Distributed computing is a model where multiple computers (nodes) work together to solve tasks more efficiently than a single system. It is widely used for large-scale applications like cloud computing, big data processing, and online gaming.
Key Features of Distributed Computing:
- Scalability – Easily adds more nodes to increase processing power.
- Fault Tolerance – If one node fails, others continue working.
- Parallel Processing – Tasks are divided among multiple computers for faster execution.
- Resource Sharing – Memory, storage, and processing power are shared across systems.
- Cluster Computing – A group of connected computers acts as a single system (used in cloud services).
- Grid Computing – Utilizes idle computing resources across multiple devices (used in scientific research).
- Cloud Computing – Provides services over the internet like storage, computing power, and networking.
- Peer-to-Peer (P2P) – Devices interact directly without a central server (used in file sharing and blockchain).
- Cloud Services – Google Drive, Dropbox, and AWS use distributed computing.
- Big Data Processing – Apache Hadoop and Spark process large datasets.
- Online Gaming – Multiplayer games like PUBG and Fortnite use distributed servers.
- Scientific Computing – Used in weather prediction, DNA sequencing, and space research.