Correlation between QoS and QoE for HTTP YouTube content in Orange cellular networks

Moteau, Stephanie; Guillemin, Fabrice; Houdoin, Thierry

doi:10.1109/latincom.2017.8240146

Cited by 4 publications

(4 citation statements)

References 12 publications

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“…Network data is gathered either from network-side traffic traces or directly by user terminals [6]. QoE is obtained either directly through subjective user feedbacks in form of Mean Opinion Scores (MOS), or more often it is substituted by objective QoE metrics such as number of video stalls or buffering ratio [7], the downlink bandwidth or the access Round Trip Time [8], whose correlation to user satisfaction is well established [9]. QoE estimation is generally performed as a supervised classification task: when objective QoE metrics such as video stalls are used, they are quantised into discrete classes.…”

Section: Related Workmentioning

confidence: 99%

Towards Long-Term Coverage and Video Users Satisfaction Prediction in Cellular Networks

Pimpinella

Redondi

Galimberti

et al. 2019

2019 12th IFIP Wireless and Mobile Networking Conference (WMNC)

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Network operators are interested in continuously monitoring the satisfaction of their customers to minimise the churn rate: however, collecting user feedbacks through surveys is a cumbersome task. In this work we explore the possibility of predicting the long-term user satisfaction relative to network coverage and video streaming starting from user-side network measurements only. We leverage country-wide datasets to engineer features which are then used to train several machine learning models. The obtained results suggest that, although some correlation is visible and could be exploited by the classifiers, long-term user satisfaction prediction from network measurements is a very challenging task: we therefore point out possible action points to be implemented to improve the prediction results.

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Section: Related Workmentioning

confidence: 99%

Towards Long-Term Coverage and Video Users Satisfaction Prediction in Cellular Networks

Pimpinella

Redondi

Galimberti

et al. 2019

2019 12th IFIP Wireless and Mobile Networking Conference (WMNC)

View full text Add to dashboard Cite

show abstract

“…The model approximates back-off duration as the function of backoff multiplier, λ, and initial contention window, W. The ith back-off duration Ư(i) is given by the back-off uniform distribution of m attempts out of K maximum attempts (2). The average back-off duration is given by (3).…”

Section: = − ( − ) −mentioning

confidence: 99%

“…TCP drawback is that the acknowledgement and retransmission services inject additional delay, which is often annoying for real-time applications. Some low bit rate applications, such as youtube employ TCP [2], high bit rate application compensates delay by introducing application buffering; however, buffering may be unacceptable for some users [3]. Other transport protocol is user datagram protocol (UDP), which minimizes service delay by limiting the headers and omitting connection-oriented services [4].…”

Section: Introductionmentioning

confidence: 99%

Increasing transmission control protocol speed by reducing the acknowledgement collision probability

Suherman

Rambe

Haris

et al. 2021

IJEECS

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Transmission control protocol (TCP) employs acknowledgement (TCP-ACK) for every transmitted packets to ensure reliable transmission. As a result, it sends the next window packets after receiving the TCP-ACK packet of previous window. This means that the earlier the TCP-ACK packet arrives, the faster the TCP next window transmission and the better the TCP performances. To do so, there should be a special treatment to the transmitted TCP-ACK to fasten next window transmission. This paper proposes a collision probability reduction for the transmitted TCP-ACK packets so that the overall TCP delay reduces. Collision probability reduction can be implemented in many ways. Initially, mathematical analysis is provided to prove that method can work as expected. The mathematic analysis shows that when TCP-ACK collision probability is reduced, the overall TCP delay is also reduced. The proposed method is then implemented in 802.11, 802.16 and complex networks. The NS-2 simulations evaluations for the aforementioned networks and the proposed method proved that collision reductions on TCP-ACK exert average TCP delay reductions about 11.86%, 28.04% and 9.46% subsequently<em>.</em>The proposed method is also applicable for other TCP types.

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“…Subjective, objective, and business parameters were incorporated to evaluate QoE for web‐based over‐the‐top service in Rivera et al Application and network layer QoS parameters were considered to analyze the QoS/QoE quantitative relationships of video streaming and voice service delivered through long term evolution (LTE) network in Vaser and Forconi . Network and VLC media player indicators were used to predict QoE for YouTube streaming in mobile networks in Moteau et al The impact of various playback events on video QoE was analyzed in Nam et al Buffer‐ and media content–related metrics were introduced to enhance the QoE/QoS evaluation systems in Alberti et al Although the prediction accuracy can be improved by taking context and human influence factors into account, the usability of QoE model may be reduced. In research community, it is well known that the QoS parameters measured in networks mainly contribute to user QoE.…”

Section: Related Workmentioning

confidence: 99%

Modular and deep QoE/QoS mapping for multimedia services over satellite networks

Wang

Huang

2018

Int J Communication

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Summary Satellite networks are promising alternatives to deal with the increasing traffic volume and provide universal access for end users. Quality of experience (QoE) as an aggregate of user perception and network quality will be a critical success factor for multimedia service delivery over satellite networks. Quality of experience prediction based on quality of service (QoS) has received much attention recently, but it has been little investigated in satellite networks. In this paper, on the basis of the modular neural network and deep belief networks (DBNs), we design a QoE/QoS mapping method for multimedia services over satellite networks to translate QoS parameters into user QoE. The task of QoE/QoS mapping for multimedia services is decomposed into several different subtasks by using traffic classification. Heterogeneous DBNs are used to learn the mapping relationships between QoE and QoS for different types of services (ie, subtask) simultaneously. An integrative approach based on relative distance is exploited to select subneural network(s) to predict resulting QoE collaboratively. To determine the weight parameters of the QoE/QoS correlation model, the dataset composed of QoS parameters and subjective opinion scores is built on the basis of satellite network simulator and subjective test. Finally, the effectiveness of our QoE/QoS mapping method is validated, and the relationship between adoption rating and opinion scores is analyzed.

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Correlation between QoS and QoE for HTTP YouTube content in Orange cellular networks

Cited by 4 publications

References 12 publications

Towards Long-Term Coverage and Video Users Satisfaction Prediction in Cellular Networks

Towards Long-Term Coverage and Video Users Satisfaction Prediction in Cellular Networks

Increasing transmission control protocol speed by reducing the acknowledgement collision probability

Modular and deep QoE/QoS mapping for multimedia services over satellite networks

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