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Distributed Computing Models
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Publish-Subscribe Model
A messaging pattern where messages published by nodes are consumed by subscribers according to interest.
Eventual Consistency Model
A consistency model that ensures that all copies of data will eventually become consistent given enough time.
Peer-to-Peer Model
A decentralized model where each node can act as both a client and server, sharing resources among peers.
MapReduce Model
A programming model for processing large datasets with a distributed algorithm on a cluster.
Shared Nothing Architecture
Each node in the system is independent and self-sufficient, with no sharing of memory or storage.
Client-Server Model
A prevalent model where multiple clients request and receive services from a centralized server.
Master-Slave Model
A model with one central controlling server (master) and multiple managed servers (slaves).
Space-Based Model
Utilizes a virtualized middleware layer that keeps data in-memory across multiple nodes to ensure robustness and scalability.
Multi-tier Model
Layered approach dividing tasks across multiple servers such as presentation, application, and data storage.
Bulk Synchronous Parallel (BSP)
A bridging model for parallel computation that assumes a coherent global state between phases of operation.
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