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Efficient Computation Offloading in Mobile Cloud Computing for Video Streaming Over 5G
DEE, Kyung Hee University, Yongin, 17104, South Korea.
DCSE, Sejong University, Seoul, 05006, South Korea.
DSC, Kyung Hee University, Yongin, 17104, South Korea.
DEE, Kyung Hee University, Yongin, 17104, South Korea.
*Corresponding Authors: Doug Young Suh. Email: " />. Md. Jalil Piran. Email: " />.
Computers, Materials & Continua 2019, 61(2), 439-463. https://doi.org/10.32604/cmc.2019.08194
Abstract
In this paper, we investigate video quality enhancement using computation offloading to the mobile cloud computing (MCC) environment. Our objective is to reduce the computational complexity required to covert a low-resolution video to high-resolution video while minimizing computation at the mobile client and additional communication costs. To do so, we propose an energy-efficient computation offloading framework for video streaming services in a MCC over the fifth generation (5G) cellular networks. In the proposed framework, the mobile client offloads the computational burden for the video enhancement to the cloud, which renders the side information needed to enhance video without requiring much computation by the client. The cloud detects edges from the upsampled ultra-high-resolution video (UHD) and then compresses and transmits them as side information with the original low-resolution video (e.g., full HD). Finally, the mobile client decodes the received content and integrates the SI and original content, which produces a high-quality video. In our extensive simulation experiments, we observed that the amount of computation needed to construct a UHD video in the client is 50%-60% lower than that required to decode UHD video compressed by legacy video encoding algorithms. Moreover, the bandwidth required to transmit a full HD video and its side information is around 70% lower than that required for a normal UHD video. The subjective quality of the enhanced UHD is similar to that of the original UHD video even though the client pays lower communication costs with reduced computing power.Keywords
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