical data store, physically distributed and replicated across multiple processes. Consistency model: a contract between a (distributed) data store and processes, in which the data store specifies precisely what the results of read and write operations are in the presence of concurrency. Essence: A data store is a distributed collection of storages accessible to clients:
Background image of page 7

Info iconThis preview has intentionally blurred sections. Sign up to view the full version.

View Full DocumentRight Arrow Icon
ECE151 – Lecture 9 8 Data-Centric Consistency Models Strong consistency models: Operations on shared data are synchronized: Strict consistency (related to time) Sequential consistency (what we are used to) Causal consistency (maintains only causal relations) FIFO consistency (maintains only individual ordering) Weak consistency models: Synchronization occurs only when shared data is locked and unlocked:
Background image of page 8
Image of page 9
This is the end of the preview. Sign up to access the rest of the document.

Page1 / 28

Lec9 - ECE151 Lecture 9 Chapter 6 Consistency and...

This preview shows document pages 1 - 9. Sign up to view the full document.

View Full Document Right Arrow Icon
Ask a homework question - tutors are online