Distributed Systems Tutorial

A distributed system is a system of multiple nodes that are physically separated but linked together using the network. Each of these nodes includes a small amount of the distributed operating system software. Every node in this system communicates and shares resources with each other and handles processes in a team. Distributed systems are a growing trend as more and more applications migrate to the cloud. They allow improved performance, scalability, and fault tolerance compared to a traditional centralized system. This Distributed System tutorial will cover all the basic to advanced topics of distributed systems like communication, remote procedure calls, Distributed File Systems, Distributed shared memory, etc. to provide you with a thorough overview of distributed systems. 

In this Distributed System tutorial, we will go through the fundamentals, the difficulties in developing and putting distributed systems into practice, as well as the methods and tools employed to overcome these difficulties. You will discover more about distributed systems and their functioning at the tutorial’s conclusion.

Distributed System Tutorial

What are Distributed Systems?

A distributed system includes multiple physically different nodes linked together using the network. All the nodes in this system communicate with each other and control processes in a team. Nodes include a small portion of the distributed operating system software. It connects multiple computers through a single channel. It uses many central processors to serve multiple real-time applications and users.

Types of Distributed Systems

There are two types of arrangement of distributed systems:

• Client/server systems: In client-server systems, the client requests a resource or file and the server fetches that resource. Users and servers usually communicate through a computer network, so they are a part of distributed systems. A client is in contact with just one server.
• Peer-to-peer systems: The peer-to-peer techniques contain nodes that are equal participants in data sharing. The nodes communicate with each other as needed to share resources. This is done with the help of a network. All the tasks are equally separated between all the nodes.
• Middleware: Middleware can be thought of as an application that sits between two separate applications and provides service to both. It works as a base for different interoperability applications running on different operating systems. Data can be transferred to other between others by using this service.
• Three-tier: Three-tier system uses a separate layer and server for each function of a program. In this data of the client is stored in the middle tier rather than sorted into the client system or on their server through which development can be done easily. It includes an Application Layer, Data Layer, and Presentation Layer. This is mostly used in web or online applications.
• N-tier: N-tier is also called a multitier distributed system. The N-tier system can contain any number of functions in the network. N-tier systems contain similar structures to three-tier architecture. When interoperability sends the request to another application to perform a task or to provide a service. N-tier is commonly used in web applications and data systems.

Distributed System – Table of Content
Introduction to Distributed System
Communication in Distributed Systems
Remote Procedure Calls in Distributed System
Synchronization in Distributed System
Source Management and Process Management
Distributed File System and Distributed shared memory
Distributed Scheduling and Deadlock
Security in Distributed System
Distributed Multimedia and Database System
Distributed Algorithm
Distributed Transactions

Introduction to Distributed System

• What Is a Distributed System
• Features of distributed system
• Goals of Distributed system
• Evolution of Distributed Computing Systems 
• Types of Transparency in a Distributed System
• What is Scalable System in Distributed System?
• Distributed Computing System Models 
• Role of Middleware in a distributed system
• Difference between Hardware and Middleware
• What is Groupware in Distributed System?
• What is a Distributed Operating System? 
• Parallel computing vs Distributed computing
• Loosely coupled and tightly coupled system
• Design Issues of Distributed System
• Introduction to Distributed Computing Environment (DCE)
• Limitations of Distributed system
• Various Failures in a distributed system
• Types of Operating Systems
• Types of Distributed Systems
• Comparison – Centralized, Decentralized, and Distributed Systems
• Three-tier client-server architecture in a distributed system

Communication in Distributed Systems

• Introduction of Message Passing
• Features of a Good Message-Passing System 
• Issues in IPC by Message Passing 
• Synchronization in Distributed System
• Message Buffering
• Multidatagram messages in a distributed system
• Group Communication

Remote Procedure Calls in Distributed System

• What is RPC Mechanism in Distributed Systems?
• Transparency of RPC
• RPC Implementation Mechanism in Distributed System
• Stub Generation in Distributed System 
• Marshalling in Distributed System
• Server Management in a Distributed System
• Parameter-Passing Semantics
• Call Semantics issues in RPC 
• Communication Protocols for RPCs
• Client-Server Model
• Lightweight RPC in a distributed system
• RMI vs DCOM
• RPC vs RMI

Synchronization in Distributed System

• Synchronization
• Clock Synchronization 
• Logical clock
• Lamport’s algorithm
• Vector clocks
• Event Ordering 
• Distributed Mutual Exclusion and its classification
• Performance metrics for mutual exclusion algorithm
• Cristian’s algorithm
• Berkeley algorithm
• Difference between Token based and Non-Token based Algorithms in Distributed Systems
• Ricart algorithm
• Token-based algorithm (Suzuki Kasumi’s broadcast algorithm)

Source Management and Process Management

• Introduction of Source Management
• Features of Global Scheduling Algorithm in Distributed System
• What is Task Assignment Approach in Distributed System?
• Load-Balancing Approach 
• Load-Sharing Approach
• Difference Between Load Balancing and Load Sharing in Distributed Systems
• Scheduling and Load Balancing in Distributed System
• Introduction of process management in the distribution system
• Process Migration

