PROJECT TITLE :
Specific Versus Diverse Computing in Media Cloud
Specific computing (SC) and numerous computing (DC), as two main visual computation manners, have been widely used in Media Cloud. However, how to decide on SC or DC in a practical scenario continues to be an open and difficult downside. Unfortunately, the ancient fluid-based analysis method cannot address this issue because of the unsure relationship between the computing manner and service dynamics. In this paper, we tend to analytically study the characteristics of SC and DC by planning a thus-known as collapsing approximation (CA) technique to exactly approximate the distribution of the service dynamics. On the qualitative finish, we have a tendency to derive an actual expression for the dynamics of CA, so enabling the cloud designer to settle on different computing manners in step with the applying requests and analyze its impact on the degrees of DC. On the technical finish, we tend to show that the evolution of the service dynamics method will be approximated by the distinctive resolution to a collapsing model over a finite time period. The highlight of this paper lies in demonstrating that the optimal computing configuration should largely rely on SC, and a very little on DC.
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