Flow Admission Control for Users Considering Dissatisfactions With Selection Errors and Loss Using Stochastic Evolutionary Game and Queueing Theory

Currently, streaming communications are widespread through YouTube and other media. Streaming communication focuses on real-time communication and requires flow admission control to ensure communication quality. Many existing studies have solved the system-side problems of streaming communications. However, few have considered user behavior, even though users also use the network. For example, if the selected bandwidth changes due to a selection error made by the user, the network traffic load should also change. However, previous studies have not taken into account the frustration caused by such errors in daily life. In this paper, we first model user bandwidth selection considering selection errors based on stochastic evolutionary game theory. Using the distribution of the derived user bandwidth selection, we propose a flow admission control method based on queueing theory. Furthermore, we define user dissatisfaction using the call loss probability derived by queueing theory, and model selection error behavior using this dissatisfaction. By numerical calculation, we drive the optimal threshold value that results in the highest overall user satisfaction when selection error is taken into account, thereby improving the overall user satisfaction.