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Wei-Chu Lin, Gen-Hen Liu, Kuan-Tsen Kuo, and Charles H.-P. Wen

DENDIST-FM: Flow Migration in Routing of OpenFlow-based Cloud Networks. Wei-Chu Lin, Gen-Hen Liu, Kuan-Tsen Kuo, and Charles H.-P. Wen Dept. Electrical and Computer Engineering National Chiao Tung University, Taiwan. Outline. Introduction Related Work and Motivation

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Wei-Chu Lin, Gen-Hen Liu, Kuan-Tsen Kuo, and Charles H.-P. Wen

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  1. DENDIST-FM: Flow Migration in Routing of OpenFlow-based Cloud Networks Wei-Chu Lin, Gen-Hen Liu, Kuan-Tsen Kuo, and Charles H.-P. Wen Dept. Electrical and Computer Engineering National Chiao Tung University, Taiwan

  2. Outline • Introduction • Related Work and Motivation • Flow Migration Mechanism in SDN • Experimental Result • Conclusion

  3. About Cloud Datacenters (1/2) • For cloud datacenter networks (DCNs), researches frequently focus on issues of • Topology • Routing • Topology research targets DCN scalability • Porland [1] • Killer Fabric [2] • Jellyfish [3]

  4. About Cloud Datacenters (2/2) • Routing research targets various performance perspectives and different applications • Hash-based Routing (HBR) • ENDIST • D2ENDIST • Evolutionary Software-Defined Networking (SDN) has emerged in cloud systems and resolves many networking problems

  5. More About SDN • Software-defined networking (SDN) separates control plane and data plane of network • embrace more flexible routing on per-flow basis • Flows can be defined cross layers MAC Source Address Ethernet Type IP Source Address IP Protocol TCP Source Port Number VLAN ID MAC Destination Address IP Destination Address TCP Destination Port Number Layer-4 Layer-3 Layer-2

  6. Outline • Introduction • Related Work and Motivation • Flow Migration Mechanism in SDN • Experimental Result • Conclusion

  7. Dynamic Routing in DCNs • D2ENDIST is a layer-2 routing algorithm and consists of • Disjoint ENDIST routing • Reroute by dynamic weighting

  8. SPB on Traditional Network Path 1: A – 6 – 2 – 0 – 4 – 8 – E Path 2: B – 6 – 2 – 0 – 4 – 8 – E Path 3: A – 6 – 2 – 0 – 4 – 8 – F Path 4: B – 6 – 2 – 0 – 4 – 8 – F Path 5: C – 7 – 2 – 0 – 4 – 8 – E Path 6: C – 7 – 2 – 0 – 4 – 8 – F Path 7: C – 7 – 2 – 0 – 4 – 9 – G Path 8: C – 7 – 2 – 0 – 4 – 9 – H Path 9: A – 6 – 2 – 7 – C Path 10: A – 6 – 2 – 7 – D 6 Over-Utilized Links: 6-2, 7-2, 2-0, 0-4, 4-8 0 1 Core 8 8 2 3 4 5 Aggr. 6 6 6 2 6 7 8 9 Edge A B C D E F G H Host P.S. Definition of over-utilized links: No more than 6 in core-aggr. No more than 3 in aggr-edge.

  9. D2ENDIST on Traditional Network Path 1: A – 6 – 2 – 0 – 4 – 8 – E Path 2: B – 6 – 2 – 0 – 4 – 8 – E Path 3: A – 6 – 2 – 0 – 4 – 8 – F Path 4: B – 6 – 2 – 0 – 4 – 8 – F Path 5: C – 7 – 3 – 1 – 5 – 8 – E Path 6: C – 7 – 3 – 1 – 5 – 8 – F Path 7: C – 7 – 3 – 1 – 5 – 9 – G Path 8: C – 7 – 3 – 1 – 5 – 9 – H Path 9: A – 6 – 3 – 7 – C Path 10: A – 6 – 3 – 7 – D 3 Over-Utilized Links: 6-2, 7-2, 2-0, 0-4 , 4-8,7-3 0 1 Core 4 4 4 4 2 3 4 5 Aggr. How about D2ENDIST on SDN? 4 6 4 2 2 2 6 7 8 9 Edge A B C D E F G H Host

  10. Motivation • SDN makes network control directly programmable across different layers • Routing can be more flexible • Path modification can be easier • Apply D2ENDIST to a OpenFlow-based cloud network • compare performances between dynamic-routing and flow-control mechanisms

  11. Outline • Introduction • Related Work and Motivation • Flow-Migration Mechanism in SDN • Traffic-aware Flow Migration (FM) • Experimental Result • Conclusion

  12. Dynamic Reroute in D2ENDIST • D2ENDIST applies reroute strategy to balance traffic load dynamically 0 1 0 1 3 3 3 3 2 3 4 5 2 3 4 5 2 5 3 3 2 3 6 7 8 9 6 7 8 9 4 2 3 4 3 2 3 3 A B C D E F G H A B C D E F G H

