Design and Analysis of Advanced Replacement Policies for WWW Caching Kai Cheng, Yusuke Yokota, Yahiko Kambayashi Department of Social Informatics Graduate School of Informatics, Kyoto University

3 March 2000DEWS 2000, Biwako2 Contents Introduction Hybrid Replacement Policies for Web Caching Cache Structure for Hybridizing Various Policies PSS-W: Hybridizing LRU, LFU and SIZE Experimental Evaluation and Analysis Conclusion and Future Work Conceptual and Methodological Support for ADVACED POLICIES managing Large Cache Space, Object Space, implementing Sophisticated Control Logic, with high performance and low overhead

3 March 2000DEWS 2000, Biwako3 Introduction (1): Caching on the World Wide Web World Wide Web or World Wide Wait –Popular: 75% of Internet Backbone Traffic [1] –Costly: Repeated Transfer of Same Content Caching the Frequently Used Close to Users –Sharing Content Over Time by a Given User –Sharing Content Between Many Users Benefits from Web Caching –Improved Response Times –Reduced Network Load –Increased Server Throughput World Wide Wait

3 March 2000DEWS 2000, Biwako4 Introduction (2) What to Cache : Replacement Policies Cache All (  ) –Unrealistic: Persistent Cache -- New Contents Increase Ceaselessly –Unnecessary: Reference Locality -- Only A Small Part of Sites or Documents Popular Choose to Cache (  ) –Bring in Highly Potential Objects –Displace Less Potential Ones Replacement Policies –Objectives: Hit Rate, Byte Hit Rate, etc –Bases: Reference Locality; Size, Cost, etc

3 March 2000DEWS 2000, Biwako5 Hybrid Replacement Policies for Web Caching Why Hybrid Caching for Web –Manage Large Cache Space, Object Space –Implement Sophisticated Control Logic –Avoid “Cache Pollution” –Reduce “Early Eviction” Hybridize Several Policies (Examples) –Segmented LRU [2]: Hybridize LFU and LRU –Size-Adjusted LRU [3]: Hybridize SIZE and LRU –Segmented FIFO [4] : Hybridize LFU and FIFO

3 March 2000DEWS 2000, Biwako6 Cache Structure for Hybridizing Various Policies (1) Basic Cache: A Definition –Cache Space –Object Space –Replacement Policy –Constraints : admission, freshness, etc. Cache Structure –Monolithic: monolithic cache space, single object list –Distributed : segmented cache space, multiple objects lists S O C P

3 March 2000DEWS 2000, Biwako7 Cache Structure for Hybridizing Various Policies (2) Our Proposal Classification Rules –Clustering Web Objects based on sizes, types, usages –Localizing Replacement Decisions Unit Caches –Maintaining Similar Web Objects Central Cache –Solving Non-Determinism of Replacement Results –Controlling “Cache Pollution”

3 March 2000DEWS 2000, Biwako8 Cache Structure for Hybridizing Various Policies (3) Object Space Cache Space Classification Rule Unit Cache 0 Unit Cache 1 Unit Cache 2 Central Cache Evictions Hits

3 March 2000DEWS 2000, Biwako9 PSS-W: Hybridizing LRU, LFU and SIZE Size-Adjusted LRU : SIZE plus LRU –Largest First –Least Recently Used First Segmented LRU : LFU + LRU –Least Frequently Used First –Least Recently Used First PSS-W –Least Frequently Used First –Least Recently Used First –Largest First Max {Atime x Size} Max {Atime x Size / Nref} LRU LFU SIZE

3 March 2000DEWS 2000, Biwako10 Pyramidal Selection Scheme (PSS) For Size-Adjusted LRU Classification Rules Based on Size Only Objects Fixed in a Single LRU queue

3 March 2000DEWS 2000, Biwako11 Fig.1.Object With Uneven Accesses Being Deleted in PSS Popular Objects Aged Out in PSS

3 March 2000DEWS 2000, Biwako12 PSS with aWarded Sizes (PSS-W) Classification Rules Based on Size and Frequency Max {Size x Atime} Objects Moving among LRU queues

3 March 2000DEWS 2000, Biwako13 Fig. 2. Objects With Uneven Accesses Stay in PSS-W Popular Object Stay Long in PSS-W

3 March 2000DEWS 2000, Biwako14 4. Trace-Driven Simulations Fig. 3. Objects With More Accesses Tend More Popular

3 March 2000DEWS 2000, Biwako15 Fig.4. Significant Improvement in Byte Hit Rate Bye Hit Rate Improvement to PSS

3 March 2000DEWS 2000, Biwako16 Fig.4. No Harm To Hit Rate Better Hit Rate than PSS

3 March 2000DEWS 2000, Biwako17 Fig.6. Hit Rate Champion Outstanding Hit Rate

3 March 2000DEWS 2000, Biwako18 Fig.7. Competitive Byte Hit Rate Competitive Byte Hit Rate

3 March 2000DEWS 2000, Biwako19 Conclusion and Future Work Highlighted Importance of Hybrid Policies for Web Caching Proposed a Cache Structure to Facilitate Hybridizing Various Policies Developed PSS-W : Hybridizing SIZE, LRU and LFU Extending for Application-Level Metrics

3 March 2000DEWS 2000, Biwako20 References ① K. Tompson et al. Wide-Area Internet Pattern and Characteristics, IEEE Network, 11(6), 1997 ② R. Karedla, et al. Caching Strategies for Improving Disk System Performance, IEEE Computer, 27(3), 1994 ③ C. Aggarwal et al. Caching on the World Wide Web, IEEE KDE 11(1), 1999 ④ R. Tuner et al. Segmented FIFO Page Replacement. Proc. ACM SIGMETRICS’81 pp