Distributed Operating Systems (DOS) are software that manages a collection of independent computers (nodes) connected over a network, making them appear to users as a single system. Unlike traditional operating systems that run on a single computer, DOS distributes tasks and resources across multiple nodes to achieve greater processing power, reliability, and availability. **Key features of DOS:** - **Distributed processing:** Tasks are broken down and executed on different nodes concurrently, utilizing the combined processing power of the network. - **Resource sharing:** Resources like files, printers, and storage devices can be shared between nodes, maximizing utilization and efficiency. - **Transparency:** To users, the system appears as a single entity, even though tasks are distributed across multiple nodes. - **Scalability:** DOS can be easily expanded by adding more nodes to the network, increasing processing power and storage capacity as needed. - **Fault tolerance:** If one node fails, other nodes can take over its tasks, minimizing downtime and ensuring continued operation. **Components of a DOS:** - **Nodes:** Independent computers running the DOS software. - **Kernel:** The core of the DOS on each node, responsible for managing local resources and communicating with other nodes. - **Communication protocols:** Rules governing how nodes exchange information and coordinate their activities. - **Distributed file system:** Provides transparent access to files stored on any node in the network. - **Security mechanisms:** Secure communication and access control to protect resources and user data. **Benefits of using DOS:** - **Increased processing power:** By distributing tasks, DOS can handle complex workloads more efficiently than a single computer. - **Improved reliability:** Fault tolerance ensures that system failures in one node don't disrupt the entire system. - **Enhanced scalability:** DOS can be easily expanded to meet growing computational demands. - **Resource sharing:** Users can access shared resources regardless of their location on the network. **Examples of Distributed Operating Systems:** - **Apache Hadoop:** An open-source framework for distributed processing of large datasets. - **Microsoft Windows Server Cluster:** A cluster computing solution for high-availability applications. - **Red Hat OpenStack:** An open-source cloud computing platform built on a distributed architecture. **Applications of DOS:** - High-performance computing: Scientific simulations, weather forecasting, and other computationally intensive tasks. - Cloud computing: Providing scalable and elastic computing resources on demand. - Big data processing: Analyzing large datasets efficiently using distributed infrastructure. - Cluster computing: Combining multiple computers to tackle complex problems. # References ```dataview Table title as Title, authors as Authors where contains(subject, "Distributed Operating Systems") ```