Distributed Computing Models
Distributed computing is when tasks are split up and sent to different computers to do the work. There are three main ways this happens:
1. Client-Server Architecture
A model where clients make requests to centralized servers, which then perform computations and process data in response to those requests.
Think of this like ordering food from a restaurant. You’re the client, and the restaurant is the server. You tell the restaurant what you want, and they do the cooking and give you the finished dish.
2. Peer-to-Peer Networks
A system where individual computers (peers) collaborate directly with each other to share resources and perform tasks, rather than relying on centralized servers.
Imagine a group of friends doing a group project together. Instead of one person doing all the work, everyone pitches in with their skills and resources to get the job done together.
3. MapReduce Paradigm
A method for processing large datasets in parallel across distributed clusters of computers. It involves two main steps: mapping, where data is divided and processed by multiple nodes, and reducing, where the results are combined to produce the final output.
This is like a factory assembly line. Each worker (or computer) does a specific task on a small part of the product, and then everything gets put together at the end to make the final product. Google came up with this idea to handle really big sets of data more efficiently.
Components of Distributed System
Many modern computing platforms, such as Internet applications or systems, are built on distributed systems, which function as essential infrastructure.
- These systems feature good scalability, fault tolerances, and application flexibility, which enable them to be used in various areas, including cloud computing, IoT, and big data analytics.
- It is necessary to learn the components of distributed systems, as it would be part of designing, developing, and maintaining faultless or efficient systems.
Important Topics for Components of Distributed System
- Communication Infrastructure
- Distributed Data Storage
- Distributed Computing Models
- Distributed Coordination
- Fault Tolerance Mechanisms
- Scalability Techniques
- Security in Distributed Systems
- Distributed System Monitoring and Management
- Deployment and orchestration
- Integration with Cloud Services