Improving QoE and Fairness in HTTP Adaptive Streaming Over LTE Network

Cicalo, Sergio; Changuel, Nesrine; Tralli, V.; Sayadi, Bessem; Faucheux, Frederic; Kerboeuf, Sylvaine

doi:10.1109/tcsvt.2015.2504732

Cited by 33 publications

(20 citation statements)

References 41 publications

(65 reference statements)

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“…MANE, proposed in [19], achieves fair playout buffer levels among HAS clients competing for same wireless resources by allocating radio resources according to video content characteristics, playout buffer levels and channel conditions. However, as in SAP, MANE also does not provide a means to control number of quality switches in adaptive video streams.…”

Section: B Related Workmentioning

confidence: 99%

“…However, as in SAP, MANE also does not provide a means to control number of quality switches in adaptive video streams. The system architecture proposed in [19] requires MANE to be located close to eNodeBs (eNBs), and requires Channel State Information (CSI) updates from eNBs. Based on these updates, it sets up rate values, i.e., Guaranteed bitrate (GBRs), that eNBs will try to guarantee to their associated clients.…”

Section: B Related Workmentioning

confidence: 99%

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Enforcing Bitrate-Stability for Adaptive Streaming Traffic in Cellular Networks

Sunny

El-Azouzi

Arfaoui

et al. 2019

IEEE Trans. Netw. Serv. Manage.

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Video streaming over cellular network has become extremely popular in 4G and will be an integral part of future cellular networks. While most modern-day video clients continually adapt quality of the video stream, they neither coordinate with the network elements nor among each other. Consequently, a streaming client may quickly overload the cellular network, leading to poor Quality of Experience (QoE) for the users in the network. Motivated by this problem, we present D-VIEWS -a scheduling paradigm that assures video bitrate stability of adaptive video streams while ensuring better system utilization. D-VIEWS only needs to be aware of the set of video bitrates and requires no changes to the streaming client and other network functions. We also study, through simulations, the performance of proportional fairness scheduler and D-VIEWS in the presence of user arrival and departure events.

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Section: B Related Workmentioning

confidence: 99%

Section: B Related Workmentioning

confidence: 99%

Enforcing Bitrate-Stability for Adaptive Streaming Traffic in Cellular Networks

Sunny

El-Azouzi

Arfaoui

et al. 2019

IEEE Trans. Netw. Serv. Manage.

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“…The solutions proposed in [28] and [29] employed an adaptive streaming solution to obtain high QoE for users in a fair manner based on the network conditions. However, most of them do not consider either user QoE or the energy consumption of mobile devices in the wireless environment.…”

Section: Fairness Issuesmentioning

confidence: 99%

E³DOAS: Balancing QoE and Energy-Saving for Multi-Device Adaptation in Future Mobile Wireless Video Delivery

Zou

Trestian

Muntean

2018

IEEE Trans. on Broadcast.

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Abstract-Smart devices (e.g. smartphones, tablets, smarthome devices, etc.) have become important companions to most people in their daily activities, and are very much used for multimedia content exchange (i.e. video sharing, real-time/nonreal-time multimedia streaming), contributing to the exponential increase in mobile traffic over the current wireless networks. While the next generation mobile networks will provide higher capacity than the current 4G systems, the network operators will face important challenges associated with the outstanding increase of both video traffic and user expectations in terms of their levels of perceived quality or Quality of Experience (QoE). Furthermore, the heterogeneity of mobile devices (e.g. screen resolution, battery life, hardware performance) also impacts severely the end-user QoE. In this context, this paper proposes an Evolved QoE-aware Energy-saving Device-Oriented Adaptive Scheme (E 3 DOAS ) for mobile multimedia delivery over future wireless networks. E 3 DOAS makes use of a coalition gamebased rate allocation strategy within the multi-device heterogeneous environment, and optimizes the trade-off between the end-user perceived quality of the multimedia delivery and the mobile device energy-saving. Testing has involved a prototype of E 3 DOAS , a crowd-sourcing-based QoE assessment method to model non-reference perceptual video quality, and an energy measurement testbed introduced to collect power consumption parameters of the mobile devices. Simulation-based performance evaluation showed how E 3 DOAS outperformed other state of the art multimedia adaptive solutions in terms of energy saving, endto-end Quality of Service (QoS) metrics and end-user perceived quality.

