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Squirrel: A peer-to-peer web cache

Squirrel: A peer-to-peer web cache. Sitaram Iyer (Rice University) Joint work with Ant Rowstron (MSR Cambridge) Peter Druschel (Rice University). PODC 2002 / Sitaram Iyer / Tuesday July 23 / Monterey, CA. Web Caching. Latency, External traffic, Load on web servers and routers.

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Squirrel: A peer-to-peer web cache

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  1. Squirrel: A peer-to-peer web cache Sitaram Iyer (Rice University) Joint work with Ant Rowstron (MSR Cambridge) Peter Druschel (Rice University) PODC 2002 / Sitaram Iyer / Tuesday July 23 / Monterey, CA

  2. Web Caching • Latency, • External traffic, • Load on web servers and routers. Deployed at: Corporate network boundaries, ISPs, Web Servers, etc.

  3. Web Cache Browser Cache Browser Web Server Client Centralized Web Cache Browser Cache Browser Client Corporate LAN Internet

  4. Cooperative Web Cache Browser Cache Web Cache Browser Web Cache Web Server Client Web Cache Web Cache Web Cache Browser Cache Browser Client Corporate LAN Internet

  5. Decentralized Web Cache Squirrel Browser Cache Browser Web Server Client Browser Cache Browser Client Corporate LAN Internet

  6. Distributed Hash Table Peer-to-peer location service: Pastry nodes k1,v1 k2,v2 k3,v3 Operations: Insert(k,v) Lookup(k) Peer-to-peer routing and location substrate k4,v4 k5,v5 k6,v6 <key,value> • Completely decentralized and self-organizing • Fault-tolerant, scalable, efficient

  7. Why peer-to-peer? • Cost of dedicated web cache No additional hardware • Administrative effort Self-organizing network • Scaling implies upgrading Resources grow with clients

  8. Setting • Corporate LAN • 100 - 100,000 desktop machines • Located in a single building or campus • Each node runs an instance of Squirrel • Sets it as the browser’s proxy

  9. Mapping Squirrel onto Pastry Two approaches: • Home-store • Directory

  10. Internet LAN Home-store model client URL hash home

  11. Home-store model client home …that’s how it works!

  12. Directory model Client nodes always cache objects locally. Home-store: home node also stores objects. Directory: the home node only stores pointers to recent clients, and forwards requests.

  13. Internet LAN Directory model client home

  14. Directory model client home Randomly choose entry from table

  15. Directory: Advantages Avoids storing unnecessary copies of objects. Rapidly changing directory for popular objects seems to improve load balancing. Home-store scheme can incur hotspots.

  16. Directory: Disadvantages Cache insertion only happens at clients, so: • active clients store all the popular objects, • inactive clients waste most of their storage. Implications: • Reduced cache size. • Load imbalance.

  17. Directory: Load spike example • Web page with many embedded images, or • Periods of heavy browsing. Many home nodes point to such clients! Evaluate …

  18. Trace characteristics

  19. Total external traffic Redmond 105 No web cache 100 95 Directory Total external traffic (GB) [lower is better] Home-store 90 Centralized cache 85 0.001 0.01 0.1 1 10 100 Per-node cache size (in MB)

  20. Total external traffic Cambridge 6.1 No web cache 6 5.9 Directory Total external traffic (GB) 5.8 [lower is better] Home-store 5.7 5.6 Centralized cache 5.5 0.001 0.01 0.1 1 10 100 Per-node cache size (in MB)

  21. LAN Hops Redmond 100% 80% 60% % of cacheable requests 40% 20% 0% 0 1 2 3 4 5 6 Total hops within the LAN Centralized Home-store Directory

  22. LAN Hops Cambridge 100% 80% 60% % of cacheable requests 40% 20% 0% 0 1 2 3 4 5 Total hops within the LAN Centralized Home-store Directory

  23. Load in requests per sec Redmond 100000 Home-store Directory 10000 1000 Number of times observed 100 10 1 0 10 20 30 40 50 Max objects served per-node / second

  24. Load in requests per sec Cambridge 1e+07 Home-store Directory 1e+06 100000 10000 Number of times observed 1000 100 10 1 0 10 20 30 40 50 Max objects served per-node / second

  25. Load in requests per min Redmond 100 Home-store Directory 10 Number of times observed 1 0 50 100 150 200 250 300 350 Max objects served per-node / minute

  26. Load in requests per min Cambridge Home-store Directory 10000 1000 Number of times observed 100 10 1 0 20 40 60 80 100 120 Max objects served per-node / minute

  27. Fault tolerance Sudden node failures result in partial loss of cached content. Home-store: Proportional to failed nodes. Directory: More vulnerable.

  28. Fault tolerance If 1% of Squirrel nodes abruptly crash, the fraction of lost cached content is:

  29. Conclusions • Possible to decentralize web caching. • Performance comparable to a centralized web cache, • Is better in terms of cost, scalability, and administration effort, and • Under our assumptions, the home-store scheme is superior to the directory scheme.

  30. Other aspects of Squirrel • Adaptive replication • Hotspot avoidance • Improved robustness • Route caching • Fewer LAN hops

  31. Thanks.

  32. (backup) Storage utilization

  33. (backup) Fault tolerance

  34. (backup) Full home-store protocol other req other req req (LAN) (WAN) a : object or notmod from home b : req home client 1 b b : object or notmod from origin 2 3 origin server

  35. other req other req req a : no dir, go to origin. Also d a , d : req 1 1 home 2 2 client b : not-modified dir a , d origin c ,e : object 3 3 2 4 c ,e : req server 1 1 dele- gate object or e 3 not-modified origin e : cGET req 2 server (backup) Full directory protocol

  36. (backup) Peer-to-peer Computing Decentralize a distributed protocol: • Scalable • Self-organizing • Fault tolerant • Load balanced Not automatic!!

  37. Decentralized Web Cache Browser Cache Browser Web Server Browser Cache Browser Internet LAN

  38. Challenge Decentralized web caching algorithm: Need to achieve those benefits in practice! Need to keep overhead unnoticeably low. Node failures should not become significant.

  39. Peer-to-peer routing, e.g., Pastry Peer-to-peer object location and routing substrate = Distributed Hash Table. Reliably maps an object key to a live node. Routes in log16(N)steps (e.g. 3-4 steps for 100,000 nodes)

  40. Home-store is better! Simpler home-store scheme achieves load balancing by hash function randomization. Directory scheme implicitly relies on access patterns for load distribution.

  41. Directory scheme seems better… Avoids storing unnecessary copies of objects. Rapidly changing directory for popular objects results in load balancing.

  42. Interesting difference Consider: • Web page with many images, or • Heavily browsing node Directory: many pointers to some node. Home-store: natural load balancing. Evaluate …

  43. Fault tolerance When a single Squirrel node crashes, the fraction of lost cached content is:

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