Department: Electrical & Computer Engineering
Faculty Advisor(s): Sujit Dey

Primary Student
Name: Yao Liu
Email: yal019@ucsd.edu
Phone: 858-534-7883
Grad Year: 2014

Cloud Mobile Rendering (CMR), where compute intensive rendering is performed on cloud servers instead of on mobile devices, can be a promising approach to enable rich rendering based multimedia applications on battery and CPU constrained mobile devices. However, since the video rendered in the cloud has to be transmitted to the mobile device over a wireless network with fluctuating and constrained bandwidth, the resulting user experience can be impacted. In our previous research, an adaptive rendering approach was proposed, wherein multiple rendering factors can be adapted such that the bit rate of the encoded rendered video is compatible with the available network bandwidth. However, changing the rendering factors may itself have adverse impact on user experience, which has not been studied earlier. In this paper, we analyze the impairment of rendering factors on the quality of user experience, and combine the rendering impairments with impairments due to video encoding factors (like bit rate and frame rate) and network factors (like bandwidth and delay) to formulate a model to measure the user experience during a Cloud Mobile Rendering session. We term this model CMR-UE in this paper. We describe our method to derive the CMR-UE model, and demonstrate its accuracy through subjective testing using participants at UCSD. We use the CMR-UE model to study the trade-off between the impact of rendering and video encoding factors on user experience, and find the optimal rendering settings that maximize CMR-UE for any given network condition. Next, we use the CMR-UE model to measure user experience during CMR sessions on a live cellular network. We demonstrate how user experience can be significantly enhanced by using appropriate rendering settings under fluctuating network bandwidth conditions.

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