English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

Most client hosts are equipped with multiple network interfaces (e.g., WiFiand cellular networks). Simultaneous access of multiple interfaces cansignificantly improve the users' quality of experience (QoE) in videostreaming. An intuitive approach to achieve it is to use Multi-path TCP(MPTCP). However, the deployment of MPTCP, especially with link preference,requires OS kernel update at both the client and server side, and a vast amountof commercial content providers do not support MPTCP. Thus, in this paper, werealize a multi-path video streaming algorithm in the application layerinstead, by considering Scalable Video Coding (SVC), where each layer of everychunk can be fetched from only one of the orthogonal paths. We formulate thequality decisions of video chunks subject to the available bandwidth of thedifferent paths, chunk deadlines, and link preferences as an optimizationproblem. The objective is to to optimize a QoE metric that maintains a tradeoffbetween maximizing the playback rate of every chunk and ensuring fairness amongchunks. The QoE is a weighted some of the following metrics: skip/stallduration, average playback rate, and quality switching rate. However, theweights are chosen such that pushing more chunks to the same quality level ismore preferable over any other choice. Even though the formulation is anon-convex discrete optimization, we show that the problem can be solvedoptimally with a polynomial complexity in some special cases. We furtherpropose an online algorithm where several challenges including bandwidthprediction errors, are addressed. Extensive emulated experiments in a realtestbed with real traces of public dataset reveal the robustness of our schemeand demonstrate its significant performance improvement compared to othermulti-path algorithms.

Optimized Preference-Aware Multi-path Video Streaming with Scalable Video Coding