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

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

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

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  1. 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

  2. Contents • Introduction : • Wireless mesh network • Video streaming • Challenges and goals • Proposed protocol (FAR) • Model design • Potential • Procedure • Performance evaluation • Conclusion • References

  3. Introduction-WMN Access point Gateway Figure 1. Wireless Mesh Network structure • Fixed infrastructure • Multihop packet forwarding • Provides wireless connection for a wide area • Provides Internet access to mobile hosts • Anycast routing

  4. Introduction-Video over WMN Figure 2. Asian Internet traffic forecast [8] • 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

  5. Introduction-Goals Video delivery with no quality degradation. Video flow resistance to congestion. Load balancing. Routing protocol that is stable, scalable, provides load balancing, and congestion avoidance in Wireless Mesh Network. Routing metric that takes into account both congestion degree and distance to gateway. Low routing control overhead. 5/16

  6. Potential based routing model Potential Gateways X- coordinates Y- coordinates 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.

  7. (FAR) Model Design • Field-basedAnycast 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). Ni,j+1 Ni-1,j Ni,j Ni+1,j Ni,j-1

  8. Metric parameters Ni,j+1 Ni-1,j Ni,j Ni+1,j Ni,j-1 Permittivity Charge Potential of neighbors • 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.

  9. Convergence

  10. Procedure Shortest possible path -1 Load-balancing + congestion avoidance -0.6 -0.4 Gateway Load sharing -0.5 -0.3 -1

  11. Performance evaluation Access point Gateway Video source 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

  12. Performance evaluation FAR AODV Received frame no. 143.

  13. Performance evaluation kbps Second Delay Delivery ratio Throughput Second Packet delay in FAR

  14. 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.

  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 Wiley 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] AnindyaBasu Alvin Lin SharadRamanathan, “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 Evaluation” [10] Chih-HengKe, et al “An Evaluation Framework for More Realistic Simulations of MPEG Video Transmission”, Journal of Information Science and Engineering.

  16. Thank you Q&A

  17. Appendix(A)-Downlink • We use source learning for downlink. • Mesh points can use reverse path of uplinks

  18. Appendix(b)-Potential calculation • 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

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