1. Adisorn Lertsinsrubtavee,Dr.Teerapat Sanguankotchakorn,Dr.Anis Laouiti,Prof.Kanchana Kanchansut 2010 – 02 – 25 The Third AsiaFI Winter School Seoul National University, Seoul, Korea Adisorn Lertsinsrubtavee,Dr.Teerapat Sanguankotchakorn,Dr.Anis Laouiti,Prof.Kanchana Kanchansut 2010 – 02 – 25 The Third AsiaFI Winter School Seoul National University, Seoul, Korea 1 Velocity effect on the Performance of MANEMO

2. Outline Background Objective Movement Scenario E- Model Data analysis Conclusion 2

3. BACKGROUND

4. Motivation The Situation –A disaster area several miles on a side in which almost all communications have been wiped out. Cellular network and Public SW are not available so people will lost of contact

5. Post disaster recovery Rescue operation Small group of movement (eg. Car, boat,..) Communication between group and to based camp Multi-hops wireless network with vehicular mobility 5

6. NEtwork MObility (NEMO) NEMO (RFC 3963) 1 Mobile Router (MR)  MRs equip in vehicles  Provide the connectivity to its client via ingress interface  Connect to high level MR to reach the HA via egress interface Home Agent (HA)  All the NEMO networks have to register HoA and CoA to localize the position Mobile Network Node(MNN)  Connect to MR through WiFi 6 [1] V. Devarapalli, R. Wakikawa, A. Petrescu, P. Thubert “RFC3963 - Network Mobility (NEMO) Basic Support Protocol”

7. NEtwork MObility (NEMO) cont. NEMO problem  Routing Optimization problem [2]  Routing is highly Inefficiency in nested NEMO  Packets have to route to HA 7 [2] Wakikawa,R., Thubert, P., Boot, T., Bound,J. & McCarthy, B Problem Statement and Requirements for MANEMO”, (draft-wakikawa-manemo-problem-statement-01.txt), IETF, Internet Draft, July 2007

8. MANEMO NEMO + MANET MANEMO Nested NEMO structure  NEMO is designed to provide global connectivity  MANET supports the data transfering in local connectivity Solution (NEMO +)  TD (Tree Discovery)  NINA (Network In Node Advertisement) 8

9. Statement of Problem What is the limitation or optimal value of velocity?  Vehicles are always used in MANEMO but until now we still have not known the limitation of their velocity How accurate of the analytic or simulation result ?  The real experiment can be the best solution to answer this question but most of research works only consider to analytic model and simulation method How can we know the optimal value is useable ?  Various movement scenarios can be provide to find out more the accurate result

10. Objective To study and apply the MANEMO approach to the real experiment To measure and evaluate the performance of MANEMO environment which impacted by velocity To assess the quality of VoIP service on the MANEMO environment To specify the limitation of velocity in the MANEMO environment 10

11. MOVEMENT SCENARIO 11

12. Parameter Declaration Group of movement Outputs measurement  Throughput  Packet Loss  End to End Delay  VoIP Call Quality Input Factors  Static case (ref.)  Speed 5 – 35 km/h

13. Output Performance Network performance assessment  ICMP ping and Netperf  RTT  Packet Loss Rate (PLR)  Throughput (Tp) VoIP call quality assessment  Linnphone (SIP soft phone application)  End to End Delay (Dee)  Packet Loss Rate (PLR) 13

14. Movement Scenario 14 IntERLab 200 m

15. Data Measurement 15 Output ParametersTools TpNetperf RTT,PLRPing Dee(RTP), PLR (RTP)Wireshark VoIP callLinnphone

16. ITU-T G.107, THE E MODEL 16

17. Introduction of E-Model Recommendation G.107 (ITU standard) Transmission planning tool  Evaluating end-to-end Voice quality Calculation a scalar quality rating value  Transmission rating factor (R) Rating Factor, R (0 - 100)  100 = Excellent performance  60 = Acceptable level 17

18. E-Model Reference Connection 18

19. E-Model Equation R = Rating factor (0-100) Ro= the effect of noise and loudness ratio Is = The effect of impairments occurring simultaneous with the speech signal Id = Delay impairment factor I e –eff =Equipment Impairment factor A= Expectation factor 19

20. Default value from ITU-T G.107 20

21. Reduction model Substitute default values from ITU-T G.107 I dd represents the impairment caused by one way delay (Ta) I e-eff represents the impairment caused by type of codec, Packet loss, and Packet loss burst ratio 21

22. DATA ANALYSIS 22

23. Network performance assessment 23 SpeedStatic5 Km/h10 km/h15 km/h25 km/h35 km/h PLR(%)0.5116.5318.4528.2932.7334.51 RTT (ms)12.6113.5116.8718.3020.9927.58

24. 24 SpeedStatic5 km/h10 km/h15 km/h25 km/h35 km/h Tp (Mbps)2.552.232.162.091.621.52 Network performance assessment

25. E model Rating factor 25 SpeedStatic5 km/h10 km/h15 km/h25 km/h35 km/h R Value91.1191.7970.9457.6346.7637.29 QualityBadPoorLowMediumHighBest

26. Rating factor with User satisfaction 26 Range of E model rating R Speech transmission quality category User satisfactionSpeed (km/h) 90≤R<100 BestVery satisfied V≤5.43 80≤R<90 HighSatisfied 5.43<V≤7.83 70<R≤80 MediumSome users dissatisfied 7.83<V≤10.35 60<R≤70 LowMany users dissatisfied 10.35<V≤14.11 50<R≤60 PoorNearly all users dissatisfied 14.11<V≤22.02 R≤50 BadNot RecommendedV>22.02

27. Performance Comparison of single group movement 27 OutputStatic35 km/hDifference (%) Throughput (Mbps) 2.551.5140.56 Packet Loss Rate(%) 0.5134.5134 RTT Delay (ms) 12.6127.58118.75 R factor 91.1126.9053.82

28. VoIP Quality assessment 28 SpeedStatic5 Km/h10 km/h15 km/h25 km/h35 km/h PLR(%)1.0020.5413.067.198.346.09 Dee (ms)10.1312.7711.4210.8311.1110.73

29. VoIP Quality assessment : R value 29 Quality BadPoorLowMedHighBest SpeedStatic5 km/h10 km/h15 km/h25 km/h35 km/h R value89.1332.9450.9868.3964.6771.38

30. CONCLUSION 30

31. Conclusion Speed increment can decrease performance of MANEMO  i.e. Packet loss, Throughput, Round Trip Time delay  Performance decreased from 34-118.5% Acceptable level of E model (R=60)  Speed must less than 14.11 km/h VoIP call quality is increased when speed is increased H/O period  H/O time has a significant impact to quality of communication  Reducing H/O time can increase the quality of speech transmission 31

32. Future work Validate the experiment result  Simulation Reducing Hanover time  Fast H/O Field experiment with different movement scenario Other routing protocols  OLSR… 32

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