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GRID COMPUTING

GRID COMPUTING. PRESENTED BY : Richa Chaudhary . AGENDA. What is Grid Computing ? How Grid Computing Works ? Reasons for using Grid Computing ? Grid Architecture Grid computing behavior Advantages and Disadvantages. WHAT IS A GRID ?.

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GRID COMPUTING

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  1. GRID COMPUTING PRESENTED BY : Richa Chaudhary

  2. AGENDA • What is Grid Computing ? • How Grid Computing Works ? • Reasons for using Grid Computing ? • Grid Architecture • Grid computing behavior • Advantages and Disadvantages

  3. WHAT IS A GRID ? Grid is a shared collection of reliable (cluster-tightly coupled) & unreliable resources (loosely coupled machines) and interactively communicating researchers of different virtual organisations (doctors, biologists, physicists). Grid System controls and coordinates the integrity of the Grid by balancing the usage of reliable and unreliable resources among its participants providing better quality of service.

  4. Grid computing is a method of harnessing the power of many computers in a network to solve problems requiring a large number of processing cycles and involving huge amounts of data. Most organizations today deploy firewalls around their computer networks to protect their sensitive proprietary data. But the central idea of grid computing-to enable resource sharing makes mechanisms such as firewalls difficult to use

  5. How Grid computing works ? • In general, a grid computing system requires: • At least one computer, usually a server, which handles all the administrative duties for the System • A network of computers running special grid computing network software. • A collection of computer software called middleware

  6. Grid Architecture

  7. Working of layers • Fabric. The lowest layer job is used to make a common interface on all possible kinds of resources available. Access by higher layers is granted via standardized processes.  • Resource and connectivity protocols: The connectivity layer defines the basic communication- and authentication protocols which are needed by the grid. While the communication protocols allow the exchange of files between different resources connected by the first layer, the authentication protocols allow to communicate confidentially and to ensure the identity of the two partners. • Collective services: The purpose of this layer is the coordination of multiple resources. Access to these resources doesn’t happen directly but merely via the underlying protocols and interfaces.  • User applications: To this layer belong all those applications which are operating in the environment of a virtual organization. Jobs of the lower layers get called by applications and can use resources transparently.

  8. Difference between grid & distributed computing

  9. Advantages of Grid Computing • Business benefits • Improve efficiency by improving computational capabilities • Bring together not only IT resources but also people. • Create flexible, resilient operational infrastructures • Address rapid fluctuations in customer demands. • Technology benefits • Federate data and distribute it globally. • Support large multi-disciplinary collaboration across organizations and business. • Enable recovery and failure • Ability to run large-scale applications comprising thousands of computes, for wide range of applications. • Reduces signal latency – the delay that builds up as data are transmitted over the Internet.

  10. Disadvantages of Grid Computing • Resource sharing is further complicated when grid is introduced as a solution for utility computing where commercial applications and resources become available as shareable and on demand resources. • The concept of commercial on-demand shareable adds new, more difficult challenges to the already complicated grid problem list including service level features, accounting, usage metering, flexible pricing, federated security, scalability, and open-ended integration. • Some applications may need to be tweaked to take full advantage of the new model. • Licensing across many servers may make it prohibitive for some apps. Vendors are starting to be more flexible with environment like this.

  11. Applications • Distributed supercomputing • High-throughput computing • On-demand computing • Data-intensive computing • Collaborative computing

  12. THANK YOU !!

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