Intermedia-Based Video Adaptation System:Design and Implementation

Video adaptation is a promising technique to bridge the gap between network status, device capabilities, and user preferences in pervasive media applications. However, conventional adaptation frameworks based on either transcoding or multiple pre-transcoding are not able to accommodate large numbers of users with diversified applications. This paper introduces an intermediate video description called ＂Inter- media＂, which consists of multiple level video signal components, such as texture, motion, and rate control information, as well as some semantic features, such as structural characteristics and Region Of Interest （ROI） information. It is generated off-line and stored in the video server or media gateway. Intermedia is then used to design a novel video adaptation system. The proposed adaptation system quickly and easily generates the required bit stream from Intermedia with very low complexity to fulfill a series of specific adaptation requirements, e.g., bitrate conversion, temporal/spatial resolution reduction, video summarization, ROI browsing, and some multi-level adaptations involving both signal level and semantic level adaptation. The satisfactory performance of such a system demonstrates the effectiveness and efficiency of the proposed video adaptation framework.

MEC-Assisted Flexible Transcoding Strategy for Adaptive Bitrate Video Streaming in Small Cell Networks

Adaptive bitrate video streaming(ABR)has become a critical technique for mobile video streaming to cope with time-varying network conditions and different user preferences.However,there are still many problems in achieving high-quality ABR video streaming over cellular networks.Mobile Edge Computing(MEC)is a promising paradigm to overcome the above problems by providing video transcoding capability and caching the ABR video streaming within the radio access network(RAN).In this paper,we propose a flexible transcoding strategy to provide viewers with low-latency video streaming services in the MEC networks under the limited storage,computing,and spectrum resources.According to the information collected from users,the MEC server acts as a controlling component to adjust the transcoding strategy flexibly based on optimizing the video caching placement strategy.Specifically,we cache the proper bitrate version of the video segments at the edge servers and select the appropriate bitrate version of the video segments to perform transcoding under jointly considering access control,resource allocation,and user preferences.We formulate this problem as a nonconvex optimization and mixed combinatorial problem.Moreover,the simulation results indicate that our proposed algorithm can ensure a low-latency viewing experience for users.