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Electronics
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Quality-of-Experience (QoE) or Quality-of-Service (QoS) in Emerging Networks
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Quality-of-Experience (QoE) or Quality-of-Service (QoS) in Emerging Networks

A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Networks".

Deadline for manuscript submissions: closed (15 December 2024) | Viewed by 6944

Special Issue Editor

Dr. Ricky K. P. Mok

E-Mail Website
Guest Editor
CAIDA, University of California, San Diego, CA 92093, USA
Interests: QoE measurement; internet path quality measurement; HTTP video streaming systems; internet infrastructure security; darknet traffic analysis

Special Issue Information

Dear Colleagues,

Over the past three decades, extensive research has been devoted to understanding and enhancing quality-of-service (QoS) parameters across network layers, encompassing network, application, and service realms. This endeavor, driven by a desire to elevate user-perceived quality—commonly referred to as quality of experience (QoE)—has witnessed significant strides.

Diverging from the objective and quantifiable nature of QoS, the measurement and estimation of QoE present a unique challenge owing to its inherently subjective character. Despite substantial advancements in QoE research, the evolution of network environments, exemplified by the advent of cloud computing, 6G technology, and immersive applications, has introduced novel complexities to the measurement and optimization of both QoS and QoE.

Simultaneously, the rapid proliferation of machine learning (ML) and artificial intelligence (AI) techniques offers a promising avenue with which to address these intricate challenges. The deployment of ML/AI models holds the potential to unravel complex problems associated with QoS and QoE in this evolving technological landscape.

This Special Issue aspires to curate a compendium of cutting-edge research, unveiling new perspectives on theories, methodologies, and applications of ML/AI in the quest to measure, evaluate, and optimize the QoS and/or QoE of networks and applications.

In this Special Issue, original research articles and reviews are welcome. Research areas may include (but are not limited to) the following topics:

  • Artificial intelligence for QoS/QoE
  • QoS/QoE for data analytics and machine learning
  • QoS/QoE in software-defined networking
  • QoS/QoE in mobile and next-generation cellular networks
  • QoS/QoE in immersive communications (immersive XR, remote multi-sensory telepresence, and holographic communications)
  • Audio/visual/multimedia user experience
  • QoE datasets
  • Novel QoS/QoE measurement, assessment and evaluation methods
  • Crowdsourcing-based QoE measurements
  • Sustainability in/through QoE research
  • Architectures and protocols for QoS/QoE support

I look forward to receiving your contributions.

Dr. Ricky K. P. Mok
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Electronics is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • QoS
  • QoE
  • measurements
  • multimedia
  • immersive technologies
  • 5G/6G
  • cloud
  • mobile
  • video streaming
  • crowdsourcing

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Published Papers (3 papers)

