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

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.

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