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Best Introduction to Distributed System Design:

Want to know introduction to distributed system design? There are many fields of m.tech thesis which can be chosen by m.tech students for their thesis work. Selection of thesis field completely depends upon the choice of the student, if a student is very good with coding and development skills then they can choose the fields which include good amount of hard coding and development work. If a student does not have great coding skills then they can always choose a topic which includes less coding and more theoretical and diagrams parts.

One of the best example if a student decides to do their m.tech thesis in cloud computing then they would have to do a lot of hard codes while on the other hand m.tech thesis in DIP requires least coding, m.tech thesis in data mining also requires a student to have good amount of development skills while again if we talk about m.tech thesis in DIP or introduction of distributed system design then thesis are the two topics which include more of theoretical part and diagrams so it becomes easy for a student to represent their m.tech thesis on thesis topics and clear their thesis work with flying colors.

Choosing right field for your thesis work is very important and at the same time choosing right guide for your thesis is equally important. If you choose a guide who does not have good knowledge of M.tech thesis in DIP or Introduction to Distributed System Design then it would be a myth to expect that your thesis would be cleared at all. It is very important to outsource your thesis to right person or company.

There are many m.tech thesis institutes which promise to provide great guidance for m.tech thesis in DIP but students must not trust only on promises and must properly research before getting registered with any m.tech thesis institute for thesis help for Introduction to Distributed System Design.

What is a distributed system?

A distributed system is a network of independent computers connected through a distribution middleware to achieve a common goal. A distributed system provides the ability to share different resources and gives the impression of a single coherent network.

Features of a distributed system

Here are the main features of the distributed system:

  • A distributed system provides resource sharing and software sharing simultaneously. Also, the components in the network are consistent.

  • A number of independent components can be connected to the network.

  • The distributed system can spread over large areas from cities to countries. Moreover, there is no need of global clock.

  • The distributed systems provide better fault tolerance as compared to other networks.

  • Performance is also better than other networks.


Goals of Distributed Systems


What goals?

Distributed systems are designed for the fulfillment of specific goals and objectives. Following are the main goals of distributed systems:

  • The components in the distributed system work as a single system without revealing background details like location, region, access, and fault thereby providing transparency.

  • Distributed Systems make it easier for the network to be configured and modified easily.

  • Distributed Systems are more secure, consistent, and reliable thus reducing the risk of errors.

  • Distributed Systems are designed to provide better performance.

  • Distributed Systems can be scaled up and scaled down according to the requirements.

Architecture/Design of Distributed Systems

Distributed Systems follow two categories of architecture:

  • Client-Server Architecture
  • Distributed Object Architecture

Client-Server Architecture

In this type of architecture, there are set of services provided by servers and the users who use these services are known as clients.

There is no need for servers to know about clients but the clients have the knowledge of servers. There are two logical processes – Server Process, Client Process.

Client Process: This process issues a request to the second process which is the server process.

Server Process: This process receives the request from the client process, processes the request and replies to the client.

Client-Server architecture can be further classified into two model based on their functionality:

  • Thin-Client Model – In this model, all the application processing and data management are done by the server itself.
  • Fat-Client Model – In this model, the server takes care of data management while the client uses a software to manage the application processing and presentation.

Distributed Object Architecture

In this type of architecture, there are no separate entities like client and server. In this, each entity act as an object that provides services to other objects and receives services from other objects.

The objects communicate with each other using a middleware system known as object request broker.

Distributed Object Architecture is much more complex than the client/server architecture. It has the following advantages:

  • It is an open system architecture in which resources can be added and removed easily.
  • The distributed object architecture system is flexible and scalable.
  • The system can be reconfigured dynamically.

Types of Distributed Systems

Following are the three main categories of distributed systems:

  • Grid Computing
  • Cluster Computing
  • Cloud Computing

Challenges/Disadvantages of Distributed Systems

Although distributed systems are designed to provide high-performance services, there are some challenges in distributed systems:

  • The biggest challenge of distributed systems is the security mainly while using public networks.
  • Fault tolerance is difficult when unreliable components are used.
  • Resource sharing is tough if proper policies and protocols are not followed.
  • As compared to centralized systems, distributed systems are more complex to manage.

