The Fourteen International Workshop on Selected Topics in Wireless and Mobile computing (STWiMob 2022)
October 10-12, 2022 | Thessaloniki, Greece
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Jesús Aguilar Armijo (Alpen-Adria-Universität Klagenfurt), Christian Timmerer (Alpen-Adria-Universität Klagenfurt) and Hermann Hellwagner (Alpen-Adria-Universität Klagenfurt)
Abstract: Segment prefetching is a technique that consists of sending the next segment(s) in advance closer to the user to serve content with reduced latency. Due to its location and capabilities, an edge computing node is an ideal component for executing
segment prefetching policies and storing/caching the prefetched segments. In this work, we study segment prefetching techniques deployed at the edge computing node for adaptive video streaming. We propose different types of segment prefetching policies
and study their costs and benefits, including segment prefetching based on past segment requests, transrating, a Markov prediction model, and machine learning. Besides, we analyze which segment prefetching policy is better under which circumstances, and the
influence of the ABR algorithm and the bitrate ladder on segment prefetching.
Keywords: Edge computing, MEC, content delivery, adaptive video streaming, HAS, segment prefetching
