Distributed Systems
Unit Outlines

Distributed Systems

AI Generated Intermediate 40 hours 10 topics

Learning Objectives

5 objectives
  • Understand fundamental concepts, characteristics, and challenges of distributed systems.
  • Analyze various communication models, architectures, and computing paradigms in distributed environments.
  • Examine design principles of distributed file systems and distributed data management strategies.
  • Evaluate fault tolerance, scalability, security, and privacy mechanisms in distributed systems.
  • Apply knowledge through case studies of real-world distributed system implementations.

Content Outline

Preview

Unit 920 - Distributed Systems

1. Introduction to Distributed Systems

  • Definition and scope of distributed systems
  • Key characteristics: concurrency, lack of a global clock, independent failures
  • Advantages: resource sharing, scalability, fault tolerance
  • Challenges: synchronization, fault handling, consistency, security

2. Communication in Distributed Systems

  • Communication models: message passing, remote procedure calls (RPC), remote method invocation (RMI)
  • Communication protocols: TCP/IP, UDP, HTTP, gRPC
  • Communication architectures: client-server, peer-to-peer
  • Serialization and marshaling techniques

3. Distributed System Architectures

  • Client-server architecture: roles, interaction patterns
  • Peer-to-peer architecture: decentralized control, scalability
  • Microservices architecture: modularity, service discovery, orchestration
  • Cloud computing architecture: service models (IaaS, PaaS, SaaS), deployment models

4. Distributed Computing Paradigms

  • Parallel computing: concepts, shared vs distributed memory
  • Cluster computing: tightly coupled nodes, high availability
  • Grid computing: resource sharing across administrative domains
  • Cloud computing: on-demand resource provisioning, elasticity
  • Applications, scalability, and fault tolerance considerations in each paradigm

5. Distributed File Systems

  • Design goals: transparency, fault tolerance, scalability
  • Hadoop Distributed File System (HDFS): architecture, data blocks, replication
  • Network File System (NFS): protocol overview, stateless vs stateful design
  • Ceph: object storage, CRUSH algorithm, scalability and fault tolerance
  • Data replication, consistency models, access protocols

6. Distributed Data Management

  • Distributed database systems: architecture, query processing, transaction management
  • NoSQL databases: types (key-value, document, column-family, graph), use cases
  • Data replication strategies: synchronous vs asynchronous replication
  • Consistency models: strong, eventual, causal consistency
  • CAP theorem and trade-offs

7. Fault Tolerance and Replication

  • Fault types: crash, omission, timing, Byzantine
  • Fault tolerance mechanisms: redundancy, checkpointing, rollback recovery
  • Replication strategies: primary-backup, multi-primary
  • Consistency models in replication
  • Recovery techniques and consensus algorithms (e.g., Paxos, Raft)

8. Scalability and Load Balancing

  • Scalability challenges: bottlenecks, resource contention
  • Load balancing algorithms: round-robin, least connections, weighted distribution
  • Horizontal scaling vs vertical scaling
  • Auto-scaling and elasticity in cloud systems
  • Performance metrics and monitoring

9. Security and Privacy in Distributed Systems

  • Security threats: eavesdropping, spoofing, denial of service, insider threats
  • Authentication mechanisms: passwords, certificates, multi-factor authentication
  • Encryption techniques: symmetric, asymmetric, TLS/SSL
  • Access control models: discretionary, mandatory, role-based access control
  • Privacy concerns and data protection regulations

10. Case Studies in Distributed Systems

  • Google's Bigtable: architecture, data model, scalability
  • Amazon DynamoDB: design principles, eventual consistency, partitioning
  • Apache Hadoop: ecosystem overview, MapReduce, HDFS
  • Microsoft Azure: cloud services architecture, scalability, security features
  • Performance characteristics and lessons learned
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Quick Information

Unit Distributed Systems
Difficulty Intermediate
Duration40 hours
Topics10
CreatedJul 20, 2026
GeneratedJul 20, 2026 01:07

Prerequisites

  • Basic knowledge of computer networks
  • Understanding of operating systems concepts
  • Familiarity with programming and algorithms

Recommended Resources

  • "Distributed Systems: Concepts and Design" by George Coulouris, Jean Dollimore, Tim Kindberg, and Gordon Blair
  • "Designing Data-Intensive Applications" by Martin Kleppmann
  • Google Research Papers on Bigtable and Spanner
  • Amazon DynamoDB Documentation
  • Apache Hadoop Official Documentation
  • Microsoft Azure Architecture Center
  • Research articles and tutorials on consensus algorithms (Paxos, Raft)

Unit Topics

10
Introduction to Distributed Systems
This topic covers the basic concepts of distributed systems, including definitions, characteristics,...
Communication in Distributed Systems
Explore the various communication models, protocols, and architectures used in distributed systems t...
Distributed System Architectures
Learn about different architectural styles such as client-server, peer-to-peer, microservices, and c...
Distributed Computing Paradigms
Delve into parallel computing, grid computing, cluster computing, and cloud computing paradigms in d...
Distributed File Systems
Study the design principles and functionalities of distributed file systems like HDFS, NFS, and Ceph...
Distributed Data Management
Explore distributed database systems, NoSQL databases, and data replication strategies in distribute...
Fault Tolerance and Replication
Understand fault tolerance mechanisms, replication strategies, consistency models, and recovery tech...
Scalability and Load Balancing
Examine scalability challenges in distributed systems, load balancing algorithms, horizontal scaling...
Security and Privacy in Distributed Systems
Discuss security threats, authentication mechanisms, encryption techniques, access control, and priv...
Case Studies in Distributed Systems
Analyze real-world case studies of distributed systems implementations in popular platforms like Goo...