Fairness Measurement and Algorithm Design of Network Transmission: A Case Study of Video Applications

Computing-networking integration takes computing as the center and networking as the foundation, connects heterogeneous computing nodes through the network, and realizes the efficient allocation and scheduling of computing-networking resources. The fairness of resource sharing among competing flows is an important research direction of computing-networking integration. As typical scenarios, video applications are becoming more and more important, but little is known about whether and how much they adhere to the fairness principle. Given the highly diversified network environment and the shortage of automated measurement tools, fairness measurement study entails significant challenges. We investigate this problem by measuring the competing behaviors of typical video application (i.e., Zoom), and find that, resource competition behaviors are complex and transient, and Zoom has its own selfish behaviors in different operation scenarios. To take a deep dive into these competitive behaviors, we develop automated tools and conduct measurement to understand its QoE (quality of experience), including end-to-end video/voice delay, video frame rate, and video quality. We discover that the strategies of seizing bandwidth are used by Zoom to ensure its own QoE. In the pursuit of better QoE, Zoom tends to selfishly send excessively redundant packets to cope with abnormal network conditions, some of which are not necessary. To this end, it is important to specify a transport algorithm which is able to balance between QoE and fairness goals. We then present the design of QLibra, and demonstrate that it can effectively ensure the QoE and behave harmlessly to competing flows.