Bandwidth prediction schemes for defining bitrate levels in SDN-enabled adaptive streaming
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Date
2019
Journal Title
Journal ISSN
Volume Title
Publisher
PEARL
Abstract
The majority of Internet video traffic today is
delivered via HTTP Adaptive Streaming (HAS). Recent studies
concluded that pure client-driven HAS adaptation is likely to be
sub-optimal, given clients adjust quality based on local feedback.
In [1], we introduced a network-assisted streaming architecture
(BBGDASH) that provides bounded bitrate guidance for a video
client while preserving quality control and adaptation at the
client. Although BBGDASH is an efficient approach for video
delivery, deploying it in a wireless network environment could
result in sub-optimal decisions due to the high fluctuations. To
this end, we propose in this paper an intelligent streaming archiĀ
tecture (denoted BBGDASH +), which leverages the power of time
series forecasting to allow for an accurate and scalable network-
based guidance. Further, we conduct an initial investigation of
parameter settings for the forecasting algorithms in a wireless
testbed. Overall, the experimental results indicate the potential
of the proposed approach to improve video delivery in wireless
network conditions.
Description
Journal article
Keywords
SDN, QoE, DASH, OpenFlow, Stability, Streaming architecture, AdapĀtive video streaming, Network-assistance, Bounded bitrate guidance