(OTT) meritve kakovosti širokopasovnih omrežij

Transcription

1 (OTT) meritve kakovosti širokopasovnih omrežij prof. dr. Andrej Kos, Janez Sterle Labratory for Telecommunications Faculty of Electrical Engineering University of Ljubljana Slovenia Ljubljana, Mons,

2 Laboratory for Telecommunications LTFE International scientific, R&D and interdisciplinary projects cooperation People Young and motivated team 50+ researchers, students, profesors, technicians 4 main groups Networking Protocols MM applications ICT for ehealth, accessibility

3 Luka Mali, Internet - Yesterday 3

4 Luka Mali, Internet - Today 4

5 Cloud

6 Luka Mali, Internet - Tomorrow 6

7 Luka Mali, Luka Mali, Mobile data growth EB/month 3,6 2,2 1,2 0,09 0,2 0,

8 Quality of Service and Quality of User Experience 8

9 QoS and QoE QoS measure of performance from the network level standards ITU-T Rec. E.800 tipical QoS metrics Delay jitter Throughput packet loss QoE quality of service/application as subjectively percepted by a user standard ITU-T Rec. G.1080/G.1010 Includes effects of the whole network and also depends on user context network performance user equipment performance service/application network dependence 9

10 Methods of QoE modeling Subjective advantages most representative disadvantages based on end users answers results are hard to repeat real-time measurements not possible compex measurements Objective advanteges universal results can be repeated metrics based only on measured results fast and real-time measurements possible disadvanteges worse aproximation of QoE for a certain users 10

11 Measured indicators QoE KPI Responsiveness PING: average RTT [s] DNS: DNS response time [s] WEB: web page download [s] Speed WEB: web page download [bit/s] http DL/UL: dowload time [s] http DL/UL: download speed [bit/s] Availability PING: lost ICMP packets [izgubljeni odgovori/poslane zahteve] WEB: page availability [nedosegljive strani/poslane zahteve] http DL/UL: availability [nedokončani prenosi/poslane zahteve] 11

12 Analogy QoS vs. QoE QoS indicaors network availability [%] delay [s] delay variation [s] lost packets [%] bandwidth [bit/s] QoE indicators service availability [%] service response [s] response variation [s] lost requests [%] service execution speed 12

13 Measurement system User emulation DWH Reporting Database Analytics zlaganje rezultatov v bazo server1 server2 web server server1 server2 file server server1 server2 server/ router server1 server2 mail server meritev DL server1 server2 FTP za UL meritev mail osnovni nadzor meritev UL Management Konfiguracije (XML) osnovni nadzor upload rezultatov Parser server1 server2 FTP za rezultate server1 server2 dns server Javna infrastruktura meritev WEB meritev PING meritev DNS Klient.exe 13

14 Internet access provider System under test Web WEB QoE sondes Europe US Japan China Slovenia Slovenia Slovenia WEB 1 WEB 2 WEB N WEB 1 WEB 2 WEB N WEB 1 WEB 2 WEB N WEB 1 WEB 2 WEB N WEB 1 WEB 2 WEB N WEB 1 WEB 2 WEB N WEB 1 WEB 2 WEB N Domain C Domain B Internet tranzit IX Internet Exchange QOE KPI Core network Access network WEB 1 WEB 2 WEB N Domain A CPE QoE agent Personal computer Home network, mobile node 14

15 Examples of OTT QoE measurements 15

16 Geo tagging 16

17 Internet of Things

18 What does an IoT platform do? A solution/server in cloud able to drive & converge all kinds of IoT data, information and applications can be generic/specific, cloud based/not cloud based, horizontal/vertical, open/closed, real time/ non real time It serves as a virtualized IoT anchorage catching drops of data across different domains contextualizing & providing an insight into what you/we have It can host a variety of (cross-domain) IoT apps classical QoS/QoE monitoring IPTV network monitoring lightnings reports alarming personal wellbeing, road traffic monitoring and simulations, smartcity, smartenergy,... It correlates information from a variety of applications 18

19 Our IoT platform Event-driven system, open source based Real-time KPI discovery predefined KPI sets for different domains tools to create new KPIs tools to mix &match KPIs (correlations) Agile simple analytics & visualizations real time and historical information alarms, trend analyses Event triggering Open interfaces 19

20 Our IoT platform Green: event-driven components Blue: data-driven components 20

21 IoT meritve IPTV 21

22 Opportunities Companies/Telcos/Persons have many sistems that generate a lot of data need systems to monitor, to assure quality, to ease tasks, to... Typical company/telco/vendor has deployed 1000s of boxes generating 100s of events per day -> terabytes of data Most of events bear no information But, how do we find the needle in the haystack and find out what caused the problem? How can we make things work better? How can we detect trends? How can we correlate data? Many use cases we show IPTV QoS/QoE as an example 22

23 IPTV system complexity Classic broadcast systems: Simple architecture Single transmitter, multiple receivers Headend Subscriber IPTV systems are substantially more complex Chain of at least 6 elements to each(!) user Multitude of support systems 23

24 Possible causes of errors Anywhere in the provider subscriber chain Content owner Subscriber Errors in content itself Encoding / transcoding errors Network-level errors Errors on customer premises poor quality jitter due to imprecise clock picture quality degradation desynchronization of audio and video codec / compression issues Packet loss, delay, jitter, low bandwidth Influence of packet loss on I/P/B video frames video quality degradation due to network errors change in luminance / chrominance components Terminal equipment streaming issues 24

25 Approaches to monitoring Network probes Expensive, Limited scope Justified for important network links Does not monitor the connection end-to-end Customer premises probes Takes into account the entire chain (end-to-end) Expensive (installation cost) Justified for problematic users (limited population) Monitoring IPTV using an IoT approach IP television system as a sensor network Each individual STB represents a sensor node Advantages of such approach Enables 100% penetration (monitoring the entire network) Presence inside the STB means end-to-end coverage 25

26 How it all fits together with a platform 26

27 Event Correlation Correlation among lightning reports (circles/elipses with amplitude) and alarms/alerts source for lightning reports No real storms with outages last few weeks 27

28 Network Error localization Links with simultaneous errors share common parents in the multicast tree 28

29 Conclusion and Next steps QoS and QoE QoE measuring system, QoE measured system Sample QoS/QoE measurments Internet of Things (IoT) IoT IPTV measurements Next steps Mobile QoS/QoE client (Android, IoS) Local reports for uses, server reports - aggregated Use case migration to IoT platform Correlation with other use cases