TYPES OF DISTRIBUTED SYSTEM: CLUSTER,GRID AND CLOUD
1. Cluster Computing:
- Architecture: Tightly coupled system with high-performance computers connected by a high-speed network (like Ethernet).
- Purpose: Focused on high-performance computing tasks that require significant processing power for complex calculations or simulations.
- Resource Sharing: Resources like storage and processing power are shared within the cluster, but access is typically restricted and managed centrally.
- Centralization: Relatively high level of centralization with dedicated cluster management software.
- Examples: Scientific computing, weather forecasting, animation rendering.
2. Grid Computing:
- Architecture: Loosely coupled system consisting of geographically dispersed computers (desktops, servers, etc.) connected to the internet.
- Purpose: Utilizes idle computing power of individual machines to tackle large-scale computational problems that require more processing power than a single computer can provide.
- Resource Sharing: Resources are contributed voluntarily or through market-based mechanisms. Users may not be aware of the specific machines contributing to their task.
- Centralization: Lower level of centralization compared to clusters. Grid middleware manages resource allocation and job scheduling.
- Examples: Drug discovery simulations, protein folding analysis, large-scale climate modeling.
3. Cloud Computing:
- Architecture: On-demand delivery of computing resources (servers, storage, databases, software) over the internet. Users access these resources through a web interface or APIs.
- Purpose: Provides a flexible and scalable way to access computing resources without managing physical infrastructure. Used for a wide range of applications, from web hosting to data analytics.
- Resource Sharing: Resources are pooled and dynamically allocated to users based on their needs. Users typically don't have control over the underlying infrastructure.
- Centralization: Highly centralized with cloud providers managing the infrastructure and offering services.
- Examples: Web hosting, online storage, software as a service (SaaS), platform as a service (PaaS), infrastructure as a service (IaaS).
Here's a table summarizing the key differences:
| Feature |
Cluster Computing |
Grid Computing |
Cloud Computing |
| Architecture |
Tightly coupled |
Loosely coupled |
On-demand via internet |
| Purpose |
High-performance computing |
Large-scale problem solving |
Flexible, on-demand resources |
| Resource Sharing |
Controlled, within cluster |
Voluntary, geographically dispersed |
Pooled, dynamic allocation |
| Centralization |
High |
Lower |
Highly centralized |
| Examples |
Scientific computing, rendering |
Drug discovery simulations, climate modeling |
Web hosting, data analytics, SaaS
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