Cluster Computing: Definition, Architecture, and Algorithms

Defining Cluster Computing

In the most basic form, Cluster computing depicts a system that consists of two or more computers or systems, often known as nodes. These nodes work together for executing applications and performing other tasks. The users using nodes have an apprehension that only a single system responds to them, creating an illusion of a single resource called virtual machines. This concept is defined as the transparency of the system. Other essential features that are required for constructing such platforms include- reliability, load balancing, and performance.

Cluster Computing Architecture

Types of Cluster

1. High Availability (HA) and Failover Clusters – These cluster models create availability of services and resources in an uninterrupted method using the system’s implicit redundancy. The basic idea in this form of Cluster is that if a node fails, then applications and services can be made available to other nodes. These types of Clusters serve as the base for critical missions, mails, files, and application servers.

HA Cluster

2. Load Balancing Clusters – This Cluster distributes all the incoming traffic/requests for resources from nodes that run the same programs and machines. In this Cluster model, all the nodes are responsible for tracking orders, and if a node fails, then the requests are distributed amongst all the nodes available. Such a solution is usually used on web server farms.

Load Balancing Cluster

3. HA & Load Balancing Clusters – This cluster model combines both clusters’ features, resulting in increased availability and scalability of services and resources. This type of Clusters is commonly used for email, web, news, and FTP servers.

HA & Load Balancing Cluster

4. Distributed & Parallel Processing Clusters – This Cluster model enhances availability and performance for applications that have large computational tasks. A large computational task gets divided into smaller tasks and distributed across the stations. Such Clusters are usually used for scientific computing or financial analysis that require high processing power. Read More>>