It can be challenging to stream video or items that require adequate screen parameters to be displayed well, but solutions exist. Hypertext transfer protocol (HTTP) adaptive streaming (HAS) is one way to produce different versions of the same item to be displayed on different user devices, for example, mobile phones, tablets, desktop computers, and so on. HAS takes into account the quality of the user’s Internet connection and adapts in order to stream the requested material.
This paper tackles an important issue of HAS, namely the user’s quality of experience (QoE) in an age of high Internet traffic. The authors point out factors that affect QoE in the context of games of streaming players, and further indicate that users are responsible for the QoE level because they are ignorant of how HAS works. Users do not care about each other and choose the maximum bitrate when retrieving material. The authors figure out that this issue is more exacerbated when concerned users are game players.
The paper, therefore, proposes a distributed network-sharing approach, called distributed game theory, and a consensus-based collaborative adaptive bitrate solution.
I appreciate the paper’s structure and writing style. It has the advantage of reading much like chapter text; at the same time, it provides support for researchers and application developers working in the field. The authors succinctly present the issues and thoroughly define each term. It is worth noting, however, that many sections are intended for readers with a strong mathematics background.
The paper provides a solution approach to an issue that game players regularly face. It also contributes to the literature. I therefore highly recommend it to researchers working on network and data exchanges, QoE and video gaming, or networked applications such as telemedicine that require high-quality video materials. Furthermore, this study will help multiplatform-based and networking application developers design and implement optimal applications.
I can imagine how beneficial this work will be for applications like telesurgery or real-time traffic monitoring that run on poor network resources. Telesurgery, for example, can benefit from the distributed network-sharing approach and consensus-based collaborative adaptive bitrate solution in cases where several medical experts located at different places are working on the same thing at the same time using a poor resource network. They can use the consensus approach judiciously to share the network resources for streaming high-quality video at each system endpoint.