Thesis and Research Topics in Distributed Systems

Following is the list of hot topics in distributed computing for thesis, research, and projects:

  • Grid Computing
  • Cluster Computing
  • Cloud Computing
  • Parallel Distributed Computing
  • Distributed Operating System

Grid Computing

In grid computing, resources from multiple computers are combined together for accomplishing a common objective. The components in the network work together as a supercomputer for better performance. Grid Computing finds its application in areas like scientific, mathematical, and educational. It is used in structural analysis, ATM banking, and scientific research.

There are two categories of grid operations:

  • Data Grid: It is a system to handle large datasets which are used to manage data and user sharing. It creates a virtual environment for organized and specialized research.
  • CPU Scavenging Grid: It is a cycle-scavenging system that transfers project from one computer to another as per requirement.

Global Grid Forum has standardized Grid Computing. A protocol is designed which include the main points:

  • Security of grid infrastructure
  • Allocation and management protocol for grid resources
  • Access to secondary storage and GridFTP on a global scale
  • Monitoring and management of the service

Cluster Computing

A Cluster Computing is a network of multiple computers forming a single logical unit and connected through a LAN. The single unit acts as a powerful machine and has the following main features:

  • Fast processing speed
  • More storage capacity
  • Better reliability and integrity
  • More availability of resources

Following are the main types of clusters:

  • Load balancing clusters
  • High-Performance clusters
  • High-Availability clusters

Main advantages of Cluster computing are:

  • Cluster Computing is a cost-effective technique of distributed computing.
  • A connection of multiple high-speed computers provides better processing speed.
  • Use of different LAN topologies provides better network infrastructure.
  • The system resources can be upgraded as per requirements thus providing flexibility.
  • The availability of resources is high which provides uninterrupted processing.

Cloud Computing

Cloud Computing is an Internet-based service that delivers shared resources and services over the internet. The resources and services include storage, server, virtual machine, applications, and software. The characteristics of cloud computing are:

  • Resource Pooling
  • Multitenancy
  • Elasticity
  • Pay per use
  • Flexibility
  • Security

Cloud Computing provides the following types of services:

  • IaaS(Infrastructure as a Service)
  • PaaS(Platform as a Service)
  • SaaS(Software as a Service)

Cloud Deployment Models

Public Cloud: The services in public cloud are open for public use but it faces the threat of third-party attacks. It is managed and operated by companies that provide hardware, software, and other infrastructure.

Private Cloud: Private Cloud is operated for the specific need of an organization. It can be managed by the company itself or a third-party provider.

Hybrid Cloud: Hybrid Cloud is a combination of two or more clouds which retain their individual identity when combined together.

Community Cloud: Community Cloud shares infrastructure for the specific need of a community and it may be managed by the community itself or a third-party provider.

Parallel Distributed Computing

Parallel Distributed Computing is a form of distributed computing which is tightly coupled. A system can be classified into distributed or parallel based on the following criteria:

  • If for exchanging information processors have access to the shared memory then it is referred to as parallel computing.
  • If each processor has its own share of personal memory then it is referred to as distributed computing. The processors communicate with each other through messages.

Distributed Operating System

Distributed Operating System is a type of operating system that has multiple central processors to serve real-time applications and multiple users. High-speed buses are used for communication between processors. These are also known as loosely coupled systems. Each processor has its own memory and resources. Distributed Operating System offers following advantages:

  • Resource Sharing
  • Failure of one site does not affect the operations at other sites
  • Proper load balance at different sites
  • Exchange of data is faster
  • Lesser number of delays in data processing

Distributed Operating System manages the distributed systems. It manages the resource sharing, scheduling, communication, and synchronization between different running processes. Each user in a distributed system is an autonomous entity but can communicate with other users up to a limit.

This was all about the basic introduction to the distributed system design. It is a very good topic for thesis and research.

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Introduction to Distributed System Design and M.tech Thesis in DIP

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