Video Streaming Performance in a Wireless Mesh Net-work with Potential-Based Autonomous Routing

Malaz Kserawi, Sangsu Jung, and J.-K. Kevin RheeKAIST2/25/2010

1/15

Contents

Introduction : Wireless mesh network Video streaming Challenges and goals

Proposed protocol (FAR) Model design Potential Procedure

Performance evaluation Conclusion References

2/15

Introduction-WMN

• Fixed infrastructure • Multihop packet forwarding• Provides wireless connection for

a wide area• Provides Internet access to mobile

hosts• Anycast routing

Access point

Gateway

Figure 1. Wireless Mesh Network structure

3/15

• Killer applications• High data rates leads to congestion especially near gateway• Inefficient load sharing causes extra delay and packet loss• Improving video quality is a MUST

Introduction-Video over WMN

2008 2009 2010 2011 2012 20130

2,000

4,000

6,000

8,000

10,000

12,000

14,000

Video communicationvideo to PCVideo to TVweb, e-mail and data file sharingVoIPGaming

Figure 2. Asian Internet traffic forecast [8]

4/15

Video delivery with no quality degradation. Video flow resistance to congestion. Load balancing. Routing protocol that is stable, scalable, provides load balancing, and con-

gestion avoidance in Wireless Mesh Network. Routing metric that takes into account both congestion degree and distance

to gateway. Low routing control overhead.

Introduction-Goals

5/165/15

Potential based routing model

Field-based Routing analogy :

Design is based on physics theory. Network is an electrostatic field. Each node has a potential value. Boundary has zero potential. Gateway has the lowest potential. Potential is the routing metric.

Gateways

6/15

Pote

ntia

l

X- coordi-nates

Y- coordi-

nates

Poisson’s equation FDM + LE

(FAR) Model Design

Field-based Anycast Routing (FAR):

hop by hop routing. Potential information exchange in Hello messages. Packets in queue are positive charge. Positive charge (packets in the queue) follows the

lowest potential (nodes with lowest metric value).

441 1111

j,ij,ij,ij,ij,i q

Ni,j Ni+1,jNi-1,j

Ni,j+1

Ni,j-1

7/15

Potential is affected by: q (charge): Packets in queue.

if increased, potential increases to avoid congestion.

Potential of neighbors (Distance from gateway).

Sensitivity to traffic.

Potential of neighbors

ChargePermittivity

Metric parameters

Ni,j Ni+1,jNi-1,j

Ni,j+1

Ni,j-1

441 1111

j,ij,ij,ij,ij,i q

8/15

j,i

Convergence

Internet

L3 Router

L2 SW

L2 SWL2 SW

9/34

Procedure

-1

-1

-0.3-0.5

-0.6-0.4

Shortest possible path

Load-balancing + congestion avoidance

Gateway Load sharing

10/15

Performance evaluation

NS-2 Evalvid toolset [9][10] Foreman CIF video file 2 Mbps channel 100 nodes 2000mx2000m Node spacing: 200m Transmission range 250m Interference range 550m

Access point

Gateway

Video source

11/15

Performance evaluation

(b)

Figure 4. Received frame quality, (a) PSNR values, (b) Average frame packets delay.

12/15

Received frame no. 143.

FAR AODV

Performance evaluation

FAR AODV0

0.51

1.52

FAR AODV0

20406080

100

FAR AODV0

50000100000150000200000250000300000350000400000450000

0 500 1000 1500 2000 2500 3000 3500 4000 4500 5000 5500 60000.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4

Delay Delivery ratio Throughput

Packet delay in FAR

13/15

Seco

ndSe

cond

kbps

Conclusion

Designed a routing protocol for wireless mesh network based on physics theory to ensure an improved video quality delivery.

Utilized Poisson's equation and Finite Difference Method to calculate the potential as a metric.

Hybrid routing metric that combines distance and congestion degree. Achieves congestion avoidance, load balancing, and gateway load sharing. Simulation showed superiority of FAR in providing better video quality

compared with AODV.

14/15

References

[1] Y. Zhang, J. Luo, H. Hu, “Wireless Mesh Networking, Architecture, protocols and Standards,” Auerbach publications, pp. 9, 2007.

[2] L. J. Segerlind, Applied finite element analysis, 2nd edition, Chap. 5, John Wiley&Sons, 1984. [3] A. R. Mitchell and D. F. Griffiths, The Finite Difference Method in Partial Differential Equations, John Wi-

ley and Sons Ltd., New York, first edition,1980.[4] C. E. Perkins and E. M. Royer. Ad-hoc on-demand distance vector routing. In proceedings of the Second

IEEE Workshop on Mobile Computing Systems and applications (WMCSA), pages 90–100, New Orleans, LA, February 25–26, 1999. IEEE Press.

[5] Anindya Basu Alvin Lin Sharad Ramanathan, “Routing using potentials : A dynamic traffic-aware routing algorithm,” in the proceeding of SIGCOMM 2003.

[6] Rainer Baumann, Simon Heimlicher, Vincent Lenders†, Martin May, “HEAT: Scalable Routing in Wireless Mesh Networks Using Temperature Fields,”

[7] Vincent Lenders, Rainer Baumann “Link-diversity Routing: A Robust Routing Paradigm for Mobile Ad Hoc Networks”

[8] Cisco visual networking index: Forecast and Methodology, white paper, 2009 Cisco systems[9] J. Klaue, B. Rathke, and A. Wolisz,” EvalVid - A Framework for Video Transmission and Quality Evalua-

tion”[10] Chih-Heng Ke, et al “An Evaluation Framework for More Realistic Simulations of MPEG Video Transmis-

sion”, Journal of Information Science and Engineering.

15/15

Thank youQ&A

16/15

Appendix(A)-Downlink

We use source learning for downlink. Mesh points can use reverse path of uplinks

17/34

yh

xh

j,i1j,ij,ij,1iij

Appendix(b)-Potential calculation

21j,ij,i1j,i

2j,1ij,ij,1i

ij2

h2

h2

Poisson’s equation[2]:A partial differential equation that describes the behavior of charge distribution in electrostatic field

Finite Difference Method (FDM)[3]:Numerical method for approximating the solution to differential equations using finite difference equations to approximate derivatives

w2

44wh 1j,i1j,ij,1ij,1ij,i2

j,i

18/34