  13. D2ENDIST in SDN More Powerful!! Path 1: A – 6 – 2 – 0 – 4 – 8 – E Path 2: B – 6 – 3 – 1 – 5 – 8 – E Path 3: A – 6 – 2 – 0 – 4 – 8 – F Path 4: B – 6 – 3 – 1 – 5 – 8 – F Path 5: C – 7 – 2 – 0 – 4 – 8 – E Path 6: C – 7 – 2 – 0 – 4 – 8 – F Path 7: C – 7 – 3 – 1 – 5 – 9 – G Path 8: C – 7 – 3 – 1 – 5 – 9 – H Path 9: A – 6 – 2 – 7 – C Path 10: A – 6 – 3 – 7 – D 1 Over-Utilized Link: 6-2, 7-3, 4-8 0 1 Core 4 4 4 4 2 3 4 5 Aggr. But that’s only theoretical. Why? 3 3 4 2 3 3 2 6 7 8 9 Edge A B C D E F G H Host

  14. D2ENDIST Problem in SDN • The shortest path algorithm (SPB) takes O(ns2) time (ns: # switches) • D2ENDIST is based on all-pairs shortest path which takes O(ns3) • Apply D2ENDIST to each flow, grows to O(nf x ns3)=O(ns5) if nf ~ ns2(nf: # flows) • Therefore, propose “Traffic-aware Flow Migration”, with only O(ns2)

  15. Example of Flow Migration • Routing path: A-6-2-0-4-8-E (1) Reroute path: A-6-2-1-4-8-E (2) Reroute path: A-6-3-0-4-8-E 0 0 1 1 9 8 5 5 4 2 5 3 2 2 3 3 4 4 5 5 6 5 3 4 4 4 4 4 6 4 6 4 5 5 5 5 4 6 5 6 6 6 7 7 8 8 9 9 5 5 3 3 A A B B C C D D E E F F G G H H

  16. DENDIST-FM:FM +DENDIST • DENDIST-FM • DENDIST: disjoint paths (for balancing the traffic load initially) • Flow Migration: dynamic reroute • Compare with D2ENDIST, • traffic-aware flow migration is a more efficient for dynamic reroute • Only requires O(ns2)

  17. Flowchart of Flow Migration

  18. D2ENDIST in SDN (Recap) Path 1: A – 6 – 2 – 0 – 4 – 8 – E Path 2: B – 6 – 3 – 1 – 5 – 8 – E Path 3: A – 6 – 2 – 0 – 4 – 8 – F Path 4: B – 6 – 3 – 1 – 5 – 8 – F Path 5: C – 7 – 2 – 0 – 4 – 8 – E Path 6: C – 7 – 2 – 0 – 4 – 8 – F Path 7: C – 7 – 3 – 1 – 5 – 9 – G Path 8: C – 7 – 3 – 1 – 5 – 9 – H Path 9: A – 6 – 2– 7 – C Path 10: A – 6 – 3 – 7 – D 1 Over-Utilized Link:6-2, 7-3, 4-8 0 1 Core 4 4 4 4 2 3 4 5 Aggr. 3 3 4 2 3 3 2 6 7 8 9 Edge A B C D E F G H Host

  19. DENDIST-FM in SDN Path 1: A – 6 – 2 – 0 – 4 – 8 – E Path 2: B – 6 – 3 – 1 – 5 – 8 – E Path 3: A – 6 – 2 – 0 – 4 – 8 – F Path 4: B – 6 – 3 – 1 – 5 – 8 – F Path 5: C – 7 – 2 – 0 – 5 – 8 – E Path 6: C – 7 – 2 – 0 – 4 – 8 – F Path 7: C – 7 – 3 – 1 – 5 – 9 – G Path 8: C – 7 – 3 – 1 – 5 – 9 – H Path 9: A – 6 – 2– 7 – C Path 10: A – 6 – 3 – 7 – D 0 Over-Utilized Link: None!!! 0 1 Core 4 4 3 4 1 2 3 4 5 Aggr. 3 3 3 2 3 3 3 6 7 8 9 Edge A B C D E F G H Host

  20. Outline • Introduction • Related Work and Motivation • Flow Migration Mechanism in SDN • Experimental Result • throughput comparison • reroute period • Conclusion

  21. Simulation Environment • NS2 provides source routing which can designate the routing path as flow-aware routing and thus is adopted in this work • A 3-tier fat-tree Topology • 5 core-level switches • 10 aggregate-level switches • 50 edge-level switches • 200 hosts • FTP traffic flows

  22. Throughput Comparison • Fat-Tree (5–10–50–200) + #flow=1000

  23. Reroute Period • Higher frequent polling  better throughput • even close to the theoretical throughput of D2ENDIST ( but with lower complexity)

  24. Outline • Introduction • Related Work and Motivation • Flow Migration Mechanism in SDN • Experimental Results • Conclusion

  25. Conclusion • SDN demonstrates its potential to enable a better network for DCN • Dynamic routing like D2ENDIST can perform better • But suffer from high complexity • DENDIST-FM integrates concepts of (1) disjoint path and (2) flow migration to yield • Better performance with • Lower complexity • Now, apply DENDIST-FM to Floodlight as future work

  26. Thank you for listening!

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