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Replication techniques and its Types in Distributed Computing

Replication techniques and its Types in Distributed Computing

Replication techniques and its Types in Distributed Computing

Replication techniques and its Types in Distributed Computing.

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Replication Techniques and Its Types in Distributed Computing

Replication in distributed computing refers to the process of creating and maintaining multiple copies of data or services across different nodes in a network. The primary goals of replication are fault tolerance, high availability, performance improvement, and load balancing.

1. Why is Replication Needed?

Fault Tolerance – Ensures system availability even if some nodes fail.
High Availability – Users can access data even if some replicas go down.
Load Balancing – Distributes requests across replicas to avoid bottlenecks.
Performance Improvement – Reduces latency by placing replicas closer to users.
Data Consistency – Ensures all nodes have the same updated data.

2. Types of Replication Techniques

A. Data Replication (Used in Databases & Storage Systems)

  1. Synchronous Replication

    • All copies are updated immediately before the transaction is committed.
    • Ensures strong consistency but has high latency.
    • Example: Banking transactions, financial systems.
  2. Asynchronous Replication

    • Changes are first made to one replica and then propagated to others later.
    • Faster but may lead to temporary inconsistencies.
    • Example: Cloud storage (Google Drive, Dropbox).
  3. Semi-Synchronous Replication

    • A middle ground where some replicas confirm updates before committing, but not all.
    • Balances between consistency and speed.

B. Computation Replication (Used in Distributed Computing & Cloud Services)

  1. Active Replication

    • All replicas execute the same request in parallel.
    • Ensures consistency but requires more resources.
    • Used in fault-tolerant systems (e.g., flight control software).
  2. Passive Replication (Primary-Backup Model)

    • A primary node processes requests and updates secondary nodes.
    • If the primary node fails, a backup takes over.
    • Used in high-availability services like databases.

C. Hybrid Replication

3. Challenges in Replication

Consistency Issues – Ensuring all copies have the same data.
Network Latency – Syncing replicas across long distances takes time.
Conflict Resolution – Handling simultaneous updates from different nodes.
Storage Overhead – Keeping multiple copies requires extra space.

Would you like a more detailed explanation of any specific replication type?

Here’s a complete and easy-to-understand explanation of Replication Techniques and their Types in Distributed Computing, ideal for students preparing for exams like GATE, or anyone learning distributed systems.


What is Replication in Distributed Computing?

Replication refers to the process of maintaining multiple copies (replicas) of data or services across different nodes in a distributed system to ensure:


Why Replication is Important?


Types of Replication Techniques

1. Data Replication

Maintaining copies of data (files, database records) across multiple machines.

Types:


2. Synchronous vs Asynchronous Replication

Synchronous Replication

Used in financial systems, where accuracy is critical.

Asynchronous Replication

Suitable for content delivery networks (CDNs) or backups.


3. Primary-Backup (Master-Slave) Replication


4. Multi-Master Replication

Used in collaborative apps, CRDTs, or eventually consistent databases.


5. State Machine Replication (SMR)

Used in distributed databases, blockchains, and fault-tolerant systems.


6. Quorum-Based Replication

Used in Amazon DynamoDB, Cassandra, etc.


Summary Table

Replication Type Description Best Use Case
Full Replication All data on all nodes High availability, low-latency reads
Partial Replication Only part of data is replicated Saves space, custom distribution
Synchronous Updates all replicas before completion Strong consistency needed
Asynchronous Updates replicas after completion Performance-sensitive systems
Primary-Backup One master handles writes Simple fault-tolerant setup
Multi-Master All nodes accept writes High scalability
State Machine Replication Identical replicas process same input log High-reliability systems
Quorum-Based Majority agreement ensures consistency Scalable and resilient databases

Bonus: Real-World Examples

System Replication Used
Google Spanner Synchronous + SMR (Paxos)
MongoDB Primary-Backup (Replica Sets)
Cassandra Quorum-Based + Eventually Consistent
Git Full replication (DVCS)

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Replication techniques and its Types in Distributed Computing

Understanding Replication in Databases and Distributed …