Major QoS Parameters Used for Fault Identification in IPTV and OTT content delivery
The task most operators face today is how to keep the subscriber base loyal. Stable high quality of broadcasting is one of the factors that helps address this challenge. To maintain high quality and detect violations in the stream, it is important to track various parameters.
All monitored parameters are divided into two types: relating to Quality of Service (QoS) and Quality of Experience (QoE). In this article, we will consider QoS parameters that are most important for OTT/IPTV content delivery.
No signal (BadSource) error is the most critical parameter displaying the “red” state of the network delivery. This state occurs when the monitoring system cannot receive data for further analysis for some reason. To address the No signal error, it is required to investigate the cause of the issue and promptly define its location: streamer, switching equipment or network. This problem can be solved by using several analyzing solutions or multiple clients (probes) within the frame of a distributed monitoring system.
For IP streaming, two basic parameters should be primarily monitored and closely analyzed: packet loss and packet jitter; timely notifications help to ensure seamless audio and video streaming.
If no packet loss is detected and packets are sent smoothly through the network, it corresponds to high quality of signal streaming and delivery. In case of packet loss and excessive jitter detection, problems with signal and packets delivery become obvious to a viewer. Therefore, packet loss and jitter measurements are of major importance for network monitoring and QoS assurance. Packet loss can be estimated by checking TS packet headers by Continuity Counter embedded in TS.
Continuity Counter (CC) errors occur if incorrect packet order is detected or one and the same packet successively occurs more than twice, or packet is lost.
Media Loss Rate (MLR) is a metric that allows detecting packet loss values. It shows the number of transport packets lost per second.
Inter-packet Arrival Time (IAT) metric is used to measure a packet jitter by checking time intervals between arriving packets. Maximum IAT defined as a summary of average IAT and jitter is also applicable.
Delay Factor is one of the most important parameters for network quality monitoring as well. It provides accurate measurement of a stream jitter which defines bitrate fluctuation from the expected values.
In addition to the primary metrics used for network signal monitoring and described above, the following parameters should be applied as well to assure comprehensive monitoring of QoS.
Multiple broadcasters event. Occasionally, when several broadcasters start streaming data in a single multicast group, erroneous situations occur and it becomes impossible to receive a good stream.
TR 101 290 is a standard that provides guidelines for measurement in Digital Video Broadcasting (DVB) satellite, cable and terrestrial and related digital television systems. It defines measurement techniques which allows comparing the obtained results with the reference values.
The standard provides thresholds, but strict compliance with the standard requirements is not mandatory for IPTV streams. Correspondingly, threshold configurations can be adjusted to exclude unwanted trigger actions. TR 101 290 analysis can be applied either for IPTV or for unencrypted OTT services (or for services that can be decrypted) based on fragmented TS technology.
In case of TR 101 290 errors detection, picture defects become visible to a viewer, such as: picture pixelization, noises and artifacts, audio and/or video freezes, loss of service, black screen etc.
Download rate/Multicast rate. Download rate over the HTTP/HTTPS protocol or total bitrate of incoming UDP/RTP stream. The monitoring system compares download/multicast rate with a segment length and its bitrate.
To track all the parameters mentioned above, we recommend using Elecard Boro. Elecard Boro is a solution for UDP, RTP, HTTP and HLS streams monitoring and measurement of QoS and QoE parameters. It allows you to quickly find any stream quality violations, receive notifications about problems, and use monitoring statistics.