Distributed and Cloud Systems Micro Specialization | Module 3: Leader Election in Cloud, Distributed Systems and Industry Systems by Prakhar Chauhan | Learn Smarter
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Module 3: Leader Election in Cloud, Distributed Systems and Industry Systems

The module explores leader election in distributed systems, emphasizing its role in achieving coordination, consensus, and fault tolerance without a central authority. It outlines classical algorithms, including ring-based methods such as the LCR and HS algorithms, and delves into more complex systems like the Bully algorithm. The chapter ends with a discussion on practical implementations of leader election in services like Google’s Chubby and Apache ZooKeeper.

Sections

  • 1

    Leader Election In Rings (Classical Distributed Algorithms)

    This section explores the problem of leader election within distributed systems, focusing on classical algorithms like the LeLann-Chang-Roberts (LCR) and Hirschberg-Sinclair (HS) algorithms.

    Learning Practice

  • 1.1

    The Leader Election Problem

    This section explores the leader election problem in distributed systems, outlining classical algorithms and their significance.

    Learning Practice

  • 1.2

    Ring-Based Leader Election Algorithms

    This section explores ring-based leader election algorithms essential for coordinating and managing distributed systems.

    Learning Practice

  • 1.2.1

    Lelann-Chang-Roberts (Lcr) Algorithm

    This section explores the LeLann-Chang-Roberts (LCR) Algorithm, a leader election mechanism for distributed systems organized in a ring topology.

    Learning Practice

  • 1.2.2

    The Hirschberg And Sinclair (Hs) Algorithm

    The HS algorithm is an efficient ring-based leader election algorithm that enhances message complexity and employs a phased approach to elect a leader in distributed systems.

    Learning Practice

  • 2

    Leader Election (Ring Le & Bully Le Algorithm)

    This section discusses leader election algorithms like Ring-based and Bully algorithms in distributed systems, focusing on their mechanics and applications in ensuring coordination.

    Learning Practice

  • 2.1

    The Leader Election Problem (Revisited)

    This section revisits the topic of leader election in distributed systems, outlining classical algorithms such as the Bully and ring-based approaches, their characteristics, and implications in real-world applications like Apache ZooKeeper.

    Learning Practice

  • 2.2

    Ring-Based Leader Election (General Principle)

    Ring-based leader election algorithms are essential for designating a leader in distributed systems, leveraging message passing in a structured ring topology.

    Learning Practice

  • 2.3

    Bully-Based Leader Election Algorithm

    The Bully Algorithm is a leader election method used in distributed systems where processes can communicate directly with one another, ensuring a robust system despite process failures.

    Learning Practice

  • 3

    Leader Election In Industry Systems: Google’s Chubby And Apache Zookeeper

    This section discusses the significance of leader election in distributed systems, focusing on algorithms and real-world implementations like Google's Chubby and Apache ZooKeeper.

    Learning Practice

  • 3.1

    Google's Chubby

    This section explores leader election in distributed systems and examines Google's Chubby, a coordination service that employs leader election for resource management.

    Learning Practice

  • 3.2

    Apache Zookeeper

    Apache ZooKeeper is a distributed coordination service designed to manage distributed applications' configuration, coordination, and leader election through a simple, hierarchical data model.

    Learning Practice

  • 4

    Design Of Zookeeper: A Detailed Look

    This section explores the design principles and architecture of Apache ZooKeeper, focusing on its role as a distributed coordination service.

    Learning Practice

  • 4.1

    Challenges Addressed By Zookeeper

    ZooKeeper addresses the challenges of race conditions, deadlocks, and coordination in distributed systems.

    Learning Practice

  • 4.2

    Zookeeper Design Goals

    This section explores the design goals of ZooKeeper, a coordination service essential for distributed systems.

    Learning Practice

  • 4.3

    Zookeeper Data Model

    The ZooKeeper Data Model outlines a hierarchical structure that facilitates efficient coordination in distributed systems through Znodes, emphasizing their significance in leader election and fault tolerance.

    Learning Practice

  • 4.4

    Zookeeper Architecture

    This section provides an overview of the ZooKeeper architecture, explaining its components, functionality, and design principles that support distributed systems.

    Learning Practice

  • 4.5

    Sessions And States

    This section outlines how client sessions and states function within Apache ZooKeeper, emphasizing the mechanisms that handle connection management and ephemeral nodes.

    Learning Practice

  • 4.6

    Zookeeper Use Cases (Coordination Primitives)

    This section discusses the role of Apache ZooKeeper in coordinating distributed applications, emphasizing its leader election capabilities and other use cases.

    Learning Practice

  • 4.7

    Zookeeper Operations

    This section discusses the core operational functionalities of Apache ZooKeeper, focusing on its API, data model, and coordination primitives essential for distributed systems.

    Learning Practice

  • 4.8

    Access Control List (Acl)

    This section describes the Access Control List (ACL) mechanism implemented in ZooKeeper to manage permissions for Znodes.

    Learning Practice

  • 4.9

    Zookeeper Applications (Industry Use Cases)

    This section explores the various applications of ZooKeeper, a coordination service, in industry use cases.

    Learning Practice

References

Untitled document (21).pdf

Class Notes

Memorization

What we have learnt

  • Leader election is crucial ...
  • Algorithms must ensure uniq...
  • Practical implementations s...

Final Test

Revision Tests