
Table of Contents
Computational Models
The Computational Model is essential for networking. The organizational Computational Models permit the analysis of complex organizational dynamics, including communication flows, decision-making processes, and power structures within a network, In a LAN or a WAN, the overall objectives of a network are to lower the cost of equipment, to provide services, allow administration and security, and establish a means of sharing data. There are three organizational computational models or methods for networking.
There are three network computing models which are mostly used in organizations:
- Centralized computing
- Distributed Computing
- Collaborative Computing
1. Centralized Computing
Networking was first implemented through centralized computing. All networking takes place in a single, centralized location, as the name suggests. A UNIX host with several dumb terminals would be the best illustration of this.
The dumb terminals are nothing more than an interface for the host’s input and output, and the host actually performs all processing. All terminals that are directly connected to the host never communicate with one another because all interaction takes place in a single location.
The entire data processing will take place on the central machine; as a result, the client machine must send all data to the central node, which will increase the amount of unnecessary traffic between the server and the client machine. This system’s speed is low because the central machine must respond to every node.

Advantages of Centralized Computing
- In centralized computing the security is excellent.
- Centralize administration as both application logic and data reside on the same machine.
Disadvantages of Centralized Computing
- It costs a lot to purchase, lease, operate, and maintain a mainframe computer.
- The imitation is that both the application and the database are part of the same machine process, making it impossible to partition the application logic beyond the mainframe’s physical limitations.
2. Distributed Computing
PCs are being replaced by dumb terminals thanks to distributed computing. PCs can function independently and communicate with servers. Tasks are carried out locally, and data is transferred without the assistance of the server.
An NT server serving as a file server with several Windows 98 clients that can operate independently is a good illustration of this scenario. The Windows 98 clients can function independently. They obtain the file from the server and carry out the required action whenever they need it to be done. The server provides them with the file but does not instruct them on how to utilize the requested data;
Application logic was carried out on the client workstation rather than the server in this system. In addition, these servers provided access to computing resources like large hard drives and printers.

Advantages of Distributed Computing
- The cost of distributed computing is low.
- In a distributed system, computer resources can be increased or decreased by requirements.
Disadvantages of Distributed Computing
- This will provide share-level security because there is no central administration present.
- As the client machine can do processing, the client’s machine needs a large amount of power to run the application.
3. Collaborative Computing
Cooperative computing, also known as collaborative computing, enables computers to share processing as well as resources (like files). This can be invoked in either of two ways. To carry out a task, a server may share some processing power with a client or borrow the entire processor of an idle machine.
Microsoft SQL server is a classic illustration of this kind of environment. When a client requests data, the SQL server performs some processing and sends the data to the client so that the system can finish processing it. The software must always be written to exploit the absence of such software.
In collaborative architecture, the actual SQL statement is transmitted across the network and processed by a server-side application. Only the results need to be sent back to the client while the SQL statement is being processed on the server. Compared to the distributed system, this is a huge improvement.
At the server end, the query to find out which students have scored 100 per cent or more in two or more subjects is evaluated, and instead of all of the table’s records, only those that meet these criteria are sent over the network.
Advantages of Collaborative Computing
- Collaborative computing increased productivity.
- Collaborative computing saves time by centralizing the resources on a single platform.
Disadvantages of Collaborative Computing
- This is costly as compared to centralized and distributive computing.
- Collaborative computing applications may be facing poor network traffic performance.
Frequently Asked Questions (FAQs)
Why do we need centralized computing?
Centralized computing is used for security, data quality, and data consistency.
Why should we use distributed systems?
To reduce the risks involved with having a single point of failure, bolstering reliability and fault tolerance.
What is collaborative systems?
Collaborative systems allow people to work together on projects and documents in real-time, which can increase productivity and efficiency
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