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Applied Sciences
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Optimization of Networked Virtual Environments
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Optimization of Networked Virtual Environments

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Computing and Artificial Intelligence".

Deadline for manuscript submissions: closed (25 January 2022) | Viewed by 5613

Special Issue Editor

Dr. Mirko Sužnjević

E-Mail Website
Guest Editor
Department of Telecommunications, Faculty of Electrical Engineering and Computing, University of Zagreb, 10000 Zagreb, Croatia
Interests: communications technology; quality of experience; multimedia communications; networked virtual environments; networked games; computational and artificial intelligence; computers and information processing

Special Issue Information

Dear Colleagues,

Networked virtual environments (NVE) enable physically distanced users to participate in the shared virtual environment. NVEs have, in the last few decades, become one of the prime mediums for the entertainment industry through multiplayer games. Although social NVEs like Second Life have suffered a steep decline in popularity, the development of virtual reality (VR) headsets and new NVE services based on VR, such as Facebook Horizons, bring new life into this area of NVE application. NVEs are still troubled with multiple issues that degrade its capabilities and perceived quality of experience for its users such as scalability issues, network degradation, adaptability to user-generated content, and so on. Even the most popular NVEs such as today’s biggest subscription-based Massively Multiplayer Online Role-Playing Game (MMORPG) World of Warcraft occasionally suffers from scalability issues due to player load, and still implements significant limitations to gatherings of large numbers of player. Implementation and optimization of player-generated and destroyed content is still a troubling issue for many MMORPGs, although many games have tackled this issue. Novel NVE platforms using virtual reality, augmented reality and remote reality face novel challenges such as positioning and orientation of participants in real time, conveying facial expressions and gesticulation, transporting large amounts of data over the network, and so on. Different approaches for economy systems in NVEs, lately focusing on free-to-play concepts and purchase of virtual goods need to be carefully planned and intervened with the game design. Constant adaptation and optimization based on user behavior testing is a must for the companies in this field today.

Therefore, optimizations of different aspects of virtual environments are an important topic for both academia and industry. Hence, in addition to NVE researchers, game developers and designers, network engineers, as well as economy experts, are asked to contribute with submissions to this Special Issue.

Dr. Mirko Sužnjević
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. Applied Sciences 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

  • scalability mechanisms for NVEs
  • quality of Experience for NVEs
  • novel NVE applications and platforms
  • networked virtual reality, augmented reality and remote reality applications
  • economy systems in NVEs
  • networked games
  • user behavior in NVEs
  • desing, implementation and evaluation of NVEs
  • HCI for NVEs
  • cloud gaming for multiplayer games

Published Papers (1 paper)

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Research

19 pages, 1434 KiB  
Article
Predicting Player Churn of a Free-to-Play Mobile Video Game Using Supervised Machine Learning
by Kuzma Mustač, Krešimir Bačić, Lea Skorin-Kapov and Mirko Sužnjević
Appl. Sci. 2022, 12(6), 2795; https://0-doi-org.brum.beds.ac.uk/10.3390/app12062795 - 09 Mar 2022
Cited by 2 | Viewed by 5075
Abstract
Free-to-play mobile games monetize players through different business models, with higher player engagement leading to revenue increases. Consequently, the foremost goal of game designers and developers is to keep their audience engaged with the game for as long as possible. Studying and modeling [...] Read more.
Free-to-play mobile games monetize players through different business models, with higher player engagement leading to revenue increases. Consequently, the foremost goal of game designers and developers is to keep their audience engaged with the game for as long as possible. Studying and modeling player churn is, therefore, of the highest importance for game providers in this genre. This paper presents machine learning-based models for predicting player churn in a free-to-play mobile game. The dataset on which the research is based is collected in cooperation with a European game developer and comprises over four years of player records of a game belonging to the multiple-choice storytelling genre. Our initial analysis shows that user churn is a very significant problem, with a large portion of the players engaging with the game only briefly, thus presenting a potentially huge revenue loss. Presented models for churn prediction are trained based on varying learning periods (1–7 days) to encompass both very short-term players and longer-term players. Further, the predicted churn periods vary from 1–7 days. Obtained results show accuracies varying from 66% to 95%, depending on the considered periods. Full article
(This article belongs to the Special Issue Optimization of Networked Virtual Environments)
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