What is Distributed Computing?

Distributed computing refers to a system where processing and data storage is distributed across multiple devices or systems, rather than being handled by a single central device. In a distributed system, each device or system has its own processing capabilities and may also store and manage its own data. These devices or systems work together to perform tasks and share resources, with no single device serving as the central hub.

One example of a distributed computing system is a cloud computing system, where resources such as computing power, storage, and networking are delivered over the Internet and accessed on demand. In this type of system, users can access and use shared resources through a web browser or other client software.

Components

There are several key components of a Distributed Computing System

• Devices or Systems: The devices or systems in a distributed system have their own processing capabilities and may also store and manage their own data.
• Network: The network connects the devices or systems in the distributed system, allowing them to communicate and exchange data.
• Resource Management: Distributed systems often have some type of resource management system in place to allocate and manage shared resources such as computing power, storage, and networking.

The architecture of a Distributed Computing System is typically a Peer-to-Peer Architecture, where devices or systems can act as both clients and servers and communicate directly with each other.

Characteristics

There are several characteristics that define a Distributed Computing System

• Multiple Devices or Systems: Processing and data storage is distributed across multiple devices or systems.
• Peer-to-Peer Architecture: Devices or systems in a distributed system can act as both clients and servers, as they can both request and provide services to other devices or systems in the network.
• Shared Resources: Resources such as computing power, storage, and networking are shared among the devices or systems in the network.
• Horizontal Scaling: Scaling a distributed computing system typically involves adding more devices or systems to the network to increase processing and storage capacity. This can be done through hardware upgrades or by adding additional devices or systems to the network..

Advantages and Disadvantages

Some Advantages of the Distributed Computing System are:

• Scalability: Distributed systems are generally more scalable than centralized systems, as they can easily add new devices or systems to the network to increase processing and storage capacity.
• Reliability: Distributed systems are often more reliable than centralized systems, as they can continue to operate even if one device or system fails.
• Flexibility: Distributed systems are generally more flexible than centralized systems, as they can be configured and reconfigured more easily to meet changing computing needs.

There are a few limitations to Distributed Computing System

• Complexity: Distributed systems can be more complex than centralized systems, as they involve multiple devices or systems that need to be coordinated and managed.
• Security: It can be more challenging to secure a distributed system, as security measures must be implemented on each device or system to ensure the security of the entire system.
• Performance: Distributed systems may not offer the same level of performance as centralized systems, as processing and data storage is distributed across multiple devices or systems.

Applications

Distributed Computing Systems have a number of applications, including:

• Cloud Computing: Cloud Computing systems are a type of distributed computing system that are used to deliver resources such as computing power, storage, and networking over the Internet.
• Peer-to-Peer Networks: Peer-to-Peer Networks are a type of distributed computing system that is used to share resources such as files and computing power among users.
• Distributed Architectures: Many modern computing systems, such as microservices architectures, use distributed architectures to distribute processing and data storage across multiple devices or systems.