1. 1 Communication Networks Prof. Dr. U. Killat Traffic Engineering for Hard Real Time Multicast Applications Using Genetic Algorithm Shu Zhang, Lothar Kreft and Ulrich Killat 15.03.2005

2. 2 Communication Networks Prof. Dr. U. Killat Problem Setting …… End Systems 1 Gateway 1 Gateway 2 End Systems N Gateway M N (N>100) multicast groups Guarantee of end-to-end delay bounds

3. 3 Communication Networks Prof. Dr. U. Killat Index 1.Problem setting 2.EDF scheduler and delay bounds 3.Genetic encoding 4.The performance of our algorithm 5.Conclusion

4. 4 Communication Networks Prof. Dr. U. Killat The Earliest Deadline First Scheduler EDF Scheduler Packet of flow 'j' arrive at time t 2 Packet of flow 'i' arrive at time t 1 Assigned a deadline of t 1 +d i Assigned a deadline of t 2 +d j d i, d j : predefined delay bounds for flow i, j on this link. Deadlines are guaranteed when the flows are "schedulable".

5. 5 Communication Networks Prof. Dr. U. Killat The Schedulability Function Ct Schedulability function F(t): F(t) 0 t d 1,j d 2,j d 3,j A 1 (t-d 1,j )A 2 (t-d 2,j )A 3 (t-d 3,j ) All flows are schedulable iff.

6. 6 Communication Networks Prof. Dr. U. Killat The Scheduling and Bandwidth Margins With token bucket as traffic envelope, we define the scheduling margin: define bandwidth margin: => Optimization objectives F(t) 0 t d 1,j d 2,j d 3,j σ1σ1 σ2σ2 σ3σ3 ρ1ρ1 ρ2ρ2 ρ3ρ3 SjSj BjBj

7. 7 Communication Networks Prof. Dr. U. Killat Assigning Delay Bounds to Links delay bounds assignment procedure

8. 8 Communication Networks Prof. Dr. U. Killat Creating Alternative Routing Candidates 0 1 2 3 4 6 5 0 1 2 3 4 6 5 Shortest path tree with original topology Shortest path tree with topology without link 1-2

9. 9 Communication Networks Prof. Dr. U. Killat Genetic Encoding Gene: Routing tree Chromosome: Complete routing planning Fitness: Scheduling and bandwidth margins Chromosome A Chromosome B 1 1 23 N 23 N … … A gene Chromosome A' Chromosome B' 1 12 3 N 2 3 N … … Crossover Mutation Parents: Offspring:

10. 10 Communication Networks Prof. Dr. U. Killat Performance of the Planning Algorithm Bandwidth margin (byte/ms) Scheduling margin (byte) 210 multicast groups Generation

11. 11 Communication Networks Prof. Dr. U. Killat Performance of the Planning Algorithm Bandwidth margin (byte/ms) Scheduling margin (byte) 350 multicast groups Generation

12. 12 Communication Networks Prof. Dr. U. Killat Conclusion: 1.Hard real time QoS can be guaranteed by proper scheduling mechanism and routing selection. 2.A traffic engineering approach using genetic algorithm has been developed. 3.The performance of the algorithm shows its effectiveness.

13. 13 Communication Networks Prof. Dr. U. Killat The Traffic Envelopes and Solutions for the Multi-node Case EDF Scheduler Flow j with envelope A j (τ) Flow i with envelope A i (τ) Flow j with envelope A j (τ+d j ) Flow i with envelope A i (τ+d i ) EDF Scheduler Flow j Flow i Shaper with envelope A j (τ) Shaper with envelope A i (τ) Flow j with envelope A j (τ+d j ) Flow i with envelope A i (τ+d i ) (1) (2)

14. 14 Communication Networks Prof. Dr. U. Killat Comparison to a naive approach Bandwidth margin (byte/ms) Scheduling margin (byte) 210 multicast groups Computation time (minutes)