A Novel Traffic Rate Measurement Algorithm for QoE-Aware Video Admission Control

TL;DR

This paper introduces a new algorithm that allows Internet providers to accept more video sessions by intelligently exceeding bandwidth limits without degrading user experience, optimizing QoE and session capacity.

Contribution

A novel traffic rate measurement algorithm that determines the maximum aggregate video rate exceeding bandwidth while maintaining QoE, enhancing session acceptance.

Findings

Accepts more video sessions without QoE degradation

Defines a parameter for exceeding bandwidth limits

Optimizes QoE-Session trade-off

Abstract

With the inevitable dominance of video traffic on the Internet, providing perceptually good video quality is becoming a challenging task. This is partly due to the bursty nature of video traffic, changing network conditions and limitations of network transport protocols. This growth of video traffic has made Quality of Experience (QoE) of the end user the focus of the research community. In contrast, Internet service providers are concerned about maximizing revenue by accepting as many sessions as possible, as long as customers remain satisfied. However, there is still no entirely satisfactory admission algorithm for flows with variable rate. The trade-off between the number of sessions and perceived QoE can be optimized by exploiting the bursty nature of video traffic. This paper proposes a novel algorithm to determine the upper limit of the aggregate video rate that can exceed the available bandwidth without degrading the QoE of accepted video sessions. A parameter $\beta$ that defines the exceedable limit is defined. The proposed algorithm results in accepting more sessions without compromising the QoE of on-going video sessions. Thus it contributes to the optimization of the QoE-Session trade-off in support of the expected growth of video traffic on the Internet.