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“…In [53] and [54], the authors have identified three main performance issues: (i) player instability, (ii) unfairness between the players and (iii) the under-utilization of the available bandwidth. It is pointed out that the main cause of these [31], [32], [34], [59] × × × × × [37], [35] ×…”

Section: B Client-side Approachesmentioning

confidence: 99%

Optimal Network-Assisted Multiuser DASH Video Streaming

Ozfatura

Erçetin

İnaltekin

2018

IEEE Trans. on Broadcast.

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Streaming video is becoming the predominant type of traffic over the Internet with reports forecasting the video content to account for 82% of all traffic by 2021. With significant investment on Internet backbone, the main bottleneck remains at the edge servers (e.g., WiFi access points, small cells, etc.). In this work, we obtain and prove the optimality of a multiuser resource allocation mechanism operating at the edge server that minimizes the probability of stalling of video streams due to buffer underflows. Our derived policy utilizes Media Presentation Description (MPD) files of clients that are sent in compliant to Dynamic Adaptive Streaming over HTTP (DASH) protocol to be cognizant of the deadlines of each of the media file to be displayed by the clients. Our policy allocates the available channel resources to the users, in a time division manner, in the order of their deadlines. After establishing the optimality of this policy to minimize the stalling probability for a network with links associated with fixed loss rates, the utility of the algorithm is verified under realistic network conditions with detailed NS-3 simulations. Index TermsMPEG-DASH, rebuffer, buffer starvation, quality of experience, dynamic programming, HTTP adaptive streaming (HAS). I. INTRODUCTIONT HERE is an increasing demand for multimedia streaming applications thanks to the ubiquity of internet access, the availability of the online content and the growing number of wireless hand-held devices. The predictions of Cisco Visual Networking Index [1] indicate that IP video traffic will constitute 82 percent of all consumer internet traffic by 2021. For instance, in 2016, YouTube and Netflix account for up to 53 percent of fixed access Internet traffic in North America [2]. Moreover, 21 percent of the mobile internet traffic in North America is solely based on YouTube [2].In this work, we derive a Dynamic Adaptive Streaming over HTTP (DASH)-compatible multiuser resource control policy, which we call blind deadline-based resource allocation (BDRA) scheme, operating at an edge server. The aim of the BDRA scheme is to perform slot-based resource allocation to users in order to minimize the probability of a stalling event at a client. When the amount of data at the buffer of a client is insufficient to continue to display the video stream, a stalling event occurs, and the client begins a re-buffering period during which it fills its buffer without displaying the video stream. The BDRA scheme utilizes Media Presentation Description (MPD) files of clients and HTTP-GET requests, which are sent in compliant to DASH protocol, in order to define and update the deadline of each media file displayed by a client. Then, it allocates slots to E. Ozfatura is with the

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Improving QoE and Fairness in HTTP Adaptive Streaming Over LTE Network

Cited by 33 publications

References 41 publications

Enforcing Bitrate-Stability for Adaptive Streaming Traffic in Cellular Networks

Enforcing Bitrate-Stability for Adaptive Streaming Traffic in Cellular Networks

E³DOAS: Balancing QoE and Energy-Saving for Multi-Device Adaptation in Future Mobile Wireless Video Delivery

Optimal Network-Assisted Multiuser DASH Video Streaming

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Improving QoE and Fairness in HTTP Adaptive Streaming Over LTE Network

Cited by 33 publications

References 41 publications

Enforcing Bitrate-Stability for Adaptive Streaming Traffic in Cellular Networks

Enforcing Bitrate-Stability for Adaptive Streaming Traffic in Cellular Networks

E3DOAS: Balancing QoE and Energy-Saving for Multi-Device Adaptation in Future Mobile Wireless Video Delivery

Optimal Network-Assisted Multiuser DASH Video Streaming

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Product

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E³DOAS: Balancing QoE and Energy-Saving for Multi-Device Adaptation in Future Mobile Wireless Video Delivery