Quality of experience for unified communications: A survey

Husić, Jasmina Baraković; Baraković, Sabina; Cero, Enida; Slamnik, Nina; Oćuz, Merima; Dedović, Azer; Zupčić, Osman

doi:10.1002/nem.2083

Cited by 21 publications

(11 citation statements)

References 103 publications

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“…There are also several studies that addressed the impact of various factors on QoE in services similar to audiovisual teleconferences, such as unified communications [ 5 ], video consultations [ 32 ], or video streaming [ 3 ].…”

Section: Related Workmentioning

confidence: 99%

Survey on user perceived system factors influencing the QoE of audiovisual calls on smartphones

Vucic

Baraković

Skorin‐Kapov

2022

Multimed Tools Appl

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With the widespread use of applications and services supporting audiovisual calls via smartphones, both in business and leisure contexts, a key challenge for service providers is meeting end user Quality of Experience (QoE) expectations and requirements. To successfully meet this challenge, there is a need to identify and analyze the key system-related factors impacting user perceived quality. In this paper, we contribute beyond state-of-the-art by conducting a large scale web-based questionnaire survey to investigate the system-related factors that subjects identify as most influential in contributing to their overall experience and quality perception. We focus in particular on leisure audiovisual calls, established via mobile devices. Our initial survey (Phase 1) was conducted in Feb. 2020, just prior to the outbreak of the COVID-19 pandemic (272 participants). To investigate if the importance of factors has changed due to increased usage of the service caused by the pandemic among the general population, we conducted a second survey (Phase 2) in October 2021 with 249 participants. Based on obtained results, we identify key system-related QoE influence factors belonging to three categories: media quality, functional support, and usability and service design. We observe no significant differences in user opinions and expectations prior to and during the period of increased service usage, despite different participant demographics and study time frames, thus contributing to generalizability of obtained results. Study results contribute to providing insights for designing future user studies investigating QoE, in terms of key factors that should be considered.

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Section: Related Workmentioning

confidence: 99%

Survey on user perceived system factors influencing the QoE of audiovisual calls on smartphones

Vucic

Baraković

Skorin‐Kapov

2022

Multimed Tools Appl

Self Cite

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“…Generally speaking, there are three classes of impact factors (or IFs) that affect the QoE of service delivery [28,68,74]: human, context, and system. The first relates to what can be called the demographic composite that makes the user.…”

Section: Causal Inferencementioning

confidence: 99%

Quality of Experience in 6G Networks: Outlook and Challenges

Taha

2021

JSAN

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In this paper, we discuss the critical characteristics of user experience in sixth generation (6G) cellular networks. We first describe cellular networks’ evolution through 5G and then discuss the enabling technologies and projected services in 6G networks. We note that these networks are markedly centered around expanded intelligence, end-to-end resource and topology synchronization, and the intrinsic support to low-latency, high-bandwidth communication. These capabilities make context-rich, cyberphysical user experiences viable. It thereby becomes necessary to define and identify the role of quality of experience in 6G networks, especially when it comes to network management. We elaborate on these expected challenges and allude to viable opportunities in emerging technologies.

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“…Based on their results, they designed QoE estimation model. The survey in Reference 29 presents an overview of the QoE studies that covers adaptive video streaming from human interaction and network domain and discusses correspondence between QoE models and factors influencing HAS.…”

Section: Related Workmentioning

confidence: 99%

QoE‐aware traffic monitoring based on user behavior in video streaming services

Laiche

Letaïfa

Aguili

2021

Concurrency and Computation

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In recent years, online video content has gained a lot of popularity and the exponential growth of video traffic continues in every area of the connected world. Thus, understanding the quality of experience (QoE) perceived by end-users of video streaming services is important for both network operators and over the top providers since estimating end user's QoE has become one of the main points to meet user expectations. However, it is not trivial to ensure an adequate QoE since user experience is affected by various influencing factors (e.g., context factors, human factors, and system factors), and it is still challenging to identify the QoE key influencing factors. To address these challenges, we focused on improving QoE estimation and management strategies by exploiting valuable human and context information because the influence of social contextual information and user behavior on the perceptual quality is often neglected.In this article, we first proposed a classification of influence factors into four categories which are: system factors, human factors, context factors, and social-behavioral factors. We developed a monitoring web application where video content is played to end-users so that subjective and objective video metrics are collected. We built a new machine learning (ML) based model for QoE prediction. We used well-known supervised ML algorithms like decision tree, k-nearest neighbors, and support vector machine. Finally, we proposed a QoE management approach in the context of software defined network/multi-access edge computing that implements the proposed QoE prediction model to optimize the video delivery transmission chain.

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Quality of experience for unified communications: A survey

Cited by 21 publications

References 103 publications

Survey on user perceived system factors influencing the QoE of audiovisual calls on smartphones

Survey on user perceived system factors influencing the QoE of audiovisual calls on smartphones

Quality of Experience in 6G Networks: Outlook and Challenges

QoE‐aware traffic monitoring based on user behavior in video streaming services

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