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,

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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 논문 .

Log 분석이 부실하므로 추천하지 않습니다 .

Site 별 , document type 별로 서로 다른 lifetime behavior 를 보인다는 논문 .

Log 분석이 부실하므로 추천하지 않습니다 .

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Introduction Web cache consistency

If-Modified-Since (IMS) Expires Time-To-Live (TTL)

Fixed TTL Adaptive TTL

Concerns only about traffic, not lifetime behavior

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Log Analysis (1/5)

EDU COM NEWS

Summary of logs from 3 classes

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Log Analysis (2/5) Document types

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

class

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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

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Log Analysis (5/5) Lifetime calculation

LTij = MTi(j+1) - MTij

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

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Results (1/4) Average lifetime

Documents in EDU class are much more stable

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Results (2/4) EDU class

GIF files are seldom modified

42% of access requests1.3% of HTML files

Documents distribution Access distribution

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Results (3/4) COM class

Similar to EDU Popular documents are more mutable


<50% of requests94% of HTML files :<10 modifications

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Results (4/4) NEWS class

More popular GIF has shorter lifetime How about JPG?


50% of access requests2.7% of HTML files

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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

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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

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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

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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

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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