Evaluating the Eﬀect of Path Diversity over QoS and QoE in...

Evaluating the Effect of Path Diversity over QoS andQoE in a High Speed Indoor Mesh Backbone

Sandip Chakraborty12, Sukumar Nandi

Department of Computer Science and EngineeringIndian Institute of Technology Guwahati,

Guwahati 781039 INDIA

08 January, 2014

1This work is supported by TATA Consultancy Services (TCS), INDIA through TCSResearch Fellowship program

2Supported by COMSNETS 2014 Travel GrantSandip Chakraborty (CSE, IITG) COMSNETS 2014 08 January, 2014 1 / 23

Preface: QoS and QoE in the Network

Quality of Service (QoS): Performance guarantee from networkperspective,

- Throughput (available bandwidth)

- End-to-end delay

- Jitter (variation in per packet delay)

Quality of Experience (QoE): Performance for user’s perspective,

- Mean Opinion Score (MOS) for voice traffic

- Peak Signal to Noise Ratio (PSNR) for video traffic

- Structural Similarity Index Measurement (SSIM) for video traffic

How path diversity affect QoS and QoE in a multi-hop IEEE 802.11nmesh network in an indoor scenario?

Sandip Chakraborty (CSE, IITG) COMSNETS 2014 08 January, 2014 2 / 23

Diversity in a Mesh Network

Path Diversity: Multiple paths from a source to a destination

Traffic Diversity:

Diversity in Path Quality: Path quality significantly varies withrespect to time.

Data Rate Diversity: Varies from 2 Mbps to 600 Mbps with IEEE802.11n


Forwarding in a Mesh Network (IEEE 802.11s)

Hybrid Wireless Mesh Protocol (Combination of proactive andreactive routing)

Routing metric: Airtime Link Metric

C =

[

Oca + Op +Bt

r

]

1

1− ef

Where,Oca and Op are the constants, named as the channel access overheadand the protocol overhead,Bt is the test frame size.The input parameters r and ef are the bit rate in Mbps and the frameerror rate for the test frame size Bt .


Testbed Environment

N6N7

N N2 N1

N

N

3

4

5

RS Lab 1RS Lab 2

Security Lab

G

N8

N N9 10

50 m


Testbed Setup

Router: RaLink RT-3352 RoC: 2T2R MAC/BBP/PA/RF, 400MHzMIPS24KEc CPU, 64MB of SDRAM and 32MB of Flash

IEEE 802.11n: 300 Mbps, channel bonding

Open80211s: http://www.open80211s.org

Linux Kernel 2.8.54

TCP (FTP) and UDP (TFTP) using iperf

(http://iperf.sourceforge.net/)

Tx Power 16dBm, Rx Sensitivity 0 dBm (45-55 mt in indoor)


http://www.open80211s.org

http://iperf.sourceforge.net/‎

Effect of Diversity over Airtime Link Metric

-120

-110

-100

-90

-80

-70

2 2.4 2.8 3.2 3.6 4 4.4S

INR

(d

Bm

)

0

10

20

30

40

50

60

2 2.4 2.8 3.2 3.6 4 4.4

Lo

ad

0.4

0.6

0.8

1

1.2

2 2.4 2.8 3.2 3.6 4 4.4

AL

M (

ms)

Time (Hrs)


Selective Greedy Forwarding (SGF)3

Selection of a set of potential forwarders (Proactive approach)

Selection of the next hop from the set of potential forwarders (Greedyapproach)

- Effect of the variation in link information over the path information

S

3Chakraborty, S.; Chakraborty, S.; Nandi, S., “Beyond conventional routing protocols:Opportunistic path selection for IEEE 802.11s mesh networks,” in proc. of IEEE 24thInternational Symposium on Personal Indoor and Mobile Radio Communications (PIMRC), pp.3224-3228, 8-11 Sept. 2013Sandip Chakraborty (CSE, IITG) COMSNETS 2014 08 January, 2014 8 / 23

Route Flapping for QoS/QoE

High Route Flapping: Network inconsistency

Low Route Flapping: Network fails to adopt with channel variation


SGF: Route Flapping

5

10

15

20

25

30

0 1 2 3 4 5 6 7 8 9 10 11SIN

R V

ari

ati

on

(d

Bm

)

0

10

20

30

40

50

60

0 1 2 3 4 5 6 7 8 9 10 11

Ro

ute

Fla

pp

ing

Lo

w L

oad

Reactive HWMPProactive HWMP

SGF

0 10 20 30 40 50 60

0 1 2 3 4 5 6 7 8 9 10 11

Ro

ute

Fla

pp

ing

Hig

h L

oad

Router Number

Reactive HWMPProactive HWMP

SGF


Forwarder Percentage (δ)

Percentage of neighbors selected as the set of potential forwarders.

