  In this paper, we investigate the recent studies on multimedia edge
computing, from sensing not only traditional visual/audio data but also
individuals' geographical preference and mobility behaviors, to performing
distributed machine learning over such data using the joint edge and cloud
infrastructure and using evolutional strategies like reinforcement learning and
online learning at edge devices to optimize the quality of experience for
multimedia services at the last mile proactively. We provide both a
retrospective view of recent rapid migration (resp. merge) of cloud multimedia
to (resp. and) edge-aware multimedia and insights on the fundamental guidelines
for designing multimedia edge computing strategies that target satisfying the
changing demand of quality of experience. By showing the recent research
studies and industrial solutions, we also provide future directions towards
high-quality multimedia services over edge computing.
