Client-server architecture

Definition

Client-server architecture is a computing model that separates tasks between service providers, known as servers, and service requesters, known as clients. In this structure, clients initiate requests for resources or services, while servers provide the necessary resources or perform specific tasks in response. This setup is crucial for efficient data processing and resource management, especially in systems that support expert systems and knowledge-based AI.

5 Must Know Facts For Your Next Test

1. Client-server architecture enables scalable systems by allowing multiple clients to connect to a single server, making it easier to manage resources.
2. In expert systems, the client can be an interface where users input queries, while the server processes these queries using the knowledge base.
3. This architecture supports various network protocols, allowing for seamless communication between clients and servers over different platforms.
4. Security in client-server architecture is essential; authentication and encryption methods protect data exchanged between clients and servers.
5. Client-server systems can be categorized into two-tier and three-tier architectures, depending on the number of layers involved in processing requests.

Review Questions

• How does client-server architecture enhance the efficiency of expert systems?
  • Client-server architecture enhances the efficiency of expert systems by clearly separating the roles of clients and servers. Clients can focus on user interaction and input collection while delegating complex processing tasks to servers. This division allows servers to manage large databases and execute inference algorithms effectively, improving response times and overall system performance.
• Discuss the implications of using middleware in client-server architecture within knowledge-based AI applications.
  • Middleware plays a crucial role in client-server architecture by facilitating communication between various components of knowledge-based AI applications. It abstracts the complexities of different protocols and allows for seamless integration of diverse services. By using middleware, developers can enhance interoperability, enabling systems to leverage multiple AI models and databases without compromising performance or reliability.
• Evaluate the impact of security considerations on the design of client-server architecture used in expert systems.
  • Security considerations significantly impact the design of client-server architecture in expert systems. Since sensitive data often flows between clients and servers, implementing robust security measures is crucial. This includes authentication protocols to verify user identities, encryption methods to protect data in transit, and access control mechanisms to ensure that only authorized users can access certain resources. Such measures not only safeguard information but also build trust with users who rely on these systems for critical decision-making.

Related terms

Distributed Computing: A model where computing tasks are spread across multiple interconnected computers, allowing for resource sharing and parallel processing.

API (Application Programming Interface): A set of rules and protocols for building and interacting with software applications, enabling communication between clients and servers.

Middleware: Software that acts as a bridge between different applications or services, facilitating communication and data management in client-server systems.