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

Gabor Molnar, Luís Ferreira Pires, Oscar de Boer, Vera Kovaleva
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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.
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对使用算法工厂进行视频传输操作的实证评估
导言:由于用户对高质量视频内容的需求不断增长,视频服务提供商正在将视频网络的重点从服务质量(QoS)转向体验质量(QoE)。通过关注 QoE,视频服务提供商可以为用户提供更加个性化和更具吸引力的体验,从而有助于提高观众的满意度和保留率。这种重点转移不仅需要更先进的网络管理方法和新工具与技术来测量和优化网络中的 QoE,还需要一种新颖的视频传输操作方法。方法 本文介绍了确保视频流服务高 QoE 的视频交付运营算法工厂的组成、互动和关系。本文还展示了在视频行业逐步实施算法工厂的成果。通过使用 2016 年至 2022 年的数据集,我们介绍了一家欧洲付费电视服务提供商的案例,该服务提供商通过客观和主观指标衡量,实现了性能的提升。结果 算法工厂的使用大大提高了付费电视服务提供商的性能。研究发现,关键事件的解决速度提高了五倍,关键事件的数量减少了 59%,所有这些都是在扩大客户群和保持相同劳动力资源水平的情况下实现的。该案例还表明,付费电视运营商的生产率措施与其基于调查的质量评级之间存在很强的正相关关系。这些结果凸显了完美的服务质量和卓越运营在提供 QoE 以满足观众不断变化的需求方面的重要性。讨论 本文补充了有关运营效率、创新和主观质量之间关系的现有文献。本文进一步提供了付费电视行业的经验证据。所提供的见解有望使传统和 OTT 视频服务提供商受益,帮助他们在快速发展的视频行业中保持领先地位。它还可转化为致力于支持提供高质量服务的类似行业的其他服务提供商。
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