Representation selection problem: Optimizing video delivery through caching

Araldo, Andrea; Martignon, Fabio; Rossi, Dario

doi:10.1109/ifipnetworking.2016.7497212

Cited by 21 publications

(21 citation statements)

References 17 publications

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“…Note that the constraints in (12) guarantee that the probability of a helper storing any version of video n cannot exceed 1. The constraint in (13) guarantees that the average occupied storage at each helper cannot exceed the cache size C. Therefore, Problem 1 can be relaxed to the following one. bound for that of Problem 1, i.e., q * SVC ≤ q * SVC,ub .…”

Section: ) Near Optimal Solutionmentioning

confidence: 99%

“…The decoding of a description is independent of that of any other description [12]. In [13], the authors consider joint optimization of caching and routing for DASH-based videos to maximize the overall user utility in a simple network model. In [14], the authors analyze and optimize the performance of random caching for DASH-based videos in a large-scale wireless network.…”

Section: Introductionmentioning

confidence: 99%

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Analysis and Optimization of Caching and Multicasting for Multi-Quality Videos in Large-Scale Wireless Networks

Jiang

Cui

2019

IEEE Trans. Commun.

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Efficient dissemination of videos is an important problem for mobile telecom carriers. In this paper, to facilitate massive video dissemination, we study joint caching and multicasting for multi-quality videos encoded using two video encoding techniques, namely scalable video coding (SVC), and HEVC or H.264 as in dynamic adaptive streaming over HTTP (DASH) respectively, in a large-scale wireless network. First, for each type of videos, we propose a random caching and multicasting scheme, carefully reflecting the relationship between layers of an SVC-based video or descriptions of a DASH-based video.Then, for each type of videos, we derive tractable expressions for the successful transmission probability in the general and high user density regions, respectively, utilizing tools from stochastic geometry. The analytical results reveal that in the high user density region, the marginal increase of the successful transmission probability with respect to the caching probability of a video with a certain quality reduces when the caching probability increases. Next, for each type of videos, we consider the maximization of the successful transmission probability in the high user density region, which is a convex problem with an exceedingly large number of optimization variables. We propose a two-stage optimization method to obtain a low-complexity near optimal solution by solving a relaxed convex problem and a related packing problem. The optimization results reveal the impact of the caching gain of a layer for an SVCbased video or a description for a DASH-based video on its caching probability. Finally, we show that the proposed solutions for SVC-based and DASH-based videos achieve significant performance gains over baseline schemes in the general and high user density regions, and demonstrate their respective operating regions, using numerical results based on real video sequences. Index TermsCache, multicast, multi-quality video, scalable video coding, dynamic adaptive streaming over HTTP, stochastic geometry, optimization.

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Section: ) Near Optimal Solutionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Analysis and Optimization of Caching and Multicasting for Multi-Quality Videos in Large-Scale Wireless Networks

Jiang

Cui

2019

IEEE Trans. Commun.

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“…Also, R n (α n (t), t) and L(q n (α n (t), i n ), t) indicate the data rate of a D2D link between user n and the device α n (t), and a chunk size of file i n of the desired quality q n (α n (t), i n ) at time t, respectively. Some video chunks can be only partially delivered as the channel condition varies and node association is updated at every time slot t. Since partial chunk transmission is meaningless in our algorithm, the flooring is used in (24). Let the Rayleigh fading channel between user n and device α n (t) denoted by h n,t .…”

Section: A User Queue Modelmentioning

confidence: 99%

“…For example, consider a user whose queue is filled with many chunks and thus is associated with the caching device delivering the chunks smaller than b n [t] = m. If this situation persists for a long time, chunks in the queue will be emptied out soon and playback delay will occur, therefore several updates of node association are required over the time interval of τ c . On the other hand, if τ c is too short, the requested video cannot be successfully delivered even when the data rate of the link is good, because of the flooring in (24). Therefore, block fading is assumed with τ c large enough for the users to receive the video chunks.…”

Section: A User Queue Modelmentioning

confidence: 99%

“…Many researchers have proposed the static file placement policies under the arXiv:1806.01594v1 [cs.NI] 5 Jun 2018 consideration of differentiated quality requests for the same file, given probabilistic quality requests [12], [22], [23] or minimum quality requirements [21]. In [24], joint optimization of the static file placement and routing is proposed. Further, the probabilistic caching policy for video files of various quality levels is presented in [25] by using stochastic geometry, given the user preference for quality level.…”

Section: Introductionmentioning

confidence: 99%

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Wireless Video Caching and Dynamic Streaming Under Differentiated Quality Requirements

Choi

Kim

Moon

2018

IEEE J. Select. Areas Commun.

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This paper considers one-hop device-to-device (D2D)-assisted wireless caching networks that cache video files of varying quality levels, with the assumption that the base station can control the video quality but cache-enabled devices cannot. Two problems arise in such a caching network: file placement problem and node association problem. This paper suggests a method to cache videos of different qualities, and thus of varying file sizes, by maximizing the sum of video quality measures that users can enjoy. There exists an interesting trade-off between video quality and video diversity, i.e., the ability to provision diverse video files. By caching high-quality files, the cacheenabled devices can provide high-quality video, but cannot cache a variety of files. Conversely, when the device caches various files, it cannot provide a good quality for file-requesting users. In addition, when multiple devices cache the same file but their qualities are different, advanced node association is required for file delivery. This paper proposes a node association algorithm that maximizes time-averaged video quality for multiple users under a playback delay constraint. In this algorithm, we also consider request collision, the situation where several users request files from the same device at the same time, and we propose two ways to cope with the collision: scheduling of one user and non-orthogonal multiple access. Simulation results verify that the proposed caching method and the node association algorithm work reliably.

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Performance Comparison of Transcoding and Bitrate-Aware Caching in Adaptive Video Streaming

Oteafy

Hassanein

2019

ICC 2019 - 2019 IEEE International Conference on Communications (ICC)

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Representation selection problem: Optimizing video delivery through caching

Cited by 21 publications

References 17 publications

Analysis and Optimization of Caching and Multicasting for Multi-Quality Videos in Large-Scale Wireless Networks

Analysis and Optimization of Caching and Multicasting for Multi-Quality Videos in Large-Scale Wireless Networks

Wireless Video Caching and Dynamic Streaming Under Differentiated Quality Requirements

Performance Comparison of Transcoding and Bitrate-Aware Caching in Adaptive Video Streaming

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