An empirical assessment of the use of an algorithm factory for video delivery operations

Gabor Molnar*, Luís Ferreira Pires, Oscar de Boer, Vera Kovaleva

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

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Abstract

Introduction: Video service providers are moving from focusing on Quality of Service (QoS) to Quality of Experience (QoE) in their video networks since the users’ demand for high-quality video content is continually growing. By focusing on QoE, video service providers can provide their subscribers with a more personalized and engaging experience, which can help increase viewer satisfaction and retention. This focus shift requires not only a more sophisticated approach to network management and new tools and technologies to measure and optimize QoE in their networks but also a novel approach to video delivery operations. Methods: This paper describes the components, interactions, and relationships of an algorithm factory for video delivery operation that assures high QoE for video streaming services. The paper also showcases the results of gradually implementing an algorithm factory in the video industry. Using a dataset from 2016 to 2022, we present the case of a European PayTV service provider that achieved improved performance measured by both objective and subjective metrics. Results: The use of an algorithm factory significantly improved the PayTV service provider’s performance. The study found a fivefold increase in the speed of critical incident resolution and a 59% reduction in the number of critical incidents, all while expanding the customer base and maintaining the same level of labor resources. The case also demonstrates a strong positive relation between the productivity measures of the PayTV operator and their survey-based quality ratings. These results underscore the importance of flawless QoS and operational excellence in delivering QoE to meet the evolving demands of viewers. Discussion: The paper adds to the existing literature on relationships between operational efficiency, innovation, and subjective quality. The paper further offers empirical evidence from the PayTV industry. The insights provided are expected to benefit both traditional and over-the-top (OTT) video service providers in their quest to stay ahead in the rapidly evolving video industry. It may also translate to other service providers in similar industries committed to supporting high-quality service delivery.

Original languageEnglish
Article number1281110
Number of pages15
JournalFrontiers in Artificial Intelligence
Volume7
DOIs
Publication statusPublished - 2024

Keywords

  • algorithm factory
  • data mining
  • machine learning
  • QoE
  • QoS
  • video delivery

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