1 / 30

The Effectiveness of Request Redirection on CDN Robustness

The Effectiveness of Request Redirection on CDN Robustness. Limin Wang Vivek Pai and Larry Peterson Princeton University. Motivation. Server infrastructure critical Failures are noticeable Consequences are serious CDNs are commonly used Robust service under heavy load

questa
Download Presentation

The Effectiveness of Request Redirection on CDN Robustness

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. The Effectiveness of Request Redirection on CDN Robustness Limin Wang Vivek Pai and Larry Peterson Princeton University OSDI 2002 Boston, MA

  2. Motivation • Server infrastructure critical • Failures are noticeable • Consequences are serious • CDNs are commonly used • Robust service under heavy load • News items, flash crowds • Overload-style attacks (DDoS) • We can exploit CDNs for this 5thOSDI, Boston, MA

  3. BBB.COM client WWW Service 5thOSDI, Boston, MA

  4. cache CCC.COM BBB.COM A A A A A A C C C C C C AAA.COM B B B B B B client server surrogate redirector Content Distribution Networks 5thOSDI, Boston, MA

  5. CCC.COM BBB.COM A A A A A A C C C C C C AAA.COM B B B B B B client server surrogate redirector Partial Replication on CDN 5thOSDI, Boston, MA

  6. CCC.COM BBB.COM A A A A C C C C AAA.COM B B B B client server surrogate redirector Partial Replication on CDN 5thOSDI, Boston, MA

  7. Often conflict Factors Affecting Redirection • Goals • Increase system throughput under load • Reduce response latencyperceived by clients • Server load • Pick least loaded server • Network proximity • Pick closest server • Cache locality • Pick server just served the object What’s the tradeoff across different loads? 5thOSDI, Boston, MA

  8. Contributions • New Class of CDN Redirection Strategies: Fine Dynamic Replication (FDR) • Selectively replicates URLs • Balances load, locality, bandwidth and proximity • 60-91% throughput improvement • Deters DDoS, absorbs flash crowds naturally • New Hybrid Simulator: NS-2 + LogSim • End-to-end — from SYN to sync() • Large scale simulations • 128 servers, 1000+ clients, ~70,000 req/sec 5thOSDI, Boston, MA

  9. Outline • Motivation and Contributions • Design Space of Redirection Strategies • Evaluation Methodology • Experimental Results • Conclusions and Ongoing Work 5thOSDI, Boston, MA

  10. Redirection Decision Dimensions • URL Hashing – decentralized, coherent • Different hashing schemes • Replication • More replicas  closer replicas • Too many replicas  working set overload • Load knowledge • How accurate? 5thOSDI, Boston, MA

  11. Background: Hashing Algorithms • Consistent Hashing (CHash) • hash(svr1), … hash(svrN) • hash(URL) • select “closest” server • Highest Random Weight (HRW) • hash(URL, svr1), … hash(URL, svrN) • sort hash values, get ordered server list • select server with highest hash value 5thOSDI, Boston, MA

  12. Strategies: Random • Random (Rand) • Requests randomly sent to surrogates • Baseline case • Assumes no pathological behavior 5thOSDI, Boston, MA

  13. Strategies: Static Replication • Replicated Consistent Hashing (R-CHash) • Each URL hashed to a fixed # of replicas • For each request, randomly selects one replica • Similar to Karger’s Consistent Hashing paper • Replicated Highest Random Weight (R-HRW) • Similar to R-CHash, but use HRW hashing • Minimizes two URLs having same set of replicas Approximates best published CDN algorithms Improve locality over Random 5thOSDI, Boston, MA

  14. Strategies: Static + Load Load-Aware Static Replication (fine grained) • LR-CHash • Estimates server load at redirectors • Picks up least-loaded server from server set • LR-HRW • Counterpart of LR-CHash Approximates CDN’s best load balancing behavior 5thOSDI, Boston, MA

  15. Strategies: Dynamic Replication (New) • Coarse Dynamic Replication (CDR) • HRW hashing  ordered server list • Walks list to find acceptably loaded server • # of replicas based on server load (estimated locally) • Fine Dynamic Replication (FDR) • # of replicas based on URL popularity, too • FDR-Global, reference scheme with global load info Dynamically balance load and locality 5thOSDI, Boston, MA

  16. Summary of Strategies 5thOSDI, Boston, MA

  17. Evaluation Methodology • Simulations • Merge NS-2 and LogSim • SYN to sync(), in detail • Work Load • Normal load • 1000 clients replaying Rice Trace • Flash crowds • 10-80% of 1000 clients hitting 10 URLs • Rest clients replaying Rice Trace 5thOSDI, Boston, MA

  18. C C C C C C C C C C C C C C WA MI MA S S S S S S S S S S IL PA CA NE DC CO R R R R R R R R R R R R R R R R R R GA SD CA TX – Server, – Client, – Router Simulation: Topology 128 servers, 1000 clients 5thOSDI, Boston, MA

  19. Dynamic Static + Load Static Capacity: Normal Load (64 svrs, 1000 clnts) 5thOSDI, Boston, MA

  20. Dynamic Static + Load Static Latency Measurement Points 5thOSDI, Boston, MA

  21. Latency: Normal Load, (64 svrs, 1000 clnts) Random Max:9.3K req/s 5thOSDI, Boston, MA

  22. Latency: Normal Load, (64 svrs, 1000 clnts) Static+Load (LR-HRW) Max: 25.4K req/s 5thOSDI, Boston, MA

  23. Handle Tail Separately (99% file  530KB) Static+Load (LR-HRW) Max: 25.4K req/s 5thOSDI, Boston, MA

  24. Server Resource Utilization (64 svrs) Under Normal Work Load at Individual Maximum Capacity 5thOSDI, Boston, MA

  25. Conclusions • New dynamic schemes work best • 60-91% improvement versus standard CDN • Without sacrificing latencies • Scale well, successful attacks more difficult • Bottleneck shifts from Disk to CPU/Network • Desired – shows selective replication works • More results in the paper • Normal workloads, flash crowd/DDoS traffic • Network Proximity and Heterogeneity • Large file effects 5thOSDI, Boston, MA

  26. Ongoing Work • PlanetLab deployment (CoDeeN networks) • Intel-funded overlay network, academic testing CDN • Currently running on 12 sites using proxy servers • Early stage, many more to do Traffic monitoring, capacity test, server management … • More simulations • Larger scale, faster simulated servers • More topologies (power-law, etc) • More traces, more elaborate client request model 5thOSDI, Boston, MA

  27. Thank you! For More Information http://www.cs.princeton.edu/nsg/cdn Acknowledgements • HP/Compaq/Intel • AlphaServer ES-40, 8GB RAM • rx4610 Server, Itanium, 16GB RAM • iMimic • DataReactor Proxy Servers 5thOSDI, Boston, MA

  28. Capacity Scalability Normal Load, 1000 normal clients 5thOSDI, Boston, MA

  29. 1 victim file, 1KB 10 victim files, avg 6KB Various Flash Crowds (32 servers) 5thOSDI, Boston, MA

  30. Capacity: Flash Crowd, 64 Servers 750 normal clients, 250 intensive clients Static + Load Dynamic Static 5thOSDI, Boston, MA

More Related