APPARATUS AND METHOD FOR MONITORING PERFORMANCE IN A COMMUNICATIONS NETWORK

• US 20150163271A1
• Filed: 12/21/2011
• Published: 06/11/2015
• Est. Priority Date: 12/22/2011
• Status: Abandoned Application

• Current Assignee: Telefonaktiebolaget LM Ericsson
• Original Assignee: Telefonaktiebolaget LM Ericsson
• Inventors: Handurukande, Sidath, Fedor, Szymon
• Application Number:
  US14/367,558
• Publication Number:
  US 20150163271A1
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: H04L 41/142 using statistical or mathematical methods
• CPC Class Codes: H04L 43/0829 Packet loss
• CPC Class Codes: H04L 43/55 Testing of service level quality, e.g. simulating service usage
• CPC Class Codes: H04L 65/75 Media network packet handling
• CPC Class Codes: H04L 65/80 Responding to QoS

Abstract

A method for monitoring the performance of a media streaming service being used to deliver media streams to user equipment devices comprises the step of determining an encoding characteristic of a first media stream (201) being monitored. A functional dependency model is established between a first System Service Key Performance Indicator, S-KPI, and one or more Resource Service Key Performance Indicators, R-KPIs, for the first media stream (203). The established functional dependency model is used for monitoring a second media stream having the same encoding characteristic as the first media stream (205).

Claims

1. A method for monitoring the performance of a media streaming service being used to deliver media streams to user equipment devices, the method comprising:

determining an encoding characteristic of a first media stream being monitored;

establishing a functional dependency model between a first System Service Key Performance Indicator, S-KPI, and one or more Resource Service Key Performance Indicators, R-KPIs, for the first media stream; and

using the established functional dependency model for monitoring a second media stream having the same encoding characteristic as the first media stream.

2. The method as claimed in claim 1, wherein the step of establishing a functional dependency model comprises the steps of establishing a functional dependency model between the first S-KPI and one or more R-KPIs for each of a plurality of different media streams, each having a different encoding characteristic.

3. The method as claimed in claim 1, wherein the step of establishing a functional dependency model comprises the steps of:

establishing a functional dependency model between the first S-KPI and one or more R-KPIs for at least a second media stream, the at least second media stream having a different encoding characteristic to the first media stream; and

using a mathematical relationship between the functional dependency models for the first and at least second media streams to extrapolate a functional dependency model between the first S-KPI and one or more R-KPIs for a third media stream, the third media stream having a different encoding characteristic to the first and second media streams.

4. The method as claimed in claim 1, wherein the step of establishing a functional dependency model comprises the steps:

establishing a functional dependency model between the first S-KPI and one or more R-KPIs for at least a second media stream, the at least second media stream having a different encoding characteristic to the first media stream;

comparing the functional dependency model established for the first media stream with the functional dependency model established for the at least second media stream;

determining a mathematical relationship between the functional dependency models; and

using the mathematical relationship to extrapolate a functional dependency model between the first S-KPI and one or more R-KPIs for a third media stream, the third media stream having a different encoding characteristic to the first and second media streams.

5. The method as claimed in claim 3, wherein the mathematical relationship is a linear relationship, an exponential relationship or a parabolic relationship.

6. The method as claimed in claim 1, wherein the encoding characteristic of a media stream is determined from information received from the source of the media stream.

7. The method as claimed in claim 1, wherein the encoding characteristic of a media stream is determined from a header portion of the media stream.

8. The method as claimed in claim 1, wherein the encoding characteristic comprises any one or more of the following:

a bit rate of the media stream;

an average bit rate of the media stream;

a maximum bit rate of the media stream;

an indication relating to whether the media stream is a variable or a constant bit rate media stream;

a frame rate of the media stream;

an indication of the type of codec used to encode the media stream.

9. The method as claimed in claim 1, wherein the encoding characteristics of different media streams are categorised into a plurality of distinct levels, such that a functional dependency model established for a media stream having a particular encoding level is used when monitoring another media stream having the same encoding level.

10. The method as claimed in claim 1, wherein the functional dependency model is adapted to take account of changes of state of an encoder used to encode the media streams, wherein a functional dependency model is established for each state of the encoder.

11. The method as claimed in claim 1, further comprising the steps of:

collecting R-KPIs from network resources;

collecting S-KPIs from a representative sample of reporting user equipment devices using the media streaming service;

determining a relationship between the collected values of R-KPIs and S-KPIs;

clustering the user equipment devices from the representative sample based on the relationship between the R-KPIs and the S-KPIs;

assigning non-reporting user equipment devices to the clusters;

collecting R-KPIs from network resources; and

estimating S-KPI values based on the relationship and the R-KPIs collected after the relationship is determined.

12. A monitoring device for use in a communications network for monitoring the performance of a media streaming service that is used to deliver media streams to user equipment devices via the communications network, the monitoring device comprising:

a detection module adapted to determine an encoding characteristic of a first media stream being monitored; and

a processing module adapted to establish a functional dependency model between a first System Service Key Performance Indicator, S-KPI, and one or more Resource Service Key Performance Indicators, R-KPIs, for the first media stream;

wherein the processing module is further adapted to use the established functional dependency model for monitoring a second media stream having the same encoding characteristic as the first media stream.

13. The monitoring device as claimed in claim 12, wherein the processing module is further adapted to establish a functional dependency model between the first S-KPI and one or more R-KPIs for each of a plurality of different media streams, each having a different encoding characteristic.

14. The monitoring device as claimed in claim 12, wherein the processing module is further adapted to establish a functional dependency model between the first S-KPI and one or more R-KPIs for at least a second media stream, the at least second media stream having a different encoding characteristic to the first media stream;

and use a mathematical relationship between the functional dependency models for the first and at least second media streams to extrapolate a functional dependency model between the first S-KPI and one or more R-KPIs for a third media stream, the third media stream having a different encoding characteristic to the first and second media streams.

15. The monitoring device as claimed in claim 12, wherein the processing module is further adapted to establish a functional dependency model between the first S-KPI and one or more R-KPIs for at least a second media stream, the at least second media stream having a different encoding characteristic to the first media stream, compare the functional dependency model established for the first media stream with the functional dependency model established for the second media stream, determine a mathematical relationship between the functional dependency models, and use the mathematical relationship to extrapolate a functional dependency model between the first S-KPI and one or more R-KPIs for a third media stream, the third media stream having a different encoding characteristic to the first and second media streams.

16. The monitoring device as claimed in claim 12, wherein the detection module is adapted to detect the encoding characteristic of a media stream from information received from the source of the media stream, or from a header portion of the media stream.

17. The monitoring device as claimed in claim 12, wherein the monitoring server forms part of a network edge device.

18. A communications network comprising a media streaming service that is adapted to provide media streams to user equipment devices via the communications network, the communications network comprising:

a monitoring device comprising;

a detection module adapted to determine an encoding characteristic of a first media stream being monitored; and

a processing module adapted to establish a functional dependency model between a first System Service Key Performance Indicator, S-KPI, and one or more Resource Service Key Performance Indicators, R-KPIs, for the first media stream;

wherein the processing module is further adapted to use the established functional dependency model for monitoring a second media stream having the same encoding characteristic as the first media stream.

19. The communications network as claimed in claim 18, wherein the processing module is further adapted to establish a functional dependency model between the first S-KPI and one or more R-KPIs for each of a plurality of different media streams, each having a different encoding characteristic.