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Squirrel: A decentralized peer-to-peer web cache

Squirrel: A decentralized peer-to-peer web cache. Paul Burstein 10/27/2003. Outline. Overview Design Evaluation Discussion. Traditional Web Caching. Goals Reduce browser latency Reduce aggregate bandwidth Reduce load on web servers Deployment Dedicated centralized machines

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Squirrel: A decentralized peer-to-peer web cache

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  1. Squirrel: A decentralized peer-to-peer web cache Paul Burstein 10/27/2003

  2. Outline • Overview • Design • Evaluation • Discussion

  3. Traditional Web Caching • Goals • Reduce browser latency • Reduce aggregate bandwidth • Reduce load on web servers • Deployment • Dedicated centralized machines • Placed at local network boundaries

  4. Squirrel Web Caching • Decentralized caching • Desktops cooperate in a peer-to-peer fashion • Mutual sharing between hosts • Hosts browse and cache

  5. Centralized Dedicated Hardware Cost Administration Handling load bursts Single point of failure Decentralized No additional hardware More users  more resources Automatic scaling Self organizing Easy deployment Pros

  6. Assumptions • Cooperative hosts • No security issues • Link and node failures • Nodes are in single geographic location • Low internal network latencies

  7. Outline • Overview • Design • Evaluation • Discussion

  8. Design Goals • Target environment: 100 - 100,000 machines • Goal: Achieve performance comparable to centralized cache

  9. Design Overview • Built on top of Pastry • Objects have 128-bit objectIds • SHA-1 hash of URL • Mapped to home node with closest nodeId • Requests: • GET – new request • cGET – conditional • Two schemes • Home-store • Directory

  10. Home-store • Objects stored at client cache and home node • External requests come through home node • Cache replacement • All objects are considered • home node fresh • home node stale

  11. Directory • Home node keeps a directory of pointers • Randomly redirect to delegates • no directory, add new delegate • cGET not modified • delegate fresh, get from delegate • cGET and stale, update • GET and stale, update

  12. Outline • Overview • Design • Evaluation • Discussion

  13. Evaluation Characteristics • Compare two schemes and dedicated cache • Performance • Latency • External bandwidth • Hit ratio • Overhead • Load • Storage • Fault Tolerance

  14. Trace Characteristics

  15. Bandwidth and Hit ratio • Bytes transferred to origin servers and back • correlated with hit rate • Centralized cache with infinite storage • 100MB cache per node achieves optimal rates • 10MB in-memory cache is reasonable • Directory scheme • Active nodes suffer from eviction • Distributed LRU is worse than centralized • Home-store • More total storage required

  16. Latency • User-perceived time for a response • With comparable hit ratios, only consider internal hops • Many requests can be satisfied locally, with 0 hops • Directory scheme latency is up to one hop greater • Some requests can be satisfied by home node • Squirrel Latency • Based on Pastry hops on cache hit • Overshadowed on cache miss

  17. Load on Nodes(1/2) • Bursty behavior observations • Max objects served per second • Up to 48 and 55 objects per second served for the two traces • Directory scheme • One delegate can get bombarded with requests from many home nodes • Home-store scheme • Replicate objects at request threshold

  18. Load on Nodes(2/2) • Sustained load measurements • Max objects/minute • Average load in any second or minute: • 0.31 objects/minute • Redmond trace, both models

  19. Fault Tolerance • Internet connection loss • Internal partitioning • Individual failure • Desktop shutdown or reboot • Graceful shutdown • Pastry aided content transfer • Directory scheme • More vulnerable to failures

  20. Results • The home-store models seems to outperform the directory model • Hit ratio • Load balancing • Internal network latency • Compared to centralized cache?

  21. Outline • Overview • Design • Evaluation • Discussion

  22. Discussion • Would this be deployed in a corporate network?

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