Grid computing is the amalgamation of several computing resources from several supervisory domains into one or more logical entity, coordinated with a high performance distributed grid and applied to solving large batch processing problems.
Such problems require a computing infrastructure with a great deal of processing cycles to run to completion. It can be described as a form of distributed and parallel system that fosters seamless and dynamic runtime sharing, accumulating, hosting and providing services globally.
The following diagram represents a grid computing structure. Grid computing is also referred to as a super virtual computer. In grid computing, computing resources are located on a loosely-coupled but geographically dispersed, distributed and heterogeneous networks unlike in cluster computing.
However, it shares some similar characteristics such as resource pooling, scalability, network access and resiliency with cloud computing. Resource sharing, virtualization, service workflow coordination, security and scalability are the basic characteristics of a grid infrastructure.
Advantages of Grid Computing
- It ensures easy scaling of applications
- It utilizes underused resources more adequately
- It allows the consolidation of the power and capabilities of several low configuration systems into one
- It adopts the use of open source, trust, transparency, and technology
- It increases the computing reliability power
- It allows seamless sharing and distribution of computing resources across networks
- It supports parallel processing of programs and data
- It guarantees optimal resource balancing
Disadvantages of Grid Computing
- It suffers from proprietary approach
- It is very complex
- If a node on the gird is down, a single point of failure occurs