Distributed File System and Distributed shared memory

• DFS 
• Characteristics of File system
• Sun network file system architecture
• Andrew file system
• File Service Architecture in Distributed System
• File Models in Distributed System
• File-Accessing Models 
• File-Sharing Semantics 
• File-Caching Schemes 
• What is Replication in Distributed System 
• Fault Tolerance 
• Atomic commit protocol
• Design Principles of DFS
• What is Distributed shared memory and its advantages
• The architecture of Distributed shared memory
• Difference between Uniform Memory Access (UMA) and Non-uniform Memory Access (NUMA)
• Design and implementation issue of distributed shared memory.
• False sharing in a distributed system 
• Algorithm for implementing DSM
• Consistency models in distributed systems
• Thrashing in Distributed shared memory

Distributed Scheduling and Deadlock

• What are scheduling and load balancing in a distributed system
• Load balancing algorithm
• Issues related to Load balancing in DS
• Components of load distribution
• Phantom deadlock
• Deadlock in a Distributed system
• Deadlock Detection in Distributed Systems
• A necessary condition for deadlock in a distributed system
• Deadlock handling strategies in a distributed system
• Banker’s algorithm in a distributed system
• Deadlock prevention policies: ordered request and collective request
• A WFG-based distributed algorithm for deadlock detection
• Chandy-Misra-Haas’s distributed deadlock detection algorithm
• Hierarchical deadlock detection

Security in Distributed System 

• What is security?
• Types of Cyberattacks
• Cryptography
• Authentication 
• Implementation of Access Matrix in Distributed OS
• Digital Signatures and Certificates
• Design Principles of Security in a distributed system

Distributed Multimedia and Database System

• What is Distributed DBMS? 
• Advantages and disadvantages of DDBMS
• Functions of DDBMS
• Types of DBMS
• Comparison of Homogeneous and Heterogeneous databases
• What are distributed multimedia system and its characteristics 
• Multimedia database and application area of multimedia

Distributed Algorithm

• Destination based routing
• Deadlock-free packet switching
• Wave and traversal algorithm
• Election algorithm (Bully algorithm, Ring algorithm)
• Comparison between Ring and Bully algorithm
• CORBA (Object model, CORBA services)
• Difference between CORBA and DCOM
• COM vs DCOM
• Lifecycle of COM
• Distributed Component Object Model (DCOM)
  

Distributed Transactions

• What is a Distributed Transaction?
• Nested transactions and Flat transactions
• Concurrency Control in Distributed Transactions
• Transaction Recovery 
• Introduction to Replication
• The mechanism for building a Distributed file system
• Two-phase commit protocol in the distributed system

Advantages of Distributed Systems

Some advantages of Distributed Systems are as follows :

• Every node in the distributed system is connected to each other because they can share data with others easily.
• The addition of more nodes in the distributed system is easy.
• If one node gets failed, it does not lead to the failure of the entire distributed system. Other nodes run fine.
• Resources like printers can be communicated with multiple nodes.

Disadvantages of Distributed Systems

Some disadvantages of Distributed Systems are as follows :

• In distributed systems, it is challenging to provide adequate security because both the nodes and the connections must be protected.
• In comparison to a single-user system, the database related to distributed systems is more complicated and difficult to manage.
• While traveling from one node to another node, some data may be lost in the network.

Conclusion

To summarize, distributed systems are a powerful and increasingly popular technique to develop large-scale applications that demand great scalability, fault tolerance, and performance. A distributed system’s design and implementation, however, can be a difficult process that calls for careful consideration of a number of elements, including network communication resource sharing and fault tolerance techniques.

This tutorial has covered the fundamentals of distributed computing, distributed algorithms, distributed transactions, and the difficulties of creating and putting into practice distributed systems in this tutorial.

It has given you a strong basis on which to design your own distributed system and continue exploring the world of distributed systems. 

FAQs on a Distributed system 

Q.1 What is a real-time example of a distributed system?  

Answer:

Here are real-life examples o distributed systems:

Ride-sharing applications: Apps like Uber and Rapido rely on distributed systems to match with riders or drivers to track location and even for payments process.
Stock Trading Platforms: Stock Trading platforms, such as NYSE, use distribution systems to process a large amount of trading data.
Social Media platform: Facebook and Twitter use the system to handle user requests, store data, and provide real-time updates.
Online marketplaces like Amazon and Online gaming such as Fortnite uses distributed systems to manage their inventory and to manage game servers.

Q.2 Why do we need a distributed system?

Answer:

Distributed Systems are needed for several reasons as it allows better performance, improved fault tolerance, and greater flexibility compared to centralized systems. Distributed Systems are widely used in modern computing, big data processing, and content delivery networks.

Q.3 What are the main problems of distributed systems?

Answer:

Some of the main problems of distributed systems are:

• Maintaining consistency and data synchronization.
• Fault tolerance and reliability can be complex.
• Security breaches due to increased attack surface. 
• Scalability and Complexity may affect due to large-scale systems.