-Dhanapathi
Data is growing exponentially. It is growing at the rate of approximately 45GB per person. This is doubling every five years. Data centres in US are consuming 100 billion KW of electricity per year. Finding better ways to store and manage data is not just enough. We need greener ways.Data centres are power hungry. We need solutions that ensure lesser power usage, less cooling, less water usage and less management space. We need more efficient, more flexible and more environment friendly solution i.e. the one that consume less no. of resources.
The solution to the problem is Grid Computing. Grid computing is the technology that enables resource virtualization, on-demand provisioning, and service (resource) sharing between organizations. Sever Virtualization and Clustering allows applications to get a shared pool of IT resources that can be distributed and redistributed.
What is Grid Computing
Grid Computing refers to the automated sharing and coordination of the collective processing power of many widely scattered, robust computers that are not normally centrally controlled, and that are subject to open standards.
Grid Computing allows the virtualization of distributed computing and data resources such as processing, network bandwidth and storage capacity to provide a unique system image, granting users and applications access to vast IT capabilities.
User enters the Grid through a Software Interface. For the user to use the Grid he should have proper authentication and authorization privileges. System performs Security Validations. Once the System finds that the user is authenticated then the System takes the user request to Resource Broker. The Resource Broker checks from the catalogue of Information Service for the resource that has the ability to perform the job requested by user. The Resource Broker directs the job to corresponding resource.
Characteristics
- Distributed System: - Several computers are connected through a network infrastructure.
- High Security: - Strict Authentication and encryption are needed.
- System Management: - Sophisticated management to keep the system running, monitoring, correct the failures and so on.
- Site Autonomy: - Autonomy of the users must be obeyed. That is users should be allowed to work on their interested system.
CPU-scavenging, cycle-scavenging, cycle stealing or shared computing creates a “grid” from the unused resources in a network of participants (whether worldwide or internal to an organization). Typically this technique uses desktop computer instruction cycles that would otherwise be wasted at night, during lunch, or even in the scattered seconds throughout the day when the computer is waiting for user input or slow devices. Volunteer computing projects use the CPU scavenging model almost exclusively.
In practice, participating computers also donate some supporting amount of disk storage space, RAM, and network bandwidth, in addition to raw CPU power. Since nodes are likely to go "offline" from time to time, as their owners use their resources for their primary purpose, this model must be designed to handle such contingencies.
Key Problems
- Security- How to authenticate and authorize users in a decentralized ways. How to ensure the safety of data that is transmitted.
- Resource Management:- How to manage the resources with out a Central Entity.
- Data Management:- How to copy data to other sites. Since the data goes through Internet, it must be ensured that Data is transmitted at a faster pace.
- Information Services- How to retrieve data from a particular site. How to find out the apt site.
Grid computing is where more than one computer coordinates to solve a problem together. Often used for problems involving a lot of number crunching, which can be easily parallelisable.
Cloud computing is where an application doesn't access resources it requires directly, rather it accesses them through something like a service. So instead of talking to a specific hard drive for storage, and a specific CPU for computation, etc. it talks to some service that provides these resources. The service then maps any requests for resources to its physical resources, in order to provide for the application. Usually the service has access to a large amount of physical resources, and can dynamically allocate them as they are needed.
In this way, if an application requires only a small amount of some resource, say computation, then the service only allocates a small amount, say on a single physical CPU (that may be shared with some other application using the service). If the application requires a large amount of some resource, then the service allocates that large amount, say a grid of CPUs. The application is relatively oblivious to this, and all the complex handling and coordination is performed by the service, not the application. In this way the application can scale well.
For example a web site written "on the cloud" may share a server with many other web sites while it has a low amount of traffic, but may be moved to its own dedicated server, or grid of servers, if it ever has massive amounts of traffic. This is all handled by the cloud service, so the application shouldn't have to be modified drastically to cope. A cloud would usually use a grid. A grid is not necessarily a cloud or part of a cloud.
Conclusion
Grid Computing is a strategy to save money and become greener at the same time. Grid Computing is a process that can be considered as a Mainstream Conveyor belt of Modern Engineering Development and Design development. Grid computing can be used in the areas of Designing Cars, Planes, Computers, Chips, New Drugs, Oil and Gas Field, Human Gnome study, Predicting the Climate changes, Calculation of risk in Financial Investment risks. Using Grid Computing as a part of Cloud Computing will increase the system ability and performance.
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