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Grid computing technology connects globally distributed processors to develop an immense source of computing power, which enables one to run applications in parallel that would take orders of magnitude more time on a single processor. Key characteristics of a global-scale grid are the strong burstiness in the amount of load on the resources and on the network capacities, and the fact that processors may be appended to or removed from the grid at any time. To cope with these characteristics, it is essential to develop techniques that make applications robust against the dynamics of the grid environment. For these techniques to be effective, it is important to have an understanding of the statistical properties of the dynamics of a grid environment.
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