On QoE monitoring and E2E service assurance in 4G wireless networks

Rengaraju, Perumalraja; Lung, Chung-Horng; Yu, F. Richard; Srinivasan, Anand

doi:10.1109/mwc.2012.6272428

Cited by 35 publications

(21 citation statements)

References 3 publications

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“…3). Some guidelines on QoE/QoS data collection in 4G networks are given in [12]. In this work, the authors propose the integration of active probes within multiple network elements between the service provider's gateway and the access network, for measuring network QoS indicators (e.g.…”

Section: The Qoe-controllermentioning

confidence: 99%

Quality of experience management in mobile cellular networks: key issues and design challenges

et al. 2015

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Section: The Qoe-controllermentioning

confidence: 99%

Quality of experience management in mobile cellular networks: key issues and design challenges

et al. 2015

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“…Basically, existing work can be classified in either concentrating on specific network technologies, e.g., mobile networks like 3G [20], 4G [28], 5G [22], on specific media (e.g., video [32], voice [12]), on specific services like Internet Protocol television (IPTV) [31], Mobile Social Networks (MSN) [6] and YouTube [33], or on the type of service deployment like cloud services [2] or peer-to-peer networks [11]. Also combinations of the aforementioned categories are actively researched, e.g., in [5].…”

Section: Introductionmentioning

confidence: 99%

Towards Internet Scale Quality-of-Experience Measurement with Twitter

Kergl

Roedler

Rodosek

2017

Lecture Notes in Computer Science

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Abstract. At present, Quality of Experience (QoE) measurements are accomplished by interrogating users for the perceived quality of a service they just have used. Influenced by many factors and often limited by domain or geographical region, this technique has several drawbacks when a general state of QoE for the internet as a whole is prospected. To achieve such a general metric, we leverage user complaints that we observe in real-time in social media. Such approaches have been successfully applied for the monitoring of specific and single services. We aim to extend existing methods in order to create an overall metric, define an internet wide QoE baseline, monitor changes and hence, provide a context for assessing smaller scale findings against a ground truth. The contribution of this work is to demonstrate the feasibility of using social media analysis for generating a meaningful value for quantifying the actual QoE of the internet.

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“…As subjective assessments for MOS are This research was supported in part by Atlantic Canada Opportunities Agency (ACOA) and Mariner Partners. impractical during service operation, a QoE model that links MOS to objective QoE factors at different layers [4,5] becomes a viable approach to estimate the user-perceived QoE. Many existing QoE models focus on key performance indicators (KPIs) at the network level (e.g., throughput, packet loss, delay, and jitter).…”

Section: Introduction and Related Workmentioning

confidence: 99%

Bandwidth allocation for video delivery in wireless networks with QoE constraints for spatially random user population

Song

Dong

2015

2015 International Conference on Computing, Networking and Communications (ICNC)

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As video streaming becomes one of the most fast growing and dominant applications in fixed and mobile networks, how to provide high quality and user satisfaction is a widely studied research topic. In this paper, we develop an analytical framework to derive the downloading rate and bandwidth requirement, so that certain objective quality of experience (QoE) constraints are met. Particularly, applicationspecific key performance indicators (KPIs) such as start-up delay and starvation probability are taken into account. Our analysis addresses heterogeneity of both user spatial locations and video requests. Computer simulations are conducted to verify the accuracy of the proposed analytical framework. Based on the analytical framework, a media server can adapt the downloading rate allocation, e.g., relative to the video playback rate, depending on user demands and network conditions. Index Terms-Video streaming, QoE, starvation probability, pre-fetching threshold, download-to-playback rate ratio.

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On QoE monitoring and E2E service assurance in 4G wireless networks

Cited by 35 publications

References 3 publications

Quality of experience management in mobile cellular networks: key issues and design challenges

Quality of experience management in mobile cellular networks: key issues and design challenges

Towards Internet Scale Quality-of-Experience Measurement with Twitter

Bandwidth allocation for video delivery in wireless networks with QoE constraints for spatially random user population

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