Distributed Computing Infrastructure

A Distributed Computing Infrastructure is a computing infrastructure that can be used to create distributed computing platforms (that support distributed computing workloads and coordinated distributed computing tasks across multiple distributed computing nodes).

• AKA: Distributed Infrastructure, Multi-Node Computing Infrastructure, Distributed System Infrastructure, Networked Computing Infrastructure.
• Context:
  • It can typically provide Distributed Computing Nodes including distributed computing servers, distributed computing storage devices, and distributed computing network equipment across multiple distributed computing locations.
  • It can typically enable Distributed Computing Coordination through distributed computing communication protocols and distributed computing synchronization mechanisms.
  • It can typically implement Distributed Computing Fault Tolerance via distributed computing redundancy, distributed computing replication, and distributed computing failure recovery systems.
  • It can typically support Distributed Computing Load Distribution across distributed computing resources for optimal distributed computing performance.
  • It can typically manage Distributed Computing Resource Allocation through distributed computing scheduling algorithms and distributed computing workload balancing.
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  • It can often enable Distributed Computing Scalability through horizontal distributed computing scaling and distributed computing capacity expansion.
  • It can often provide Distributed Computing Data Consistency via distributed computing consensus protocols and distributed computing transaction coordination.
  • It can often facilitate Distributed Computing High Availability through distributed computing clustering and distributed computing failover mechanisms.
  • It can often implement Distributed Computing Security across distributed computing networks with distributed computing access control and distributed computing encryption.
  • It can often support Distributed Computing Monitoring through distributed computing performance metrics and distributed computing health checks.
  • It can often enable Distributed Computing Elasticity for dynamic distributed computing resource adjustment based on distributed computing demand patterns.
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  • It can range from being a Local Distributed Computing Infrastructure to being a Global Distributed Computing Infrastructure, depending on its distributed computing geographic scope.
  • It can range from being a Homogeneous Distributed Computing Infrastructure to being a Heterogeneous Distributed Computing Infrastructure, depending on its distributed computing node diversity.
  • It can range from being a Tightly-Coupled Distributed Computing Infrastructure to being a Loosely-Coupled Distributed Computing Infrastructure, depending on its distributed computing component interdependency.
  • It can range from being a Centrally-Managed Distributed Computing Infrastructure to being a Self-Organizing Distributed Computing Infrastructure, depending on its distributed computing governance model.
  • It can range from being a Static Distributed Computing Infrastructure to being a Dynamic Distributed Computing Infrastructure, depending on its distributed computing reconfiguration capability.
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  • It can integrate with Distributed Computing Management Platforms for distributed computing orchestration and distributed computing automation.
  • It can connect to Cloud Computing Infrastructures for hybrid distributed computing deployments and distributed computing resource federation.
  • It can support Distributed Computing Development Frameworks for distributed computing application development and distributed computing service deployment.
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• Examples:
  • Traditional Distributed Computing Infrastructures, such as:
    • Cluster Computing Infrastructure for high-performance distributed computing with tightly-coupled distributed computing nodes.
    • Grid Computing Infrastructure for scientific distributed computing across geographically distributed computing resources.
    • Peer-to-Peer Distributed Computing Infrastructure for decentralized distributed computing without central distributed computing control.
  • Enterprise Distributed Computing Infrastructures, such as:
    • Data Center Distributed Computing Infrastructure for enterprise distributed computing workloads with redundant distributed computing systems.
    • Multi-Site Distributed Computing Infrastructure for disaster recovery distributed computing and business continuity distributed computing.
    • Hybrid Distributed Computing Infrastructure combining on-premises distributed computing with cloud distributed computing services.
  • Cloud-Native Distributed Computing Infrastructures, such as:
    • Container Orchestration Infrastructure like Kubernetes Distributed Computing Infrastructure for microservice distributed computing.
    • Serverless Distributed Computing Infrastructure for event-driven distributed computing and auto-scaling distributed computing.
    • Edge Distributed Computing Infrastructure for low-latency distributed computing and distributed computing at network edge.
  • Specialized Distributed Computing Infrastructures, such as:
    • AI Distributed Computing Infrastructure for machine learning distributed computing training and distributed computing AI inference.
    • Blockchain Distributed Computing Infrastructure for decentralized distributed computing transaction processing.
    • IoT Distributed Computing Infrastructure for sensor network distributed computing and distributed computing data collection.
    • Real-Time Distributed Computing Infrastructure for time-critical distributed computing applications and distributed computing stream processing.
  • Research Distributed Computing Infrastructures, such as:
    • Academic Grid Computing Infrastructure for computational science distributed computing and distributed computing research collaboration.
    • Supercomputing Distributed Computing Infrastructure for massively parallel distributed computing and high-throughput distributed computing.
  • ...
• Counter-Examples:
  • Centralized Computing Infrastructure, which uses single computing location rather than distributed computing nodes.
  • Standalone Computing Infrastructure, which operates independently without distributed computing coordination.
  • Personal Computing Infrastructure, which serves individual users rather than distributed computing workloads.
• See: Distributed Computing System, Computing Infrastructure, Cloud Computing Infrastructure, High-Performance Computing Infrastructure, Network Infrastructure, Cluster Computing System, Grid Computing System.

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