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P122
• The duration of the cuts - accumulated durations of the cuts that occurred during one streaming session.
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P123
The drawback of this approach is that it is difficult to differentiate between video site performance and ISP performance as some video sites might use different streaming servers for different ISPs.
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P124
There’s also a third approach which is a combination of the other two. It consists of using a video that is longer than a defined minimum length (e.g. 20 seconds). The video is requested with the encoded bitrate set to the maximum available value. If there’s a break, the test is repeated with a lower bitrate. The test is repeated at decreasing bitrates until there’s no break during the playback. The highest bit rate at which the playback is successful is then considered to be an indicator of video streaming quality of service. Such a test should be repeated to get more accurate results.
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P125
The monitoring of the video streaming quality of service also includes the case of live streaming. In this case, an additional parameter can be added: additional delay introduced by encoding the live stream
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P126
It is also possible to measure video streaming QoS by simply measuring the video streaming bitrate instead of measuring impacts such as decreased video quality, increased negotiation time and the number and duration of cuts. This bitrate can be compared to the IAS speed measurement results, while taking into account that bitrate is also influenced by player capabilities and requirements. Thus a mobile network providing IAS to predominantly small screen terminals would typically show lower bitrates, regardless of the performance of the network itself.
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4.2.3 Other use cases
P127
Other use cases could be the subject of future study, following similar methodologies to those described previously. Such candidate use cases include Voice over IP (VoIP), audio streaming or peer-to-peer file sharing and any other future applications not yet released.
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P128
This chapter describes recommendations on identifying the end user environment factors which may affect measurement results and in some cases, minimising impacts to the measurement results.
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P129
The main challenge for this type of measurement is the potential impact of the end user environment on the measurement results. Some end users might not be aware of the potentially negative influence of their own terminal equipment and home network but assume that all issues are on the access service or content provider’s side.
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P130
Based on this, it is important that end users are informed of how to properly set up their terminal equipment to minimise error. It is also crucial to inform the end user that conducting multiple QoS measurements will provide a more representative view of IAS performance, and better analysis and assessment of measurement results.
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P131
Moreover, in order to ensure that measurement results are accurate, a measurement server must protect itself against overload, to prevent a case where too many simultaneous measurement sessions cause interference. Therefore any measurement server must implement access control and queueing such that excessive measurement requests are responded to with a temporary delay, resulting in clients waiting until the measurement server is ready.
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P132
The end user environment consists of many elements, some of which could limit IAS performance. These limiting factors are listed and described below in two separate sub-sections differentiating between fixed and mobile environments.
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P133
It is recommended that, when available, the measurement client retrieves the required data from the local hardware and operating system (computer and modem router) and from the IAS provider both before and while running measurements.
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P134
A prerequisite of such data collection is the informed consent of the user, which should be required by the measurement client before measurement commencement.
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