Robust QoE-Driven DASH Over OFDMA Networks

Xiao, Kefan; Mao, Shiwen; Tugnait, J.K.

doi:10.1109/tmm.2019.2929929

Cited by 13 publications

(3 citation statements)

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“…This scheme aims to maximize the profit of the video service provider while satisfying users' quality requirements. The problem of QoE-aware multi-bitrate video caching is considered in [12]- [14], [32]. In [32], a compound QoE model is proposed for the delivery of Dynamic Adaptive Streaming over HTTP (DASH) videos over an orthogonal frequency-division multiplexing access (OFDMA) network.…”

Section: B Adaptive Bitrate Video Cachingmentioning

confidence: 99%

“…The problem of QoE-aware multi-bitrate video caching is considered in [12]- [14], [32]. In [32], a compound QoE model is proposed for the delivery of Dynamic Adaptive Streaming over HTTP (DASH) videos over an orthogonal frequency-division multiplexing access (OFDMA) network. Algorithms for user equipment (UE) rate adaptation and BS resource allocation are developed, along with a stochastic model predictive control (SMPC) scheme to achieve high robustness on video rate adaption.…”

Section: B Adaptive Bitrate Video Cachingmentioning

confidence: 99%

“…In (32), the inequality holds true becauseα p,q i,j are obtained by solving Problem (P1) with the givenx. Similar inequalities can be shown for the bandwidth constraints, as…”

Section: B Linearization and Rounding Algorithmmentioning

confidence: 99%

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Joint Video Caching and Processing for Multi-Bitrate Videos in Ultra-Dense HetNets

Zhang

Mao

2020

IEEE Open J. Commun. Soc.

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Caching popular videos at the edge has been confirmed as a promising way to support low-latency video transmission and alleviate the backhaul traffic burden. Meanwhile, mobile edge computing (MEC) has also been regarded as an effective solution to meet the 5G low-latency service requirements. In this paper, we propose to fully utilize both the storage and computing resources at edge servers to support multiple bitrate video streaming. We design the video caching, processing, and user association models that aim to minimize the average retrieval latency of all users. This problem is modeled as a mixed-integer bilinear problem, which is NP-hard. We show that under practical constraints on storage, bandwidth, and processing capacity, the problem does not exhibit sub-modular property and the performance of a greedy algorithm may not be strictly guaranteed. To deal with this challenging problem, we decompose the original problem into a cache placement problem and a user-BS association problem, while still preserving the interplay between the two sub-problems. A linearization and rounding algorithm, including: (i) a greedy rounding proactively caching scheme and (ii) a random-rounding user-BS association scheme, is then proposed, with performance bounds derived. Extensive simulation results show that the proposed scheme can achieve a near-optimal performance under various storage, computing capacity, and downlink bandwidth settings.Index Terms-Video caching, video transcoding, multiple bitrate video, mobile edge computing (MEC), submodularity.

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