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Computational and Data Grids: Principles, Applications and Design

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After a lot of development efforts, computer science led us undoubtedly to technological revolutions which have been characterized by the creation of the Internet that influences the future of this science. The next revolutionary step occurred by the necessity of the creation of a new computer network, when researchers realized that the computer resources are underutilized. Researchers observed that machines spent much time idly waiting for human input increasing their cost through their underutilization. Their efforts concentrated in maximizing the utilization of computational resources, decreasing at the same time the cost of the computers. A vision for a new computer infrastructure was born at Argonne National Laboratory. The fathers of this unforeseen revolution were Foster & Kesselman (1997). They coined a new term about this new infrastructure which changed the way we think about computer science while they aimed to make computational resources available and efficient to everyone, like electricity.

The term Grid has defined a new scientific area of computing which combines heterogeneous, geographically dispersed computer resources that are a part of various administrative domains and cooperate in order to reach a common goal. The most significant achievement of this new emerged infrastructure is the resources sharing across various loosely coupled networks. The outcome of resources sharing combination with uniqueness characteristics, such as adaptability, applicability, flexibility, interoperability, usability, and scalability, is a grid network which provides us with vast computational and storage capabilities.

A strong basis of the definition was given by the father of the grid, Foster (2002), who defined a grid network with the following requirements. A grid system should have resources coordination that are not subject to centralized control, the usability of standard, open, general-purpose protocols and interfaces, while it delivers nontrivial Quality-of-Service (QoS). The integration between distributed and heterogeneous resources is achieved through a middleware. The usage of a grid middleware is compulsory because it acts as a mediator layer providing a consistent and homogeneous access to resources managed locally with different syntax and access methods.
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