video streaming performance in a wireless mesh network with potential-based autonomous routing
DESCRIPTION
Video Streaming Performance in a Wireless Mesh Network with Potential-Based Autonomous Routing. Malaz Kserawi, Sangsu Jung, and J.-K. Kevin Rhee KAIST 2/25/2010 . Contents. Introduction : Wireless mesh network Video streaming Challenges and goals Proposed protocol (FAR) Model design - PowerPoint PPT PresentationTRANSCRIPT
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
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Contents
Introduction : Wireless mesh network Video streaming Challenges and goals
Proposed protocol (FAR) Model design Potential Procedure
Performance evaluation Conclusion References
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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
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• 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]
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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
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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
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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
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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
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j,i
Convergence
Internet
L3 Router
L2 SW
L2 SWL2 SW
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Procedure
-1
-1
-0.3-0.5
-0.6-0.4
Shortest possible path
Load-balancing + congestion avoidance
Gateway Load sharing
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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
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Performance evaluation
(b)
Figure 4. Received frame quality, (a) PSNR values, (b) Average frame packets delay.
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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
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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.
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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.
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Thank youQ&A
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Appendix(A)-Downlink
We use source learning for downlink. Mesh points can use reverse path of uplinks
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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
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