Computational Grids combine heterogeneous, distributed resources across geographical and organisational boundaries. Grids may be formed to provide computational power for CPU-intensive simulation, high throughput computing for analysing many small tasks or for data intensive tasks such as those required by the LHC Experiments. For all of these situations the challenges are the same: how to enable dynamic access to these resources as securely, reliably and as efficiently as possible, without central control and omniscience.
The following chapter discuss the main concepts and components that combine to make computational Grids possible.
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There are four main characteristics that distinguish a Grid from other common distributed systems [REF]:
Heterogeneous: The resources of a Grid may be provided by multiple organisations, which are geographically distributed and execute local and autonomy resource utilisation policies. These resources are heterogeneous in service ability and the style of utilisation.
Extendable: A Grid is able to grow from a small amount resource set into a huge global infrastructure. The service ability of a Grid is scaleable to cope with the resource demands of various applications.
Dynamic: Since the resources and the services are contributed by multiple organisations and each organisation has its local resource management and utilisation policy, these resources and services are constantly dynamic available and shared subject to the autonomy of resources contributors and their utilisation behaviours.
High Communication Latency: Since a Grid may be constructed and distributed across a wide geographical distance, the communication latencies involved are likely higher than on any other localised system.
A Grid, according to Ian Foster [REF]:
These three points can be used as a starting point for our discussion. Distributed computing is a well known problem with many potential solutions. CORBA, RMI and more recently Web Services have been developed to cope with the failures and lack of information and control that is inherent in a distributed system. But these systems are no longer enough to satisfy the needs of the scientific and, increasingly, the business community. By combining distributed resources into a single virtual resource, users are able to access far more computing power at lower cost and higher efficiency. The real cost is in the increased complexity of the system. Resources providers and consumers are dynamic and the information and control of the system is incomplete. Hardware and network failures, power cuts and human error together with different architectures, operating systems and middleware must all be handled.
Without centralised control, networks of trust must be established. Collaborations create Virtual Organisations (VOs), which span traditional organisations and can be formed dynamically.
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