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N ETWORK -C ODING M ULTICAST N ETWORKS W ITH Q O S G UARANTEES Abdullah Şahin Hasan Saygın Arkan 10.01.2010.

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Presentation on theme: "N ETWORK -C ODING M ULTICAST N ETWORKS W ITH Q O S G UARANTEES Abdullah Şahin Hasan Saygın Arkan 10.01.2010."— Presentation transcript:

1 N ETWORK -C ODING M ULTICAST N ETWORKS W ITH Q O S G UARANTEES Abdullah Şahin Hasan Saygın Arkan

2 IntroductionIntroduction 1 BackgroundBackground 2 Unicast vs. MulticastUnicast vs. Multicast 3 Numerical ResultsNumerical Results 4 ConclusionConclusion 5 Outline

3 What we are going to present …

4 Define The Problem …

5 Solve for Unicast

6 Convert to Multicast

7 I NTRODUCTION

8 Introduction “Network-Coding Multicast Networks With QoS Guarantees” – Xuan, Y.: Lea, C.-T. – IEEE/ACM Transactions on Networking – 30 August 2010 Related Work Terms – QoS, Network Coding, unicast, multicast…

9 U NICAST & M ULTICAST C ONGESSION

10 Problem Definition

11

12 Internal Rooter Edge Router Edge Rouger Edge Router Egde Router Unicast Data Packet

13 Multicast Internal Rooter Edge Router Edge Rouger Edge Router Egde Router Data Packet

14 Unicast Solution t ij = traffic rate from i edge to j edge α i = ingress traffic & β i = egress traffic (α i, β i ) = (Θ α i ’, Θ β i ’ ) Task is maximizing Θ Edge Router α i = ingress traffic β i = egress traffic

15 Unicast Solution Σ t ij < α i ’ Σ t ij < β i ’ Not Applicable on Multicast – α = β for unicast, but not for multicast Edge Router

16 Multicast Solution G = multicast edge group = { s g, D(g), t g } source, destination set, data rate Binary Vectors: ϒ g (i) = 1, if i = s g δ g (j) = 1, if j € D(g) 0, otherwise0, otherwise

17 Multicast Solution Σ ϒ g (i). t g < α i ’ - ingress traffic Σ δ g (j). t g < β i ’ - egress traffic t ij = Σ (δ g (j). ϒ g (i). t g )

18 Optimal Routing i j x ij e

19 Optimal Routing

20

21 For IP networks – Calculation on weights MPLS-Type Explicit Routing Networks – Arbitrarily chosen nodes, and calculation of max loaded link

22 N UMERICAL R ESULTS

23 Numerical Results Constraint-Based Routing Approach Non-Blocking Based Approach – 15 Nodes, 62 directed links, capacity of 300. – 10 consecutive rejects = fully loaded – Number of receivers per multicast flow is random (binomial distribution [2, N-1], N is total edge

24 Numerical Results Nonblocking Multicast Networks b/a ratio, average fan-out = 3, 15 edge nodes

25 Numerical Results Nonblocking Multicast Networks b/a ratio, average fan-out = 4, 15 edge nodes

26 Numerical Results Nonblocking vs CBR 5 edge nodes, average fan-out = 3

27 Numerical Results Nonblocking vs CBR 15 edge nodes, average fan-out = 3

28 Numerical Results Nonblocking vs CBR 15 edge nodes, average fan-out = 4

29 Conclusion Better to have admission control at the edge, NOT inside it! Non-Blocking removes that need Main Problem – low throughput Optimal Paths in Unicast = Optimal Paths in Multicast Nonblocking with Network Coding

30 Q UESTIONS ?


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