Muslin: A QoE‐aware CDN resources provisioning and advertising system for cost‐efficient multisource live streaming

Silva, Simon Da; Bruneau-Queyreix, Joachim; Lacaud, Mathias; Negru, Daniel; Réveillère, Laurent

doi:10.1002/nem.2081

Cited by 5 publications

(3 citation statements)

References 21 publications

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“…They showed MDC increased the performance of DASH applications. In [31], the authors presented a cost-effective DASH system utilizing MS-Stream. In AR/VR applications, when the users move their head and change the viewport, the new viewport data should arrive to the users quickly in order to prevent motion sickness.…”

Section: ) Http Adaptive Streaming Characteristicsmentioning

confidence: 99%

SDN Assisted Codec, Path and Quality Selection for HTTP Adaptive Streaming

Kalan

Sayıt

2021

IEEE Access

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Adaptive streaming over HTTP is the dominant video streaming technology for more than a decade. HTTP Adaptive Streaming (HAS) systems provide a framework which enables clients to adapt quality with respect to network fluctuations during streaming, hence to optimize the perceived quality on the client side. Recently, network assistance is integrated with HAS in order to improve underlying network conditions and to provide network-related information to the clients. The performance of HAS systems can be further enhanced if the characteristics of the streamed video are considered. In this paper, we propose a HAS system architecture where Software Defined Networking (SDN) technology is utilized for assisting clients to select the most appropriate video codec and bitrate under the constraint of current network conditions as well as routing the video packet over the appropriate paths. In the proposed architecture, layered video is used, where each additional layer improves the quality. The controller estimates the packet loss probability by taking video codec characteristics, the bitrates of the layers and network capacity into account. Based on these estimations, the controller selects the appropriate codec type and video quality for the clients and manage the network. Simulation results show that the performance of the video streaming architecture can be improved significantly when codec, quality and path selection are jointly considered, and combined with SDN flexibility and advantageous.

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Section: ) Http Adaptive Streaming Characteristicsmentioning

confidence: 99%

SDN Assisted Codec, Path and Quality Selection for HTTP Adaptive Streaming

Kalan

Sayıt

2021

IEEE Access

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“…Second, traffic generated by video consumption is redundant as the CDN has to stream a popular video as many times as the number of connected players. Thus, it affects the Content Provider (CP)'s Operational Expenditure (OPEX) [4].…”

Section: Introductionmentioning

confidence: 99%

Context-Aware Adaptive Prefetching for DASH Streaming over 5G Networks

Uriol

Yeregui

Gabilondo

et al. 2023

2023 IEEE International Symposium on Broadband Multimedia Systems and Broadcasting (BMSB)

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The increasing consumption of video streams and the demand for higher-quality content drive the evolution of telecommunication networks and the development of new network accelerators to boost media delivery while optimizing network usage. Multi-access Edge Computing (MEC) enables the possibility to enforce media delivery by deploying caching instances at the network edge, close to the Radio Access Network (RAN). Thus, the content can be prefetched and served from the MEC host, reducing network traffic and increasing the Quality of Service (QoS) and the Quality of Experience (QoE). This paper proposes a novel mechanism to prefetch Dynamic Adaptive Streaming over HTTP (DASH) streams at the MEC, employing a Machine Learning (ML) classification model to select the media segments to prefetch. The model is trained with media session metrics to improve the forecasts with application layer information. The proposal is tested with Mobile Network Operators (MNOs)' 5G MEC and RAN and compared with other strategies by assessing cache and player's performance metrics.

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“…The proliferation of CDN vendors and business models allows the CP to use multiple CDN providers simultaneously [7], [8], [9]. However, extreme concurrency dynamics can affect CDN capacity, causing performance degradation and outages, while overestimated demand affects costs, thereby increasing the operational expenditure (OPEX) of the CP [10].…”

Section: Introductionmentioning

confidence: 99%

Predictive CDN Selection for Video Delivery Based on LSTM Network Performance Forecasts and Cost-Effective Trade-Offs

Viola

Martín

Morgade

et al. 2021

IEEE Trans. on Broadcast.

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Owing to increasing consumption of video streams and demand for higher quality content and more advanced displays, future telecommunication networks are expected to outperform current networks in terms of key performance indicators (KPIs). Currently, content delivery networks (CDNs) are used to enhance media availability and delivery performance across the Internet in a cost-effective manner. The proliferation of CDN vendors and business models allows the content provider (CP) to use multiple CDN providers simultaneously. However, extreme concurrency dynamics can affect CDN capacity, causing performance degradation and outages, while overestimated demand affects costs. 5G standardization communities envision advanced network functions executing video analytics to enhance or boost media services. Network accelerators are required to enforce CDN resilience and efficient utilization of CDN assets. In this regard, this study investigates a cost-effective service to dynamically select the CDN for each session and video segment at the Media Server, without any modification to the video streaming pipeline being required. This service performs time series forecasts by employing a Long Short-Term Memory (LSTM) network to process real time measurements coming from connected video players. This service also ensures reliable and cost-effective content delivery through proactive selection of the CDN that fits with performance and business constraints. To this end, the proposed service predicts the number of players that can be served by each CDN at each time; then, it switches the required players between CDNs to keep the (Quality of Service) QoS rates or to reduce the CP's operational expenditure (OPEX). The proposed solution is evaluated by a real server, CDNs, and players and delivering dynamic adaptive streaming over HTTP (MPEG-DASH), where clients are notified to switch to another CDN through a standard MPEG-DASH media presentation description (MPD) update mechanism.

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Muslin: A QoE‐aware CDN resources provisioning and advertising system for cost‐efficient multisource live streaming

Cited by 5 publications

References 21 publications

SDN Assisted Codec, Path and Quality Selection for HTTP Adaptive Streaming

SDN Assisted Codec, Path and Quality Selection for HTTP Adaptive Streaming

Context-Aware Adaptive Prefetching for DASH Streaming over 5G Networks

Predictive CDN Selection for Video Delivery Based on LSTM Network Performance Forecasts and Cost-Effective Trade-Offs

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