With the increased investment of different industries in the IT sector, the IT field is growing rapidly. As a result, strategists and analysts of the IT sector are constantly researching cost-effective and transparent IT resources to maximize performance. Concepts such as Distributed computing plays a key role which ensures fault tolerance and enables resource accessibility. Here we collected data regarding “What is distributed computing” and put it together to offer a detailed understanding of distributed computing.

What Is Distributed Computing?

Multi-computer collaboration to tackle a single problem is known as distributed computing. It transforms a computer network into a potent single computer that has ample resources to handle difficult problems. A distributed system is made up of different configurations with mainframes, personal computers, workstations, and minicomputers.

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How Does Distributed Computing Work?

The Distributed computing architecture is made up of several client PCs that are outfitted with very lightweight software agents and one or more dedicated distributed computing management servers. When the agents on the client machines detect that the machine is idle, they notify the management server that the machine is not in use and is ready for a processing job followed by an agent's request for an application bundle. When the client machine receives this application package to process from the management server, it runs the application software whenever it has free CPU cycles and delivers the results back to the management server. When the user returns and needs the resources again, the management server returns the resources that were used to execute various activities while the user was away.  

Key Benefits of Distributed Computing

Here are some of the key benefits of distributed computing.

  1. Scalability - Distributed systems can scale to meet your needs and workload. When new nodes, or more computing devices, are required, they can be added to the distributed computing network.
  2. Availability - If one of the computers fails, your distributed computing system will not fail. Because it can continue to run even if individual computers fail, the design demonstrates fault tolerance.
  3. Consistency - Computers in a distributed system share information and duplicate data, yet the system manages data consistency across all computers automatically. As a result, you gain the benefit of fault tolerance without sacrificing data consistency. 
  4. Transparency - Distributed computing technologies separate the user from the physical equipment logically. You can communicate with the system as if it were a single computer, without having to bother about individual machine setup and configuration. Different hardware, middleware, software, and operating systems can coexist to keep your system running properly.
  5. Efficiency - Distributed systems provide faster performance while making the best use of the underlying hardware's resources. As a result, you can handle any workload without fear of system failure due to volume spikes or underutilization of costly hardware.

What is Grid Computing?

Geographically dispersed computer networks combine to execute common tasks in grid computing. Distributed grids have the advantage of being formed from computing resources belonging to multiple individuals or organizations. 

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Top Distributed Computing Use Cases

Today, distributed computing is everywhere. Mobile and web applications are instances of distributed computing since numerous machines collaborate in the backend to provide you with accurate information.

Life Sciences and Healthcare

Distributed computing is used in healthcare and life sciences to model and simulate complicated life science data. With distributed systems, image analysis, medicinal medication research, and gene structure analysis have all become faster. Here are a few examples:

  • By visualizing molecular models in three dimensions, you can speed up structure-based medication design.
  • Reduce the time it takes to process genomic data to gain early insights into cancer, cystic fibrosis, and Alzheimer's.
  • Create intelligent systems that assist doctors in diagnosing patients by processing enormous amounts of complex imagery such as MRIs, X-rays, and CT scans.

Engineering Analysis

Engineers can use distributed systems to model difficult physics and mechanical principles. This research is used to improve product design, construct complicated structures, and create speedier cars. 

  • Computational fluid dynamics study investigates the behavior of liquids and applies those findings to aircraft design and racing.
  • To evaluate new plant engineering, electronics, and consumer items, computer-aided engineering requires compute-intensive simulation tools. 

Financial Services 

Distributed systems are used by financial services firms to execute high-speed economic simulations that assess portfolio risks, forecast market movements, and aid in financial decision-making. They can build web apps that take advantage of the capability of distributed systems to perform the following:

  • Provide low-cost, customized premiums
  • To securely support a huge volume of financial transactions, use distributed databases.
  • Protect clients from fraud by authenticating users.

Types of Distributed Computing Architecture

In distributed computing, you create apps that can run on multiple computers rather than just one. Distributed architecture is classified into four kinds.

Client-server Architecture 

Client-server is the most prevalent approach to organizing software on a distributed system. Clients and servers are the two groups of functions.

Clients - They have restricted access to information and computing power. Instead, they send queries to the servers, which are in charge of the majority of the data and other resources. The client accepts requests and communicates with the server on your behalf.

Servers - Server computers synchronize and manage resource access. They provide statistics or status information in response to customer inquiries. In most cases, one server can handle requests from several machines. 

Three-tier Architecture

In three-tier distributed systems, client computers stay as the first layer you access. Server machines, on the other hand, are further classified as follows:

Application servers - Application servers serve as the communication's intermediary tier. They contain the application logic or fundamental functions for which the distribution system was designed.

Database servers - Database servers function as the third tier, storing and managing data. They are in charge of data retrieval and consistency.

Three-tier distributed systems eliminate communication bottlenecks and improve distributed computing efficiency by separating server responsibility. 

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N-tier Architecture

N-tier models feature many client-server systems that communicate with one another to address the same problem. Most current distributed systems employ an n-tier architecture, with various enterprise applications operating as one system behind the scenes.

Peer-to-peer Architecture

All networked computers are given equal duties in peer-to-peer distributed systems. There is no distinction between client and server computers, and any computer can carry out all functions. Peer-to-peer architecture has grown in popularity for applications such as content sharing, file streaming, and blockchain networks.

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Conclusion

Distributed computing systems can run on hardware from a variety of suppliers and use a wide range of standards-based software components. These systems are unaffected by the underlying software. They can run on a variety of operating systems and employ a variety of communication protocols. Some hardware may utilize UNIX or Linux as the operating system, but other devices may use Windows. This hardware can communicate with other machines through SNA or TCP/IP over Ethernet or Token Ring. 

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FAQs

1. What is parallel computing?

Parallel computing is the act of breaking down big problems into smaller, independent, frequently comparable sections that can be executed concurrently by several processors communicating via shared memory. The results are integrated upon completion as part of an overall algorithm. The basic purpose of parallel computing is to enhance available computation power for faster application processing and issue-solving.

2. Why use distributed computing?

Distributed computing allows an application running on one computer to access processing power, memory, or storage on another. Although distributed computing may improve the performance of a stand-alone application, this is rarely the basis for distributing an application. Some applications, such as word processing, may not benefit at all from dispersion. In many circumstances, a specific issue may be demand distribution.

3. What are distributed computing applications?

There are numerous Distributed computing applications available. Some real-world examples of distributed systems:

  1. Computer Graphics Distributed Rendering
  2. Peer-to-Peer Networks (P2P)
  3. Online Massively Multiplayer Gaming

4. What are the best examples of distributed computing?

Example 1: Healthcare practitioners monitor both in-hospital and at-home patients using hybrid clouds and edge computing. Furthermore, it can aid in the tracking and monitoring of symptoms and illnesses through the use of IoT-based applications and sensors.

Example 2: Cars of the future would use artificial intelligence (AI) to assess data and make decisions. It will also employ 5G to record real-time data. As a result, leveraging distributed cloud computing opens up new possibilities for speedier data transfer and more accurate decision-making. Furthermore, Tesla's projects are real-world illustrations of how to use distributed cloud computing. 

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