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Centralized System Architecture:

  • Centralized means the data is in one place.
  • Centralized database - that is have one large computer to which you connect a large number of terminals. Everyone is working directly on the machine that holds the database.

Client-server Architecture:

  • Client server just means the clients are in a different place than the data. It simply means the database is considered one unit managed by one DBMS in one location and to which clients connect.
  • Client/Server DB system relies [traditionally] on a single database-server, which passes information to a client machine, where some of the data processing is done

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How does client-server computing enhance communication and data sharing between clients and servers in a networked environment?

Client-server computing enhances communication and data sharing by allowing clients to request and receive information from servers over a network. This architecture enables efficient sharing of resources, centralized management, and improved security in a networked environment.


Is the ARM architecture better than x86 for computing tasks?

The ARM architecture is often considered more energy-efficient and better suited for mobile devices, while x86 is typically more powerful and commonly used in desktop and server computing. The choice between the two depends on the specific computing tasks and requirements.


What are the key differences between distributed computing and parallel computing, and how do these differences impact their respective performance and scalability?

Distributed computing involves multiple computers working together on a task, often across a network, while parallel computing uses multiple processors within a single computer to work on a task simultaneously. Distributed computing can be more flexible and scalable but may face challenges with communication and coordination between the computers. Parallel computing can be faster and more efficient for certain tasks but may be limited by the number of processors available. The choice between distributed and parallel computing depends on the specific requirements of the task at hand.


How does client/server computing enhance communication and data sharing between multiple devices on a network?

Client/server computing enhances communication and data sharing between multiple devices on a network by allowing for a centralized server to store and manage data, while clients can access and interact with this data. This setup enables efficient sharing of resources, improved security, and better coordination among devices on the network.


What are the key differences between parallel computing and distributed computing, and how do these differences impact their respective performance and scalability?

Parallel computing involves breaking down a task into smaller parts that are executed simultaneously on multiple processors within the same system. Distributed computing, on the other hand, involves dividing a task among multiple independent computers connected through a network. The key difference lies in how the tasks are divided and executed. In parallel computing, all processors have access to shared memory, allowing for faster communication and coordination. In distributed computing, communication between computers is slower due to network latency. This difference impacts performance and scalability. Parallel computing can achieve higher performance for tasks that can be divided efficiently among processors, but it may face limitations in scalability due to the finite number of processors available. Distributed computing, on the other hand, can scale to a larger number of computers, but may face challenges in coordinating tasks and managing communication overhead.

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