0 5

10 15 20 25 30 35 40 45

0 1 2 3 4 5 6 7 8 9 10 11

Ro

ute

Fla

pp

ing

Lo

w L

oad

δ = 60%δ = 40%δ = 20%

0 5

10 15 20 25 30 35 40 45

0 1 2 3 4 5 6 7 8 9 10 11

Ro

ute

Fla

pp

ing

Hig

h L

oad

Router Number

δ = 60%

δ = 40%δ = 20%


QoS Metrics: MAC Throughput

0

1

2

3

4

5

6

7

8

10 20 30 40 50 60

Avera

ge P

er

User

MA

C T

hro

ug

hp

ut

(Mb

ps)

Average Number of Users

HWMP: ProactiveHWMP: Reactive

SGF: δ=30%SGF: δ=40%SGF: δ=50%


QoS Metrics: Forwarding Delay

100

200

300

400

500

600

700

800

900

1000

1100

10 20 30 40 50 60

Avera

ge E

nd

-to

-En

d D

ela

y (

ms)





QoS Metrics: Average Jitter

16

18

20

22

24

26

28

30

32

10 20 30 40 50 60

Avera

ge J

itte

r (m

s)





QoE Metrics: MOS (Voice)

2.6

2.8

3

3.2

3.4

3.6

3.8

4

4.2

4.4

10 20 30 40 50 60

MO

S





QoE Metrics: PSNR (Video)

5

10

15

20

25

30

35

10 20 30 40 50 60

PS

NR

(d

B)





QoE Metrics: SSIM (Video)

0.65

0.7

0.75

0.8

0.85

0.9

0.95

1

10 20 30 40 50 60

SS

IM





Adopting δ with Traffic Load Variation

At the beginning of every DTIM interval, mesh routers computetraffic load in terms of number of associated users (Qr (t)).

δmin ≥ 2, δmax ≤ 0.5Nr

Model the network as a birth-death process;

δiδi −1 δmaxδmin

+1

i−1pi

ipi−1

δmin


Average Forwarding Delay

100

200

300

400

500

600

700

800

900

1000

1100

10 20 30 40 50 60

Avera

ge E

nd

-to

-En

d D

ela

y (

ms)



SGF + Adaptive SPF


Average Jitter

16

18

20

22

24

26

28

30

32

10 20 30 40 50 60

Avera

ge J

itte

r (m

s)



SGF + Adaptive SPF


Voice: MOS

2.6

2.8

3

3.2

3.4

3.6

3.8

4

4.2

4.4

10 20 30 40 50 60

MO

S



SGF + Adaptive SPF


Channel Fluctuation vs MOS

-40

-30

-20

-10

0

5.2 5.6 6 6.4 6.8 7.2 7.6 8SIN

R V

ari

ati

on

(d

Bm

)

10 20 30 40 50 60 70 80

5.2 5.6 6 6.4 6.8 7.2 7.6 8

Lo

ad

2.4

3.6

4.8

6

7.2

5.2 5.6 6 6.4 6.8 7.2 7.6 8

MO

S

Time (Hrs)

HWMP ProactiveHWMP Reactive

SGF


Conclusion

Explores the effects of path diversity over QoS and QoE in a highspeed mesh network

Evaluated ‘Selective Greedy Forwarding’: A new routing paradigmthrough testbed results,

- Channel fluctuation and traffic load affects the performance of SGF

- Use large δ at low traffic load, and small δ at high traffic load, to avoidboth high and low route flapping

- Adopt forwarding paths based on network conditions


Conclusion

Explores the effects of path diversity over QoS and QoE in a highspeed mesh network

Evaluated ‘Selective Greedy Forwarding’: A new routing paradigmthrough testbed results,

- Channel fluctuation and traffic load affects the performance of SGF

- Use large δ at low traffic load, and small δ at high traffic load, to avoidboth high and low route flapping

- Adopt forwarding paths based on network conditions

Thank You


Evaluating the Eﬀect of Path Diversity over QoS and QoE in...

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