Hint-based Acceleration of Web Proxy Cache Daniela Rosu Arun Iyengar Daniel Dias IBM T.J.Watson...
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Transcript of Hint-based Acceleration of Web Proxy Cache Daniela Rosu Arun Iyengar Daniel Dias IBM T.J.Watson...
![Page 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.](https://reader035.fdocuments.us/reader035/viewer/2022062805/5697c0251a28abf838cd4e67/html5/thumbnails/1.jpg)
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 [email protected]
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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
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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.
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Accelerated Web Proxy(cont.)
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Accelerated Web Proxy(cont.)
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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)
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Hint Representation(cont.)
--independently & interleaved
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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
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4.Comparison
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5.Proxy Accelerator Cache PA should maximize the hit ratio --size , GDS(1) WP should minimize the Network-
related costs
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6.Throughput Improvements(PA improve WP throughput)
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Throughput Improvements(cont.)(PA cpu speed affect improvement)
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Throughput Improvements(cont.)(PA-level cache improve throughput)
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7.Impact of Hint Management
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Impact of Hint Management(cont.)
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Impact of Hint Management(cont.)
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Impact of Hint Management(cont.)
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Impact of Hint Management(cont.)
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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
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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