Video transcoding at the edge: cost and feasibility perspective

Abstract

The developments in smartphones, high data rates, and substantial video data traffic have increased the burden on cellular networks. Consequently, this burden significantly affects the Quality of Experience of the cellular users leading to an increased network delay for the diverse video content requests. To accommodate the requests from different users with varying requirements, one of the promising solutions is to cache videos in the near vicinity of users and transcode them online. The online transcoding is performed at the edge level of the cellular network to minimize the network delay and use the bandwidth efficiently. However, the feasibility of online transcoding is significantly affected by various factors, such as the codecs, configurations of virtual machines, the cost incurred, and estimated time to complete the transcoding task, among other parameters. Although online transcoding is discussed in the literature adequately, few studies discuss the feasibility of online transcoding while considering all the aforementioned critical parameters. This study examined the effects of a diverse range of critical parameters on the feasibility of online transcoding. We performed extensive simulations on the local machine environment to study various possible factors affecting online transcoding in detail. We then transcoded the same videos on Amazon Elastic Cloud Computing (EC2) Virtual Machines (VMs) to further study realistic cloud settings with fine-tuned configurations. Our experiments show the superior performance of some codecs and the effects of machine configurations on transcoding tasks duration. We aim to provide a benchmark for practitioners and researchers considering online transcoding in real-time multimedia applications.