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GRID COMPUTING PRESENTED BY : Richa Chaudhary
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AGENDA What is Grid Computing ? How Grid Computing Works ?
Reasons for using Grid Computing ? Grid Architecture Grid computing behavior Advantages and Disadvantages
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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. The grid can be thought of as a distributed system with non-interactive workloads that involve a large number of files.
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Now the question arises,what is grid computing,as u see in this figure Grid computing (or the use of a computational grid) is applying the resources of many computers in a network to a single problem at the same time - usually to a scientific or technical problem that requires a great number of computer processing cycles or access to large amounts of data. 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
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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 Now its vry imp 2 knw hw grid computing works At least one computer, usually a server, which handles all the administrative duties for the system. Many people refer to this kind of computer as a control node. Other application and Web servers (both physical and virtual) provide specific services to the system. A network of computers running special grid computing network software. These computers act both as a point of interface for the user and as the resources the system will tap into for different applications. Grid computing systems can either include several computers of the same make running on the same operating system (called a homogeneous system) or a hodgepodge of different computers running on every operating system imaginable (a heterogeneous system). The network can be anything from a hardwired system where every computer connects to the system with physical wires to an open system where computers connect with each other over the Internet. A collection of computer software called middleware. The purpose of middleware is to allow different computers to run a process or application across the entire network of machines. Middleware is the workhorse of the grid computing system. Without it, communication across the system would be impossible. Like software in general, there's no single format for middleware.
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Grid Architecture
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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. Fabric layer:All resources on which such a standardized interface is applicable, can be integrated in the grid concept. This contains computers, storage systems, networks or sensors. Resouce & conn layer :This contains initiation, observation, control, clearance and negotiation of security parameters. Also processor resources get assigned, reserved, observed and controlled. Collective :The jobs of this layer contain among others the creation of a directory service, they supply monitoring, diagnostic and file replication services. Furthermore grid-capable development systems are provided to be able to use popular programming models also in a grid environment.
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Difference between grid & distributed computing
Distributed computing refers to the means by which a single computer program runs in more than one computer at the same time. In particular, the different elements and objects of a program are being run or processed using different computer processors. Distributed computing is similar to parallel computing and grid computing. Grid computing, on the other hand, refers to a more dedicated distributed computing setup – one whose computer ‘members’ are especially dedicated to the program being processed.
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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. Grid computing has been around for over 12 years now and its advantages are many
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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. Grid computing has been around for over 12 years now and its advantages are many
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Applications Distributed supercomputing High-throughput computing
On-demand computing Data-intensive computing Collaborative computing One of the most obvious applications is in medicine. Imagine if your doctor had access to a grid that could handle administrative databases, medical image archives and specialized instruments such as MRI machines, CAT scanners and cardioangiography devices... This could enhance diagnosis procedures, speed analysis of complex medical images, and enable life-critical applications such as telerobotic surgery and remote cardiac monitoring.
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THANK YOU !! One of the most obvious applications is in medicine. Imagine if your doctor had access to a grid that could handle administrative databases, medical image archives and specialized instruments such as MRI machines, CAT scanners and cardioangiography devices... This could enhance diagnosis procedures, speed analysis of complex medical images, and enable life-critical applications such as telerobotic surgery and remote cardiac monitoring.
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