1 research outputs found
PLVER: Joint Stable Allocation and Content Replication for Edge-assisted Live Video Delivery
The live streaming services have gained extreme popularity in recent years.
Due to the spiky traffic patterns of live videos, utilizing the distributed
edge servers to improve viewers' quality of experience (QoE) has become a
common practice nowadays. Nevertheless, current client-driven content caching
mechanism does not support caching beforehand from the cloud to the edge,
resulting in considerable cache missing in live video delivery.
State-of-the-art research generally sacrifices the liveness of delivered videos
in order to deal with the above problem. In this paper, by jointly considering
the features of live videos and edge servers, we propose PLVER, a proactive
live video push scheme to resolve the cache miss problem in live video
delivery. Specifically, PLVER first conducts a one-tomultiple stable allocation
between edge clusters and user groups, to balance the load of live traffic over
the edge servers. Then it adopts proactive video replication algorithms to
speed up the video replication among the edge servers. We conduct extensive
trace-driven evaluations, covering 0.3 million Twitch viewers and more than 300
Twitch channels. The results demonstrate that with PLVER, edge servers can
carry 28% and 82% more traffic than the auction-based replication method and
the caching on requested time method, respectively