Distributed Systems Models

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Different models of distributed systems, such as peer to peer, client-server, and others.

Network Protocols: The protocols used to ensure communication between different components in a distributed system.
Message Queues: A tool/platform that enables asynchronous communication between components in a distributed system.
Consensus Protocols: A set of algorithms that help to maintain consistency across different nodes in a distributed system.
Cluster Management: The process of managing, monitoring, and scaling a cluster of nodes in a distributed system.
Data Replication: The process of copying data across different nodes in a distributed system to ensure availability and data consistency.
Load Balancing: The process of distributing incoming network traffic across multiple nodes in a distributed system to maintain availability.
Fault Tolerance: The ability of a system to continue operating even if one or more components fail.
Distributed File Systems: A file system that is distributed across multiple nodes in a distributed system.
Time Synchronization: The process of ensuring that clocks across different components in a distributed system are synchronized.
Distributed Databases: A database that is distributed across multiple nodes in a distributed system.
Peer-to-Peer Networks: A type of network where all nodes have equal responsibilities and can communicate and share resources with each other directly.
MapReduce: A framework for parallel processing of large datasets across a distributed system.
Eventual Consistency: A consistency model that allows for some degree of inconsistency across different nodes in a distributed system.
Microservices: Architecture that decomposes an application into small, independent, and loosely coupled services that communicate with each other via APIs.
Service Discovery: The process of discovering available services in a distributed system.
Containerization: The process of packaging applications and their dependencies into containers that can run anywhere.
Orchestration: The process of automating the deployment, scaling, and management of containers in a distributed system.
Security: The processes and techniques used to secure a distributed system, including authentication, authorization, and encryption.
Cloud Computing: A model for delivering computing resources over the internet, including storage, processing power, and applications.
Internet of Things (IoT): A network of physical devices that are connected to the internet and can communicate with each other.
Client-server model: A client-server model is a distributed system model in which a single server provides services to multiple clients that request them.
Peer-to-peer (P2P) model: In the P2P model, all nodes in a network function as both clients and servers. Each node can access resources and services from other nodes, as well as share its own resources and services.
Hybrid model: A hybrid model combines client-server and P2P models, where some nodes operate as servers while others operate as both clients and servers.
Cloud computing model: Cloud computing is a distributed model in which computing resources, such as storage and processing power, are provided over the internet by a third-party provider.
Grid computing model: Grid computing is a distributed model in which multiple independent computers work together to solve a complex problem, usually requiring a large amount of computation.
Cluster computing model: Cluster computing is a distributed model in which multiple independent computers are connected and work together as a single system to increase performance or reliability.
Mobile agent model: In a mobile agent model, software agents are sent to remote nodes to perform tasks and retrieve data. The agents can move between nodes dynamically as needed.
Message-passing model: The message-passing model is a distributed system model in which processes communicate with each other using messages sent over a network.
Service-oriented architecture (SOA) model: In an SOA model, services are loosely coupled and can be accessed over a network using standardized protocols.
Event-driven model: The event-driven model is a distributed system model in which processes respond to events, such as the receipt of a message, by triggering actions or processes.
"A distributed system is a system whose components are located on different networked computers, which communicate and coordinate their actions by passing messages to one another."
"Distributed computing is a field of computer science that studies distributed systems."
"The components of a distributed system interact with one another in order to achieve a common goal."
"Three significant challenges of distributed systems are: maintaining concurrency of components, overcoming the lack of a global clock, and managing the independent failure of components."
"When a component of one system fails, the entire system does not fail."
"Examples of distributed systems vary from SOA-based systems to massively multiplayer online games to peer-to-peer applications."
"A computer program that runs within a distributed system is called a distributed program."
"Distributed programming is the process of writing such programs."
"There are many different types of implementations for the message passing mechanism, including pure HTTP, RPC-like connectors, and message queues."
"Distributed computing also refers to the use of distributed systems to solve computational problems."
"In distributed computing, a problem is divided into many tasks."
"Each task is solved by one or more computers, which communicate with each other via message passing."
"The components of a distributed system... communicate and coordinate their actions by passing messages to one another."
"Maintaining concurrency of components" is a significant challenge in distributed systems.
"Overcoming the lack of a global clock" is a significant challenge in distributed systems.
"Managing the independent failure of components" is a significant challenge in distributed systems.
"When a component of one system fails, the entire system does not fail."
"Examples of distributed systems vary from SOA-based systems to massively multiplayer online games to peer-to-peer applications."
"A computer program that runs within a distributed system is called a distributed program."
"Computers in distributed computing... communicate with each other via message passing."