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Published byTimothy Clyde McLaughlin Modified over 9 years ago
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Evaluating Content Management Technique for Web Proxy Cache M. Arlitt, L. Cherkasova, J. Dilley, R. Friedrich and T. Jin 20005166 MinSu Shin
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Contents Introduction Data collection and Reduction Key Workload Characteristics Experimental Design Simulation Results Virtual caches Conclusion and Critique
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Introduction How effective are current proxy cache replacement policies for real workload? What new replacement policies? Performance metrics Hit rate : how many times hit? Byte hit rate : how many bytes hit?
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Data Collection Access logs from ISP Jan 3 rd, 1997 ~ May 31 st,1997 Backbone ISP Proxy Server
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Workload Characteristics Cacheable Object 92% of all requests were for cacheable objects
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Workload Characteristics Object Set Size 16 million unique cacheable objects 389GB : too much? Object Sizes Most of the requested objects are small Largest : 148MB video Large number of small object vs. small number of large object
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Workload Characteristics Recency of Reference 1/3 : within one hour 2/3 : within 24 hour Frequency of Reference 60% of the distinct objects were requested only single time Discriminate against one-timers Turnover Objects that were once popular are no longer requested
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Cache Replacement policies Least-Recently-Used (LRU) Consider only single workload characteristic SIZE – replace the largest object Some of the small object that never be accessed again – how? LFU (least frequently used) LFU-Aging
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Cache Replacement policies GreedyDual-Size (GD-Size) Replace the object with the lowest utility GD-Size(1) : maximize hit rate GD-Size(packet) : best byte-hit rate C : cost associated with bringing object i to cache S : object size L : running age factor, replace object f, L = K f
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Suggested Policies GDSF (GreedyDual-Size with Frequency) GD-Size not consider frequency LFU-Dynamic Aging LFU with inflation factor L
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Performance
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Virtual Cache Logical partition into N virtual caches Virtual caches have different management policies LFU-DAGDSF-Hits New access evicted replacement High byte hit rate + High hit rate reinserted
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Performance of Virtual cache
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VC1 has more impact on total performance
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Conclusion and Critique Good policy Investigate various policies Suggest some effective method Virtual server is key idea? Not Good Not counting operation complexity Not original idea about workload characteristic
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