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Hint-based Acceleration of Web Proxy Cache

This document explores innovative methodologies for enhancing the performance of web proxy caches by minimizing cache-miss overhead. It introduces an accelerated web proxy model called Proxy Accelerator (PA) and discusses its operational efficiencies, particularly with embedded OS optimization. Key topics include hint representation using directory schemes and Bloom Filters for data management, ensuring hint consistency, maximizing cache hit ratios, and analyzing throughput improvements associated with these techniques. The study concludes that eager hint registration and Bloom Filter schemes significantly enhance proxy performance, especially in clustered environments.

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Hint-based Acceleration of Web Proxy Cache

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  1. Hint-based Acceleration of Web Proxy Cache Daniela Rosu Arun Iyengar Daniel Dias IBM T.J.Watson Research Center Unversity of Yuan Ze,Syslab Mike Tien mike@syslab.cse.yzu.edu.tw

  2. Outline • 1.Accelerated Web Proxy • 2.Hint Representation • 3.Hint Consistency • 4.Comparison • 5.Proxy Accelerator Cache • 6.Throughput Improvements • 7.Impact of Hint Management • 8.Summary • 8.Conclusion

  3. 1.Accelerated Web Proxy • To speed up proxy caches by reducing their cache-miss overhead. • Extended content-based router called a proxy accelerator(PA). • With embedded O.S optimized for communication.

  4. Accelerated Web Proxy(cont.)

  5. Accelerated Web Proxy(cont.)

  6. 2.Hint Representation • Accurate–information directory scheme (Hash Table) • Approximate-information based on Bloom Filters --bitmap(hint space) PA(entries,hash table) WP(collision counter)

  7. Hint Representation(cont.) --independently & interleaved

  8. 3.Hint Consistency • Protocol ensure that the information at the PA site reflects the content of the WP • Protocol choices --entity that identifies the updates --protocol initiator --rate of update messages --exchanged information • Previously proposed --WP-only update --eager hint register

  9. 4.Comparison

  10. 5.Proxy Accelerator Cache • PA should maximize the hit ratio --size , GDS(1) • WP should minimize the Network-related costs

  11. 6.Throughput Improvements(PA improve WP throughput)

  12. Throughput Improvements(cont.)(PA cpu speed affect improvement)

  13. Throughput Improvements(cont.)(PA-level cache improve throughput)

  14. 7.Impact of Hint Management

  15. Impact of Hint Management(cont.)

  16. Impact of Hint Management(cont.)

  17. Impact of Hint Management(cont.)

  18. Impact of Hint Management(cont.)

  19. 8.Summary • Bloom Filter-based scheme exhibits lower computation and communication overhead • WP meta-data may reduce its memory hit ratio • Hint look-up overheads are small with respect to the typical request processing overhead • Eagar hint registration reduces update-related overheads and prevents hit ratio reductions caused by update delay • False hit ratio is more significantly affected by hint representation than by update period

  20. 9.Conclusion • This miss ratios at proxy caches are often relatively high,we have developed a method to improve the performance of a cluster-based Web proxy by shifting some of its cache miss-related functionality to be executed on a proxy accelerator • Eagar registration is a “must” and that the Bloom Filter-based scheme is more appropriate than the directory scheme for large WP clusters or when PA and WP nodes have comparable power

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