1. 1 Lifetime Behavior and its Impact on Web Caching X. Chen and P. Mohapatra, IEEE Workshop on Internet Applications (WIAPP), 1999. 김호중, CA Lab. Site 별, document type 별로 서로 다른 lifetime behavior 를 보인다는 논 문. Log 분석이 부실하므로 추천하지 않습니다. Site 별, document type 별로 서로 다른 lifetime behavior 를 보인다는 논 문. Log 분석이 부실하므로 추천하지 않습니다.

2. 2 / 16 Introduction Web cache consistency If-Modified-Since (IMS) Expires Time-To-Live (TTL) Fixed TTL Adaptive TTL Concerns only about traffic, not lifetime behavior

3. 3 / 16 Log Analysis (1/5) EDUCOMNEWS Summary of logs from 3 classes

4. 4 / 16 Log Analysis (2/5) Document types

5. 5 / 16 Log Analysis (3/5) Access pattern of different types in each class

6. 6 / 16 Log Analysis (4/5) Not-modified (304) / Get retrieval (200) Large NM/Get rate : TTL < lifetime Change of a document can be found quickly Waste of network resources

7. 7 / 16 Log Analysis (5/5) Lifetime calculation LT ij = MT i(j+1) - MT ij How to detect modification in a log? Change of file size Distorting factors Objects never changed in a log : lifetime? Results of frequently accessed objects are more accurate

8. 8 / 16 Results (1/4) Average lifetime Documents in EDU class are much more stable

9. 9 / 16 Results (2/4) EDU class GIF files are seldom modified 42% of access requests1.3% of HTML files Documents distributionAccess distribution

10. 10 / 16 Results (3/4) COM class Similar to EDU Popular documents are more mutable Documents distributionAccess distribution <50% of requests 94% of HTML files : <10 modifications

11. 11 / 16 Results (4/4) NEWS class More popular GIF has shorter lifetime How about JPG? Documents distributionAccess distribution 50% of access requests2.7% of HTML files

12. 12 / 16 Design Issues (1/3) Document classification Highly mutable documents Frequent modification Not worth caching Stable documents 44% of HTML and 78% of images are unchanged 20% of HTML and 80% of images are stable Short life documents Accessed or existed 1~2 days 1/3 of NEWS class, 20% of COM class others

13. 13 / 16 Design Issues (2/3) Two-state TTL algorithm Transient state : short TTL Stready state : long TTL Simulation Fixed TTL (1/4 of average lifetime) 19.8% stale data / 10.9% Not-Modified-Since Adaptive TTL (1/2 of elapsed time since last modification) 7.3% stale data / 25.4% Not-Modified-Since Two-state TTL +0.9% stale data / -3.1 Not-Modified-Since +2.8% cache hit rate

14. 14 / 16 Design Issues (3/3) Web-adjusted caching algorithm Stable data Best candidate for conventional caching algorithms Short time data LRU with 2-state expiration time Highly mutable data Avoid LFU TTL must be shorter Pushing may be better than caching

15. 15 / 16 Conclusion Lifetime-based workload characterization Different type, different class Different lifetime behavior Popular files tend to be changed frequently Cache algorithm design Document classification Two-state TTL algorithm

16. 16 / 16 Critique How to classify sites & documents at proxy? For popular sites & document? Reverse proxy cache Two-state TTL algorithm adaptive TTL with only min. & max. No relationship with document classification Plenty of data, lack of analysis