2004

221-239

222 Electronic Commerce Studies

A Cache Document Replacement Mechanism Considering Document Added-Value

Toly Chen

Feng Chia University

Ju-Chi Huang

Chaoyang University of Science and Technology

Abstract

Most traditional cache document replacement policies are focused on

the efficiency respect and cache documents are replaced according to their

last access times, request frequencies, and sizes. However, the goal of an

EC website is to make profits, and the information that can be cached to a

user should also promote the user to consume. For this reason, a new cache

document replacement policy also considering the value added to the

website by caching a document to a user is proposed in this study. As a

result, the new policy considers four attributes of every document

including the last access time, request frequency, size, and value added to

the website. To evaluate the added value to the EC website by caching a

document, some data and web mining techniques are applied. Firstly, the

aggregation tree of all users’ browsing paths is analyzed to found out the

relationship between each web page and the payment page. Then the

strength of such a relationship is assessed with the association rule and the

absolute-value distance. Based on them, the added value of every cache

document can be derived according to an equation modified from the

traditional GDSF cache replacement policy. When cache replacement

occurs, the document with the smallest added value will be firstly taken

away from the cache. In this way, web pages that are more frequently

associated with consumption behaviors will be cached to the users with

higher probabilities, and users with consumption behaviors (i.e. consumers)

can be provided with better caching performance than normal users. An

experimental EC website has been constructed in this study to generate

some data for evaluating the effectiveness of the proposed mechanism. In

the respects of “customer hit rate” and “customer byte hit rate”, the new

mechanism outperformed all traditional cache document replacement

policies.

Keywords: E-Commerce, Cache Document Replacement Policy, Added

Value

224 Electronic Commerce Studies

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226 Electronic Commerce Studies

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228 Electronic Commerce Studies

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230 Electronic Commerce Studies

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232 Electronic Commerce Studies

4

Cache size(Kb)

Hit rate(%)

LFU

LRU

SIZE

GDSF

0%

10%

20%

30%

40%

50%

60%

70%

25 50 75 100

125

150

Cache size(Kb)

Byte hit rate(%)

LFU

LRU

SIZE

GDSF

0%

5%

10%

15%

20%

25%

30%

35%

40%

45%

25 50 75 100

125

150

Cache size(Kb)

Customer hit

rate(%)

LFU

LRU

SIZE

GDSF

234 Electronic Commerce Studies

0%

5%

10%

15%

20%

25%

30%

35%

25 50 75 100

125

150

Cache size(Kb)

Customer byte

hit rate(%)

LFU

LRU

SIZE

GDSF

Hit rate Byte hit

rate

Customer

hit rate

Customer

byte hit rate

2 3 1 2 8

GDSF 1 2 2 3 8

LFU 4 1 5 4 14

LRU 5 4 4 1 14

SIZE 3 5 3 5 16

Hit rate Byte hit

rate

Customer

hit rate

Customer

byte hit rate

3 3 1 1 8

GDSF 1 2 2 3 8

LFU 4 1 5 4 14

SIZE 2 5 3 5 15

LRU 5 4 4 2 15

Hit rate Byte hit

rate

Customer

hit rate

Customer

byte hit rate

GDSF 2 2 2 2 8

3 4 1 1 9

SIZE 1 3 3 5 12

LFU 4 1 4 3 12

LRU 5 5 5 4 19

10% 30% 50%

LRU Y Y Y

LFU Y Y Y

SIZE Y Y ---

GDSF Y Y Y

236 Electronic Commerce Studies

10% 30% 50%

LRU --- Y Y

LFU Y Y Y

SIZE Y Y Y

GDSF Y Y Y

10% 30% 50%

LRU Y Y Y

LFU Y Y Y

SIZE Y --- ---

GDSF --- --- ---

10% 30% 50%

LRU Y Y Y

LFU --- --- ---

SIZE Y Y Y

GDSF --- --- ---

238 Electronic Commerce Studies

(1)

(2)

(3)

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tolychen@ms37.hinet.net