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NETWORK-CODING MULTICAST NETWORKS WITH QOS

GUARANTEES

Abdullah ŞahinHasan Saygın Arkan

10.01.2010

• Introduction1• Background2• Unicast vs. Multicast3• Numerical Results4

• Conclusion5

Outline

What we are going to present …

Define The Problem …

Solve for Unicast

Convert to Multicast

INTRODUCTION

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…

UNICAST & MULTICASTCONGESSION

Problem Definition• Admission Control – How?• New QoS Architecture – Non-Blocking

Network! – No admission control

• Low throughput for multicast– Impractical

• Data Transmission– Transmission in Client – Local Server TRIVIAL– Transmission in Backbone PROBLEM!

Problem Definition– Transmission in Backbone PROBLEM!

Internal Rooter

Edge Router

Edge Rouger

Edge Router

Egde Router

Unicast

Data Packet

Data Packet

Multicast

Internal Rooter

Edge Router

Edge Rouger

Edge Router

Egde Router

Data PacketData Packet

Data Packet

Data Packet

Unicast Solution• tij = traffic rate from i edge to j edge

• αi = ingress traffic & βi = egress traffic

• (αi, βi) = (Θ αi’ , Θ βi

’)• Task is maximizing Θ

Edge Router

αi = ingress trafficβi = egress traffic

Unicast Solution

• Σ tij < αi’

• Σ tij < βi’

• Not Applicable on Multicast– α = β for unicast, but not for multicast

Edge Router

Multicast SolutionG = multicast edge group

= { sg, D(g), tg }source, destination set, data rate

Binary Vectors:ϒg(i) = 1, if i = sg δg(j) = 1, if j € D(g)

0, otherwise 0, otherwise

Multicast Solution

• Σ ϒg(i) . tg < αi’ - ingress traffic

• Σ δg(j) . tg < βi’ - egress traffic

• tij = Σ(δg(j) . ϒg(i) . tg)

Optimal Routing

i

j

xije

Optimal Routing

Optimal Routing

• For IP networks – Calculation on weights

• MPLS-Type Explicit Routing Networks– Arbitrarily chosen nodes, and calculation of max loaded

link

NUMERICAL RESULTS

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

Numerical Results

• Nonblocking Multicast Networks

• b/a ratio, average fan-out = 3, 15 edge nodes

Numerical Results

• Nonblocking Multicast Networks

• b/a ratio, average fan-out = 4, 15 edge nodes

Numerical Results

• Nonblocking vs CBR

• 5 edge nodes, average fan-out = 3

Numerical Results



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

QUESTIONS?