Progressive download video services, such as YouTube and podcasts, are responsible for a major part of the transmitted data volume in the Internet and it is expected, that they will also strongly affect mobile networks. Streaming video quality mainly depends on the sustainable throughput achieved during transmission. To ensure acceptable video quality in mobile networks (with limited capacity resources) the perceived quality by the customer (QoE) needs to be monitored by estimation. For that, the streaming video quality needs to be measured and monitored permanently. For TCP based progressive download we propose to extract the the video timestamps which are encoded within the payload of the TCP segments by decoding the video within the payload. The actual estimation is then done by play out buffer fill level calculations based on the TCP segment timestamp and their internal play out timestamp. The perceived quality for the user is derived from the number and duration of video stalls. Algorithms for decoding Flash Video, MP4 and WebM Video have already been implemented. After deriving the play out time it is compared to the timestamp of the respective TCP segment. The result of this comparison is an estimate of the fill level of the play out buffer in terms of play out time within the client. This estimation is done without access to the end device. The same measurement procedure can be applied for any TCP based progressive download Internet service. Video was simply taken as an example because of its current large share in traffic volume in operator networks.

Progressive download video services, such as YouTube, are responsible for a major part of the transmitted data volume in the Internet and it is expected, that they also will strongly affect mobile networks. Streaming video quality mainly depends on the sustainable throughput achieved during transmission. In order to achieve an acceptable video quality in mobile networks (with limited capacity resources), traffic engineering mechanisms have to be applied. For that, the streaming video quality needs to be measured and monitored permanently. Therefore, the video timestamps which are encoded within the payload of the TCP segments have to be extracted. For that it is necessary to decode the video within the transported payload. Algorithms for decoding Flash Video, MP4 and WebM Video have already been implemented as a demonstration implementation in support of the network based measurement contribution to SG12 by Chemnitz University for TCP encoded progressive download Internet services. In the demonstration, the derived play out buffering from the monitored traffic is being output internally. A second application is then used to graphically display the estimation result. The measurement and estimation is solely done within a measurement point of an operator network without access to the client’s end device.

Progressive download video services, such as YouTube and podcasts, are responsible for a major part of the transmitted data volume in the Internet and it is expected, that they will also strongly affect mobile networks. Streaming video quality mainly depends on the sustainable throughput achieved during transmission. To ensure acceptable video quality in mobile networks (with limited capacity resources) the perceived quality by the customer (QoE) needs to be monitored by estimation. For that, the streaming video quality needs to be measured and monitored permanently. For TCP based progressive download we propose to extract the the video timestamps which are encoded within the payload of the TCP segments by decoding the video within the payload. The actual estimation is then done by play out buffer fill level calculations based on the TCP segment timestamp and their internal play out timestamp. The perceived quality for the user is derived from the number and duration of video stalls. Algorithms for decoding Flash Video, MP4 and WebM Video have already been implemented. After deriving the play out time it is compared to the timestamp of the respective TCP segment. The result of this comparison is an estimate of the fill level of the play out buffer in terms of play out time within the client. This estimation is done without access to the end device. The same measurement procedure can be applied for any TCP based progressive download Internet service. Video was simply taken as an example because of its current large share in traffic volume in operator networks.

Progressive download video services, such as YouTube, are responsible for a major part of the transmitted data volume in the Internet and it is expected, that they also will strongly affect mobile networks. Streaming video quality mainly depends on the sustainable throughput achieved during transmission. In order to achieve an acceptable video quality in mobile networks (with limited capacity resources), traffic engineering mechanisms have to be applied. For that, the streaming video quality needs to be measured and monitored permanently. Therefore, the video timestamps which are encoded within the payload of the TCP segments have to be extracted. For that it is necessary to decode the video within the transported payload. Algorithms for decoding Flash Video, MP4 and WebM Video have already been implemented as a demonstration implementation in support of the network based measurement contribution to SG12 by Chemnitz University for TCP encoded progressive download Internet services. In the demonstration, the derived play out buffering from the monitored traffic is being output internally. A second application is then used to graphically display the estimation result. The measurement and estimation is solely done within a measurement point of an operator network without access to the client’s end device.