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CoBlitz: A Scalable Large-file Transfer Service (COS 461)

CoBlitz: A Scalable Large-file Transfer Service (COS 461). KyoungSoo Park Princeton University. Large-file Distribution. Increasing demand for large files Movies or software release On-line movie / downloads Linux distribution Files are 100MB ~ tens of GB One-to-many downloads

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CoBlitz: A Scalable Large-file Transfer Service (COS 461)

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  1. CoBlitz: A Scalable Large-file Transfer Service(COS 461) KyoungSoo Park Princeton University

  2. Large-file Distribution • Increasing demand for large files • Movies or software release • On-line movie/ downloads • Linux distribution • Files are 100MB ~ tens of GB • One-to-many downloads How to serve large files to many clients? • Content Distribution Network(CDN)? • Peer-to-peer system?

  3. What CDNs Are Optimized For Most Web files are small (1KB ~ 100KB)

  4. Why Not Web CDNs? • Whole file caching in participating proxy • Optimized for 10KB objects • 2GB = 200,000 x 10KB • Memory pressure • Working sets do not fit in memory • Disk access is 1000 times slower • Waste of resources • More servers needed • Provisioning is a must

  5. Peer-to-Peer? • BitTorrent takes up ~30% Internet BW 1. Download a “torrent” file 2. Contact the tracker 3. Enter the “swarm” network 4. Chunk exchange policy - Rarest chunk first or random - Tit-for-tat: incentive to upload - Optimistic unchoking 5. Validate the checksums up down peers torrent tracker Benefit: extremely good use of resources!

  6. Peer-to-Peer? • Custom software • Deployment is a must • Configurations needed • Companies may want managed service • Handles flash crowds • Handles long-lived objects • Performance problem • Hard to guarantee the service quality • Others are discussed later

  7. What We’d Like Is Large-file service with No custom client No custom server No prepositioning No rehosting No manual provisoning

  8. CoBlitz: Scalable Large-file CDN • Reducing the problem to small-file CDN • Split large-files into chunks • Distribute chunks at proxies • Aggregate memory/cache • HTTP needs no deployment • Benefits • Faster than BitTorrent by 55-86% (~500%) • One copy from origin serves 43-55 nodes • Incremental build on existing CDNs

  9. Origin Server HTTP RANGE QUERY coblitz.codeen.org chunk 1 chunk 2 chunk 1 chunk 2 chunk 1 chunk1 chunk 3 chunk 3 chunk 5 chunk 5 chunk 5 chunk 4 chunk 4 chunk 5 How It Works Only reverse proxy(CDN) caches the chunks! CDN = Redirector + Reverse Proxy DNS chunk1 chunk2 CDN CDN chunk3 Client Agent CDN CDN Agent Client CDN CDN chunk4 chunk5

  10. waiting done done Smart Agent • Preserves HTTP semantics • Parallel chunk requests CDN sliding window of “chunks” done CDN HTTP Client CDN CDN waiting waiting done CDN done no action waiting no action waiting no action waiting Agent

  11. Chunk Indexing: Consistent Hashing Problem: How to find the node responsible for a specific chunk? Static hashing f(x) = some_f(x) % n But n is dynamic for servers - node can go down - new node can join … N-1 0 … X1 X3 CDN node (proxy) Consistent Hashing F(x) = some_F(x) % N (N is a large but fixed number) Find a live node k, where |F(k) – F(URL) | is minimum Xk : Chunk request X2

  12. Operation & Challenges • Provides public service over 2.5 years • http://coblitz.codeen.org:3125/URL • Challenges • Scalability & robustness • Peering set difference • Load to the origin server

  13. Unilateral Peering • Independent proximity-aware peering • Pick “n” close nodes around me • Cf. BitTorrent picks “n” nodes randomly • Motivation • Partial network connectivity • Internet2, CANARIE nodes • Routing disruption • Isolated nodes • Benefits • No synchronized maintenance problem • Improve both scalability & robustness

  14. Both can reach Only can reach Only can reach Peering Set Difference • No perfect clustering by design • Assumption • Close nodes shares common peers

  15. Peering Set Difference • Highly variable App-level RTTs • 10 x times variance than ICMP • High rate of change in peer set • Close nodes share less than 50% • Low cache hit • Low memory utility • Excessive load to the origin

  16. Peering Set Difference • How to fix? • Avg RTT  min RTT • Increase # of samples • Increase # of peers • Hysteresis • Close nodes share more than 90%

  17. Reducing Origin Load • Still have peering set difference • Critical in traffic to origin • Proximity-based routing • Converge exponentially fast • 3-15% do one more hop • Implicit overlay tree • Result • Origin load reduction by 5x Origin server Rerun hashing

  18. Scale Experiments • Use all live PlanetLab nodes as clients • 380~400 live nodes at any time • Simultaneous fetch of 50MB file • Test scenarios • Direct • BitTorrent Total/Core • CoBlitz uncached/cached/staggered • Out-of-order numbers in paper

  19. 55-86% Throughput Distribution 1 0.9 BT-Core 0.8 Out-of-order staggered 0.7 0.6 Fraction of Nodes <= X (CDF) 0.5 Direct 0.4 BT - total 0.3 BT - core In - order uncached 0.2 In - order staggered 0.1 In - order cached 0 0 2000 4000 6000 8000 10000 Throughput(Kbps)

  20. 95% percentile: 1000+ secs faster Downloading Times

  21. Why Is BitTorrent Slow? • In the experiments • No locality – randomly choose peers • Chunk indexing – extra communication • Trackerless BitTorrent – Kademlia DHT • In practice • Upload capacity of typical peers is low • 10 to a few 100 Kbps for cable/DSL users • Tit for tat may not be fair • A few high-capacity uploaders help the most • BitTyrant[NSDI’07]

  22. Synchronized Workload Congestion Origin Server

  23. Addressing Congestion • Proximity-based multi-hop routing • Overlay tree for each chunk • Dynamic chunk-window resizing • Increase by 1/log(x), (where x is win size) if chunk finishes < average • Decrease by 1 if retry kills the first chunk

  24. Number of Failures

  25. BitTorrent: 20% > 5Mbps CoBlitz:70+% > 5Mbps Performance After Flash Crowds

  26. Data Reuse 7 fetches for 400 nodes, 98% cache hit

  27. Real-world Usage • 1-2 Terabytes/day • Fedora Core official mirror • US-East/West, England, Germany, Korea, Japan • CiteSeer repository (50,000+ links) • University Channel (podcast/video) • Public lecture distribution by PU OIT • Popular game patch distribution • PlanetLab researchers • Stork(U of Arizona) + ~10 others

  28. Fedora Core 6 Release • October 24th, 2006 • Peak Throughput 1.44Gbps Release point 10am 1 G Origin Server 30-40Mbps

  29. On Fedora Core Mirror List • Many people complained about I/O • Performing peak 500Mbps out of 2Gbps • 2 Sun x4200 w/Dual Operons, 2G mem • 2.5 TB Sata-based SAN • All ISOs in disk cache or in-memoy FS • CoBlitz uses 100MB mem per node • Many PL node disks are IDEs • Most nodes are BW capped at 10Mpbs

  30. Conclusion • Scalable large-file transfer service • Evolution under real traffic • Up and running 24/7 for over 2.5 years • Unilateral peering, multi-hop routing, window size adjustment • Better performance than P2P • Better throughput, download time • Far less origin traffic

  31. Thank you! More information: http://codeen.cs.princeton.edu/coblitz/ How to use: http://coblitz.codeen.org:3125/URL* *Some content restrictions apply See Web site for details Contact me if you want full access!

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