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Introduction PowerPoint PPT Presentation

Introduction Related Work Pull-Based Freshness Policies Web Caching Synchronizing Collections Push-Based Policies 1. Static Web Content 2. Caching Dynamic Content 3. Caching Approximate Values Caching in Other Contexts Problem Definition

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Introduction

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Introduction l.jpg

Introduction


Related work pull based freshness policies web caching synchronizing collections l.jpg

Related WorkPull-Based Freshness Policies Web Caching Synchronizing Collections


Push based policies 1 static web content 2 caching dynamic content 3 caching approximate values l.jpg

Push-Based Policies1. Static Web Content2. Caching Dynamic Content3. Caching Approximate Values


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Caching in Other Contexts


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Problem Definition


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Pull-Based Model Freshness Dimension Latency Dimension Resource Dimension


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Optimization Problem


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Modeling Of Updates1. A model for Cyclic Updates2. Estimating Histories3. Cyclic and Acyclic Update Instantiations


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Architecture1. Client-Side2. Server-Side


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Pull-Based Freshness Policies1. Time-To-Live(TTL)2. Aggregate History Based Policy(AggHist)3.Individual History Based Policy(IndHist)Discussion


Comparison of ttl indhist and agghist 1 data traces world cup data email data l.jpg

Comparison of TTL,INDHIST, and AGGHIST1. Data Traces World Cup Data Email Data


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2. Setup World Cup Experiments E-Mail Experiments Metrics


Results accuracy of estimates world cup trace e mail traces l.jpg

Results Accuracy Of Estimates World Cup Trace E-Mail Traces


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Number Of Validations E-Mail Traces World Cup Trace


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Adaptive Pull-Based Policies1. Adaptive IndHist / AggHist Policy Results


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Adaptive IndHist / TTL Burst Detection and Adaptive IndHist/TTL policy Results


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Conclusions


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REFERENCES Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.1   Alonso, R., Barbara, D., and Garcia-Molina, H. 1990. Data caching issues in an information retrieval system. ACM Trans. Datab. Syst. 15, 3, 359--384. 2   Amiri, K., Tewari, R., Park, S., and Padmanabhan, S. 2002. On space management in a dynamic edge data cache. In Proceedings of the 5th International Workshop on the Web and Databases (WebDB). 37--42. 3   Arlitt, M. and Jin, T. 1998. 1998 world cup web site access logs. (Available at http://www.acm.org/sigcomm/ITA/). 4   Baralis, E., Paraboschi, S., and Teniente, E. 1997. Materialized view selection in a multidimensional database. In Proceedings of the 23rd Conference on Very Large Data Bases (VLDB). 156--165. 5   BlackBerry. 2005. BlackBerry Wireless Handhelds. http://www.blackberry.com. 6   Bright, L. 2003. Improving data delivery in wide area and mobile environments. Ph.D. dissertation, University of Maryland. 7   Bright, L., Bhattacharjee, S., and Raschid, L. 2002. Supporting Diverse Mobile Applications with Client Profiles. In Proceedings of ACM Workshop on Wireless Mobile Multimedia (WoWMoM). ACM, New York, 88--95. 8   Bright, L. and Raschid, L. 2002. Using latency-recency profiles for data delivery on the web. In Proceedings of the 28th Conference on Very Large Data Bases (VLDB). 550--561. 9   Candan, K., Li, W.-S., Luo, Q., Hsiung, W.-P., and Agrawal, D. 2001. Enabling dynamic content caching for database-driven web sites. In Proceedings of the ACM SIGMOD Conference. ACM, New York, 532--543. 10   Carney, D., Lee, S., and Zdonik, S. 2003. Scalable application-aware data freshening. In Proceedings of the 19th International Conference on Data Engineering (ICDE). 481--492. 11   Cate, V. 1992. Alex---A global filesystem. In Proceedings of the USENIX File System Workshop. 1--12. 12   Challenger, J., Iyengar, A., and Dantzig, P. 1999. A scalable system for consistently caching dynamic web data. In Proceedings of IEEE INFOCOM. IEEE Computer Society Press, Los Alamitos, CA, 294--303.


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