CODE: Computation Offloading in D2D-Edge System for Video Streaming

Abstract

Video traffic over the Internet is increasing rapidly, reaching up to 82% of the total Internet traffic by 2022. This enormous growth of video traffic which also include immersive video content (augmented reality and virtual reality streaming) is challenging for the existing network architectures. Mobile edge computing (MEC) is arising as a promising solution to enhance the user experience. However, edge servers have usually limited computational capabilities and may not cope with unplanned sudden spikes in traffic from live streaming of large events or when a video goes viral, known as the <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">thundering herd problem</i> . To improve the edge resource utilization, cooperation among edge servers has been proposed earlier. However, such cooperation is not useful in single-server scenario or when the neighboring servers are also fully utilized. Thus, in this article, we propose a novel D2D-MEC collaborative framework called as CODE (Computation Offloading in D2D-Edge) system in which an edge server offloads its computations to the distributed user devices (downlink). Two distinct schemes, i.e., maximal offloading with delay constraint (MOD) and minimum delay offloading (MDO) and a lightweight heuristic, are proposed to solve the computation offloading problem. Our simulation results report that the MOD scheme reduces the network delay up to 65%, whereas the MDO scheme reduces the edge computation load up to 83%.