1. Datacast: A Scalable and Efficient Reliable Group Data Delivery Service for Data Centers Jiaxin Cao, Chuanxiong Guo, Guohan Lu, Yongqiang Xiong, Yixin Zheng, Yongguang Zhang, Yibo Zhu, Chen Chen University of Science and Technology of China Microsoft Research Asia Tsinghua University University of California, Santa Barbara University of Pennsylvania

2. Reliable Group Data Delivery The problem of RGDD is: 010203101112132021222330313233 00 given a data source, Src,and a set of receivers, R 1, R 2, …, R n, how to reliably transmit bulk data from Src to all the receivers? In a data center network, Data

3. Reliable Group Data Delivery RGDD is important in DCNs: Bootstrapping or OS upgrading. Distributed file systems, e.g., GFS. VM setup. And more...

4. Reliable Group Data Delivery A good RGDD design should have the following properties: Scalable (large group numbers and large group sizes) High bandwidth efficiency

5. Existing solutions to RGDD Existing solutions can be classified into two categories: Reliable IP multicast.Not scalable, e.g., ACK implosion. End-host based overlays.Low bandwidth efficiency. None of the existing systems can perfectly achieve RGDD.

6. New opportunities in DCN Recently, there are two clear trends in DCN: Multiple edge-disjoint Steiner trees for RGDD. Practical packet caching abilities in network devices. We can cache packet! 00 010203 10 111213 20 212223 30 313233 00 102030 01 112131 02 122232 03 132333

7. The architecture of Datacast Fabric Manager Master i Master j Src R1R1 R2R2 IMD Src R1R1 R2R2 R3R3 R4R4 RGDD Group i 1 RGDD Group i 2 RGDD Group i n Network Topology How to calculate multiple Steiner trees? How to efficiently transmit data in each Steiner tree?

8. Multiple edge-disjoint Steiner trees in DCN Our multiple Steiner trees algorithm takes three steps: 1.Use specific algorithms to construct spanning trees. 2.Prune the spanning trees. 3.Use Breath First Search(BFS) to repair the trees broken by network failures. This algorithm is fast (O(k|V|) + O(|E|) + O(k|E|)) and efficient.

9. Datacast transport protocol Datacast is built on top of Content Centric Network (CCN): 00010203 10111213 20212223 30313233 Inst Data Inst Data Inst Data Inst Data

10. Datacast transport protocol

14. Simulation: multiple Steiner trees algorithm We tested our algorithm in Fattree(24,3), BCube(8, 3), Torus(16, 3) under the link failure rates (LFR) of 1%, 3% and 5%. Running times.Steiner tree numbers.

15. Simulation: Datacast congestion control 00 010203 10 111213 20 212223 30 313233 00 102030 01 112131 02 122232 03 132333 Steiner Tree 1.Steiner Tree 2.

16. Simulation: Datacast congestion control Based on Theorem 1, Datacast needs 125KB caches to work at full rate. Based on Theorem 2, the duplicate data ratios is 1.19%. Cache Size (KB)Throughput(Mbps)Duplicate Data Ratio (%) 891.3801.15 3295.0761.14 12898.7991.11 51298.7991.10 204898.7991.12

17. Simulation: Datacast congestion control Compare with BitTorrent. Fattree.BCube.Torus.

18. Experiment: Datacast congestion control

19. We compare Datacast with BitTorrent. We use both of them to transmit 4GB data. Finish time (s)Link stress Datacast16.91.01 BitTorrent521.39

20. Related work Reliable IP multicast Pgm congestion control (pgmcc) Active Reliable Multicast (ARM) End-host based overlays SplitStream End System Multicast Cornet

21. Conclusion In this paper, we propose Datacast which Calculates multiple edge-disjoint Steiner trees in DCNs Uses CCN to turn hard group states to soft packet caching Uses a simple rate-based AIMD congestion control algorithm to achieve high efficiency Datacast is scalable and achieves high bandwidth efficiency

22. Thank you!