## 2 The Proposed Video QoE Metric for Dynamic Adaptive Streaming Services
### Study of Factors Influencing QoE Based on the DASH Standard  
According to the DASH standard, a video is encoded at different bitrates, and each video bitstream is separated into chunks and a Media Presentation Description (MPD) is generated in binary extensible markup language format. The MPD file describes the information corresponding to a video, URL address and the segment format list of the video chunk, such as the encoding bitrate, resolution and length of a video, and is stored on the server. The client selects the most suitable video bitstream to download on the basis of current network condition, the processing capability of the hardware, and the cache status to improve a user's QoE. DASH-based video transmission may cause two kinds of distortion-video quality switching and stalling, leading to fluctuations in video quality and disfluency of the video, which seriously affect users' QoE. The following parameters are used for quantifying various influencing factors of QoE based on the DASH standard. * Video quality  
(1) Average bitrate of video. The video encoding bitrate directly affects the reconstructed quality of a video. The higher the video bitrate, the better the quality of the video. In this paper, DASH standard method is used to extract the video bitrate, and the average value of bitrate is calculated to express the average level of video quality. Here, \(Avg_{n}\) represents the average bitrate of the \(n\)th chunk. For the \((n+1)^{\text{th}}\) chunk, the average bitrate \(Avg_{n+1}\) is calculated using the following formula:  
\[Avg_{n+1}=\frac{n*Avg_{n}+Bitrate_{n+1}}{n+1} \tag{2}\]  
(2) The frequency of each video quality level. This is used to represent the frequency of each video quality level appears in a video, which can be calculated as:  
\[P_{i}=\frac{B_{i}}{N} \tag{3}\]  
where \(B_{i}\) represents the number of \(i^{\text{th}}\) video quality level in a video, \(N\) is the number of segments of a video. Each segment is encoded with a bit rate, corresponding to a quality level. * Fluency of a video  
(1) Video frame rate. This refers to the frames per second and can be used to indicate the fluency of video playback. (2) Re-buffering times and duration. When the network conditions change drastically, the bandwidth fluctuations, bit errors and other factors often lead to interruption in the process of video playback and re-buffering. This is one of the major factors that heavily affect the QoE. A research conducted by Amazon shows that frequent re-buffering reduces the user's interest in watching videos by approximately 39% [22]. In this paper, the re-buffering time is counted to exhibit the impact of network conditions on QoE. While watching a video online, the total duration of the video is divided into the following segments: The original video duration, initial buffering time and re-buffering time. The average re-buffering time \(t_{\mathit{stallingP}}\) is denoted as:  
\[t_{\mathit{stallingP}}=\frac{t_{\mathit{stalling}}}{t_{\mathit{original}}+t_{ \mathit{stalling}}+t_{\mathit{initial}}} \tag{4}\]  
where \(t_{\mathit{stalling}}\), \(t_{\mathit{original}}\) and \(t_{\mathit{initial}}\) represent stalling time, original video time and initial buffering time, respectively. (3) Initial buffering time. This indicates the time taken by a client for requesting a video for playback from the server. Initial buffering time is decided by video chunk size, network status and client attributes, separately. It is one of the most crucial factors that affect the QoE and is regarded as a key factor in this paper. * Fluctuation of a video quality  
(1) Switching times of video bitrate. The DASH standard adaptively selects the video bitrate on the basis of the network conditions and client buffering status to mitigate the impact of dynamic changes in network conditions on QoE. Frequent switching of bitrate will lead to fluctuation in the quality of a video.