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System Software Lab 1 Enhancement and Validation of Squid ’ s Cache Replacement Policy John Delley Martin Arlitt Stephane Perret WCW99 김 재 섭 EECS System.

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Presentation on theme: "System Software Lab 1 Enhancement and Validation of Squid ’ s Cache Replacement Policy John Delley Martin Arlitt Stephane Perret WCW99 김 재 섭 EECS System."— Presentation transcript:

1 System Software Lab 1 Enhancement and Validation of Squid ’ s Cache Replacement Policy John Delley Martin Arlitt Stephane Perret WCW99 김 재 섭 EECS System Software Lab.

2 System Software Lab 2 Contents Introduction  Web Cache Architecture  Explicit proxies & Transparent proxies Role of the Replacement Policy Related Work  LRU, LFU, LFU-Aging, GDS, GDS-F Replacement Policy Implementation Simulation Simulation Results Conclusion & Critiques

3 System Software Lab 3 Introduction Web Cache Architecture Explicit Cache Transparent Cache

4 System Software Lab 4 Role of the Replacement Policy Determine future popularity of documents Use Resource in the most advantageous way WebProxy Workload Characterization  Tremendous breath and turnover in popular object Measures of Efficiency  Hit rate  Byte hit rate Bytes returned directly from the cache / Total byte accessed  CPU or IO system utilization  Average object retrieval latency Inversely proportional to object hit rate Hard to estimate

5 System Software Lab 5 Related Work LRU  Temporal locality  Single linked list  Removal of object =>O(1)  Update takes constant time LFU  Heap  Cache pollution LFU-Aging GDS(Greedy Dual Size)  Consider account size and cost function for retrieving object GDS-F

6 System Software Lab 6 Replacement Policy Implementation LFU with Dynamic Aging  Variant of LFU  Accommodate shift in the set of popular object  Insertion & Modification Reference count + cache age  No needs for parameterization GDS-Hits  Variant of GDS  Optimized for popular smaller objects Reference count/size + cache age

7 System Software Lab 7 Simulation Implementation experiences  Squid 1 LRU is implemented scanning a set of hash buckets and qsort Not precise  Squid 2 Heap based 36,000 unique objects 8M memory 100M Disk

8 System Software Lab 8 Simulation Results (Squid 1)

9 System Software Lab 9 Simulation Results (Squid 1)

10 System Software Lab 10 Simulation Results (Squid 2)

11 System Software Lab 11 Simulation Results (Squid 2)

12 System Software Lab 12 Conclusion & Critiques Conclusion  Accommodate shift in the set of popular object  Two frequency-based cache replacement policies Critique  In LFU-DA reference count can increase infinitely  GDS-Hits Only concentrate on hit rate by caching small object What are the benefits for user?  Ideas are too trivial and its simulations are also unreliable.  What ’ s difference between Squid 1 and Squid 2 ?


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