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Velocity effect on the Performance of MANEMO. Adisorn Lertsinsrubtavee,Dr.Teerapat Sanguankotchakorn,Dr.Anis Laouiti,Prof.Kanchana Kanchansut 2010 – 02 – 25 The Third AsiaFI Winter School Seoul National University, Seou l, Korea. Outline. Background Objective Movement Scenario E- Model - PowerPoint PPT Presentation
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Adisorn Lertsinsrubtavee,Dr.Teerapat Sanguankotchakorn,Dr.Anis Laouiti,Prof.Kanchana Kanchansut2010 – 02 – 25
The Third AsiaFI Winter SchoolSeoul National University, Seoul, Korea
Velocity effect on the Performance of MANEMO
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Outline
• Background• Objective• Movement Scenario• E- Model• Data analysis• Conclusion
BACKGROUND
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 notavailable so people will lost of contact
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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
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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
[1] V. Devarapalli, R. Wakikawa, A. Petrescu, P. Thubert “RFC3963 - Network Mobility (NEMO) Basic Support Protocol”
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NEtwork MObility (NEMO) cont.
• NEMO problem Routing Optimization problem[2]
Routing is highly Inefficiency in nested NEMO
Packets have to route to HA
[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
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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)
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
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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
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MOVEMENT SCENARIO
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
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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)
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Movement Scenario
IntERLab
200 m
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Data Measurement
MR 1MR 2
MR 3
Mobile Network 1
HQ (CN) HAHome Network
802.11 AP
IPv6 Router
MNN2MNN1
Move with different speed
Logical connection
Output Parameters ToolsTp Netperf
RTT,PLR PingDee(RTP), PLR (RTP) Wireshark
VoIP call Linnphone
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ITU-T G.107, THE E MODEL
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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
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E-ModelReference Connection
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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• Ie –eff =Equipment Impairment factor
• A= Expectation factor
o s d e effR R I I I A
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Default value from ITU-T G.107
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Reduction model
• Substitute default values from ITU-T G.107• Idd represents the impairment caused by one way
delay (Ta)• Ie-eff represents the impairment caused by type of
codec, Packet loss, and Packet loss burst ratio
93.35 dd e eefR I I
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DATA ANALYSIS
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Network performance assessment
Speed Static 5 Km/h 10 km/h 15 km/h 25 km/h 35 km/h
PLR(%) 0.51 16.53 18.45 28.29 32.73 34.51
RTT (ms) 12.61 13.51 16.87 18.30 20.99 27.58
Static 5 10 15 25 350510152025303540
Packet Loss Rate
Speed (km/h)
Perc
enta
ges
Static 5 10 15 25 350
5
10
15
20
25
30RTT average
Speed (km/h)
ms
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Static 5 10 15 25 350
0.5
1
1.5
2
2.5
3
Throughput
Speed (km/h)
TP [M
B/s]
Speed Static 5 km/h 10 km/h 15 km/h 25 km/h 35 km/h
Tp (Mbps) 2.55 2.23 2.16 2.09 1.62 1.52
Network performance assessment
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E model Rating factor
Speed Static 5 km/h 10 km/h 15 km/h 25 km/h 35 km/h
R Value 91.11 91.79 70.94 57.63 46.76 37.29
Static
<5
10
15
25
35
0 10 20 30 40 50 60 70 80 90 100
R value without H/O period
R value
Spee
d (k
m/h
)
Quality Bad Poor Low Medium High Best
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Rating factor with User satisfaction
Range of E model rating R
Speech transmission quality category
User satisfaction Speed (km/h)
90≤R<100 Best Very satisfied V≤5.43
80≤R<90 High Satisfied 5.43<V≤7.83
70<R≤80 Medium Some users dissatisfied 7.83<V≤10.35
60<R≤70 Low Many users dissatisfied 10.35<V≤14.11
50<R≤60 Poor Nearly all users dissatisfied 14.11<V≤22.02
R≤50 Bad Not Recommended V>22.02
Static <5 10 15 25 350102030405060708090100
Rating Factor of speed effect compare with user satisfaction level
Speed (km/h)
R va
lue
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Performance Comparison of single group movement
Output Static 35 km/h Difference (%)Throughput (Mbps) 2.55 1.51 40.56
Packet Loss Rate(%) 0.51 34.51 34
RTT Delay (ms) 12.61 27.58 118.75
R factor 91.11 26.90 53.82
Throughput Packet Loss RTT Delay R value R value exclude
H/O time
0
20
40
60
80
100
120
140
40.5634.00
118.75
53.82
Performance decreased
Perc
enta
ges
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VoIP Quality assessment
Static 5 10 15 25 350
5
10
15
20
25
Packet Loss
Speed (km/h)
Perc
enta
ges
Static 5 10 15 25 350
2
4
6
8
10
12
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End to End Delay avearage
Speed (km/h)
Tim
e [m
s]Speed Static 5 Km/h 10 km/h 15 km/h 25 km/h 35 km/h
PLR(%) 1.00 20.54 13.06 7.19 8.34 6.09
Dee (ms) 10.13 12.77 11.42 10.83 11.11 10.73
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VoIP Quality assessment : R value
Static
5
10
15
25
35
0 10 20 30 40 50 60 70 80 90 100
R value
R value
Spee
d (k
m/h
)
Quality Bad Poor Low Med High Best
Speed Static 5 km/h 10 km/h 15 km/h 25 km/h 35 km/h
R value 89.13 32.94 50.98 68.39 64.67 71.38
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CONCLUSION
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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
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Future work
• Validate the experiment result Simulation
• Reducing Hanover time Fast H/O
• Field experiment with different movement scenario• Other routing protocols
OLSR…
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THANK YOU