Enhancing QoE for Video Streaming Considering Congestion: A Fault Tolerance Approach

Since tremendous amount of traffic is generated in modern networks as a result of the mobile devices and video streaming, the congestion issue is faced more frequently in the networks. Accordingly, failures and performance losses in networks due to congestion result in deteriorated Quality of Experience (QoE) from the end user perspective that may cause financial and reputation loss for the service provider. Even though the new video streaming paradigm, Dynamic Adaptive Streaming over HTTP (DASH), is proposed as a solution for the changing condition of the networks, it is not sufficient considering the heavily loaded links that show the symptoms of link failures. Therefore, the flexible implementation of the data plane fault tolerance scheme that can be applied for other problems like congestion in networks is crucial. Thus, in this study, we apply the data plane fault tolerance approach in the Software-Defined Network to improve the QoE of DASH clients in the case of congestion rather than the failure. To detect the congestion in the network level, we use the Bidirectional Forwarding Protocol (BFD) that is originally implemented for link failures. In our experiments, we investigate the effect of the BFD interval, video segment size, and traffic load on QoE parameters. Our results show that if the fault tolerance approach is applied using a small BFD interval with a large segment size, QoE parameters are noticeably enhanced considering the non-applied case.