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Rendering Cloud for Processing Computer Vision, Graphics and Image

Authors: Kun Gao -; Wang Qin -; Lifeng Xi -;

Rendering Cloud for Processing Computer Vision, Graphics and Image

Abstract

This paper proposes a novel rendering cloud computing architecture for computer vision, graphics and image processing. This architecture attends to rendering cloud computing through the concept of rendering-aware cloud and cloud-aware rendering. At first we present a rendering-aware cloud that focus on the capability of distributed computing, computer reposition and quality of service. In order to attain the best QoS for rendering processing, we design a RBC (Rendering Border Cloudlet) framework, in which data reposition, data computing, and rendering processing are presented at the border to supply the capability of distributed parallel computing and QoS. And then we design a cloudaware rendering which process the rendering service and program interface, for example data reposition and information exchanging, resource allocation and tasks scheduler, can optimally employ cloud architecture to attain better performance. Finally, we conduct experiments to validate the feasibility of the architecture we proposed. The result of experiments illustrate that the architecture has the capability to render computer digital media over the cloud environment.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
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