Consensus Algorithms

Consensus algorithms allow the different nodes distributed throughout them to agree on a single shared value or outcome in spite of individual node failures and disagreements among them (meaning despite the situations when one of the nodes failed or there were discrepancies among them).

  • They provide a fundamental basis for distributed applications like distributed DBMS, blockchain, blockchain networks, and BFT protocols such as Paxos, Raft, and BFT.
  • These guidelines guarantee consistency and fault tolerance in the presence of various types of pathways. 

Let’s understand consensus algorithm in distributed system using paxos algorithm:

  • Initiation: In Paxos, a node, called the proposer, initiates a proposal by sending a “prepare” message to a majority of nodes (known as acceptors) in the system.
  • Voting: Upon receiving the prepare message, each acceptor checks if it has promised to accept proposals with higher numbers. If not, it responds with a promise and may include any previously accepted proposal.
  • Proposal Phase: The proposer collects promises from a majority of acceptors. It then sends a proposal with the highest numbered proposal among the promises to the acceptors.
  • Acceptance: If the acceptors receive a proposal and have not made a promise to accept a proposal with a higher number, they accept the proposal and inform the learner.
  • Consensus: Once a proposal is accepted by a majority of acceptors, consensus is reached, and the value proposed by the consensus becomes the chosen value for the system

Distributed System Algorithms

Distributed systems are the backbone of modern computing, but what keeps them running smoothly? It’s all about the algorithms. These algorithms are like the secret sauce, making sure everything works together seamlessly. In this article, we’ll break down distributed system algorithms in simple language.

Important Topics for Distributed System Algorithms

  • Communication Algorithms
  • Synchronization Algorithms
  • Consensus Algorithms
  • Replication Algorithms
  • Distributed Query Processing Algorithms
  • Load Balancing Algorithms
  • Distributed Data Structures and Algorithms
  • Failure Detection and Failure Recovery Algorithms
  • Security Algorithms for a Distributed Environment

Similar Reads

1. Communication Algorithms

Communication algorithms are the guiding regulations for data exchanges that take place in a distributed system between nodes. They cover a broad area of communication mechanisms, message relay algorithms, and routing schemes for efficient data transmission and low latency....

2. Synchronization Algorithms

Synchronization Algorithms closely interact with each other to synchronize parallel executions within dispensed nodes. This synchronization is enabled so that indifferent processes or threads operate simultaneously to avoid race conditions, deadlocks, and inconsistencies....

3. Consensus Algorithms

Consensus algorithms allow the different nodes distributed throughout them to agree on a single shared value or outcome in spite of individual node failures and disagreements among them (meaning despite the situations when one of the nodes failed or there were discrepancies among them)....

4. Replication Algorithms

Replication algorithms enable those processes of replicating multiple instructions of data in different nodes, which boosts the level of fault tolerance, availability, and performance....

5. Distributed Query Processing Algorithms

Distributed query processing algorithms in distributed systems involve executing queries across multiple nodes to retrieve and process data distributed across the network. These algorithms aim to optimize query performance, minimize communication overhead, and ensure data consistency....

6. Load Balancing Algorithms

The load balancing algorithms split and distribute the computation task or network traffic equally among the nodes in order to avoid overloading and prevent the resources from getting used or spent....

7. Distributed Data Structures and Algorithms

Distributed Data Structures and Algorithms is the study of how to store and manipulate data on multiple computers in a way that optimizes performance and provides high availability while maintaining consistency of data in the face of concurrent updates by different users....

8. Failure Detection and Failure Recovery Algorithms

Failure detection and recovery algorithms in distributed systems are essential for maintaining system reliability and availability in the face of node failures or network partitions. These algorithms monitor the health and status of nodes in the system, detect failures promptly, and take appropriate actions to recover from failures....

9. Security Algorithms for a Distributed Environment

Security algorithms in distributed systems are designed to protect data, communication channels, and system resources from unauthorized access, tampering, and other security threats. Some security algorithms in distributed environment are:...

Conclusion

In conclusion, distributed system algorithms form the backbone of modern distributed computing, enabling efficient coordination, communication, and fault tolerance among interconnected nodes. From consensus and replication algorithms to synchronization and security mechanisms, these algorithms play a critical role in ensuring the reliability, scalability, and security of distributed systems....