Grid computing can mean different things to different individuals. The grand vision is often presented as an analogy to power grids where users (or electrical appliances) get access to electricity through wall sockets with no care or consideration for where or how the electricity is actually generated. In this view of grid computing, computing becomes pervasive and individual users (or client applications) gain access to computing resources (processors, storage, data, applications, and so on) as needed with little or no knowledge of where those resources are located or what the underlying technologies, hardware, operating system, and so on are.
Though this vision of grid computing can capture one's imagination and may indeed someday become a reality, there are many technical, business, political, and social issues that need to be addressed. If we consider this vision as an ultimate goal, there are many smaller steps that need to be taken to achieve it. These smaller steps each have benefits of their own.
Therefore, grid computing can be seen as a journey along a path of integrating various technologies and solutions that move us closer to the final goal. Its key values are in the underlying distributed computing infrastructure technologies that are evolving in support of cross-organizational application and resource sharing-in a word, virtualization-virtualization across technologies, platforms, and organizations. This kind of virtualization is only achievable through the use of open standards. Open standards help ensure that applications can transparently take advantage of whatever appropriate resources can be made available to them. An environment that provides the ability to share and transparently access resources across a distributed and heterogeneous environment not only requires the technology to virtualize certain resources, but also technologies and standards in the areas of scheduling, security, accounting, systems management, and so on.
Grid computing could be defined as any of a variety of levels of virtualization along a continuum. Exactly where along that continuum one might say that a particular solution is an implementation of grid computing versus a relatively simple implementation using virtual resources is a matter of opinion. But even at the simplest levels of virtualization, one could say that grid-enabling technologies are being utilized.
Starting in the lower left you see single system partitioning. Virtualization starts with being able to carve up a machine into virtual machines. As you move up this spectrum you start to be able to virtualize similar or homogeneous resources. Virtualization applies not only to servers and CPUs, but to storage, networks, and even applications. As you move up this spectrum you start to virtualize unlike resources. The next step is virtualizing the enterprise, not just in a data center or within a department but across a distributed organization, and then, finally, virtualizing outside the enterprise, across the Internet, where you might actually access resources from a set of OEMs and their suppliers or you might integrate information across a network of collaborators.
Early implementations of grid computing have tended to be internal to a particular company or organization. However, cross-organizational grids are also being implemented and will be an important part of computing and business optimization in the future.
The distinctions between intraorganizational grids and interorganizational grids are not based in technological differences. Instead, they are based on configuration choices given: Security domains, degrees of isolation desired, type of policies and their scope, and contractual obligations between users and providers of the infrastructures. These issues are not fundamentally architectural in nature. It is in the industry's best interest to ensure that there is not an artificial split of distributed computing paradigms and models across organizational boundaries and internal IT infrastructures.
Grid computing involves an evolving set of open standards for Web services and interfaces that make services, or computing resources, available over the Internet.
Very often grid technologies are used on homogeneous clusters, and they can add value on those clusters by assisting, for example, with scheduling or provisioning of the resources in the cluster. The term grid, and its related technologies, applies across this entire spectrum.
If we focus our attention on distributed computing solutions, then we could consider one definition of grid computing to be distributed computing across virtualized resources. The goal is to create the illusion of a simple yet large and powerful virtual computer out of a collection of connected (and possibly heterogeneous) systems sharing various combinations of resources.