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Research

30 pages, 6929 KiB  
Article
Global Quality of Service (QoX) Management for Wireless Networks
by Leire Cristobo, Eva Ibarrola, Itziar Casado-O’Mara and Luis Zabala
Electronics 2024, 13(16), 3113; https://doi.org/10.3390/electronics13163113 - 6 Aug 2024
Cited by 2 | Viewed by 1896
Abstract
In the fast-changing technological landscape, novel applications are emerging with the potential to reshape the world. These applications, while promising, impose stringent requirements in terms of quality of service (QoS). The advent of wireless networks like 5G, 6G and Wi-Fi 6 brings about [...] Read more.
In the fast-changing technological landscape, novel applications are emerging with the potential to reshape the world. These applications, while promising, impose stringent requirements in terms of quality of service (QoS). The advent of wireless networks like 5G, 6G and Wi-Fi 6 brings about resource management solutions to ensure these requirements while meeting the user expectations within the interconnected environment. Nevertheless, user behaviors are also evolving, highlighting the importance of satisfaction and quality of experience (QoE). Furthermore, changes in user behavior trigger shifts in business models, where the quality of business (QoBiz) takes on a pivotal role. This evolving ecosystem, encompassing QoS, QoE, and QoBiz, demands a comprehensive and adaptable approach that conventional QoS management frameworks fail to perform. This paper introduces an implementation methodology for a global QoS management model named QoXphere. The implementation methodology is grounded in machine learning techniques and addresses the multifaceted aspects of quality of service (QoX) and their interconnections within wireless networks. The objective is to facilitate dynamic resource management that not only elevates user satisfaction but also optimizes provider benefits. Real-world examples illustrate the methodology’s applicability in widely deployed networks, complemented by simulated scenarios of modern network environments that further validate the approach. Full article
(This article belongs to the Special Issue Quality-of-Experience (QoE) or Quality-of-Service (QoS) in Emerging Networks)
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21 pages, 1453 KiB  
Article
Quality of Experience That Matters in Gaming Graphics: How to Blend Image Processing and Virtual Reality
by Awais Khan Jumani, Jinglun Shi, Asif Ali Laghari, Vania V. Estrela, Gabriel Avelino Sampedro, Ahmad Almadhor, Natalia Kryvinska and Aftab ul Nabi
Electronics 2024, 13(15), 2998; https://doi.org/10.3390/electronics13152998 - 30 Jul 2024
Cited by 6 | Viewed by 2307
Abstract
This paper investigates virtual reality (VR) technology which can increase the quality of experience (QoE) on the graphics quality within the gaming environment. The graphics quality affects the VR environment and user experience. To gather relevant data, we conduct a live user experience [...] Read more.
This paper investigates virtual reality (VR) technology which can increase the quality of experience (QoE) on the graphics quality within the gaming environment. The graphics quality affects the VR environment and user experience. To gather relevant data, we conduct a live user experience and compare games with high- and low-quality graphics. The qualitative feedback obtained through questionnaires prove the importance ofcontextualizing users’ experiences playing both games. Furthermore, our findings prove the crucial role of graphics quality in adopting user engagement and enjoyment during gaming sessions. Users consistently reported their feeling more connected when interacting with games and receiving high-quality graphics. If the graphics quality received is low, the user rating for a particular game is low. Further examination of VR technology reveals its potential to revolutionize graphics quality within game play. Full article
(This article belongs to the Special Issue Quality-of-Experience (QoE) or Quality-of-Service (QoS) in Emerging Networks)
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17 pages, 4019 KiB  
Article
QoE-Based Performance Comparison of AVC, HEVC, and VP9 on Mobile Devices with Additional Influencing Factors
by Omer Nawaz, Markus Fiedler and Siamak Khatibi
Electronics 2024, 13(2), 329; https://doi.org/10.3390/electronics13020329 - 12 Jan 2024
Cited by 3 | Viewed by 2079
Abstract
While current video quality assessment research predominantly revolves around resolutions of 4 K and beyond, targeted at ultra high-definition (UHD) displays, effective video quality for mobile video streaming remains primarily within the range of 480 p to 1080 p. In this study, we [...] Read more.
While current video quality assessment research predominantly revolves around resolutions of 4 K and beyond, targeted at ultra high-definition (UHD) displays, effective video quality for mobile video streaming remains primarily within the range of 480 p to 1080 p. In this study, we conducted a comparative analysis of the quality of experience (QoE) for widely implemented video codecs on mobile devices, specifically Advanced Video Coding (AVC), its successor High-Efficiency Video Coding (HEVC), and Google’s VP9. Our choice of 720 p video sequences from a newly developed database, all with identical bitrates, aimed to maintain a manageable subjective assessment duration, capped at 35–40 min. To mimic real-time network conditions, we generated stimuli by streaming original video clips over a controlled emulated setup, subjecting them to eight different packet-loss scenarios. We evaluated the quality and structural similarity of the distorted video clips using objective metrics, including the Video Quality Metric (VQM), Peak Signal-to-Noise Ratio (PSNR), Video Multi-Method Assessment Fusion (VMAF), and Multi-Scale Structural Similarity Index (MS-SSIM). Subsequently, we collected subjective ratings through a custom mobile application developed for Android devices. Our findings revealed that VMAF accurately represented the degradation in video quality compared to other metrics. Moreover, in most cases, HEVC exhibited an advantage over both AVC and VP9 under low packet-loss scenarios. However, it is noteworthy that in our test cases, AVC outperformed HEVC and VP9 in scenarios with high packet loss, based on both subjective and objective assessments. Our observations further indicate that user preferences for the presented content contributed to video quality ratings, emphasizing the importance of additional factors that influence the perceived video quality of end users. Full article
(This article belongs to the Special Issue Quality-of-Experience (QoE) or Quality-of-Service (QoS) in Emerging Networks)
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