內(nèi)容中心網(wǎng)絡(luò)中一種基于內(nèi)容等級及流行度的緩存策略

黃勝; 劉四軍; 滕明埝; 姜良浩; 郝言明; 何玉杰

doi:10.11999/JEIT160816

內(nèi)容中心網(wǎng)絡(luò)中一種基于內(nèi)容等級及流行度的緩存策略

doi: 10.11999/JEIT160816

基金項目:

國家自然科學(xué)基金(61571072, 61371096)，重慶市基礎(chǔ)與前沿研究計劃項目(cstc2015jcyjA40015, cstc2013jcyjA40052)，重慶市教委科學(xué)技術(shù)研究項目(KJ130515)

計量
- 文章訪問數(shù): 1391
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- 被引次數(shù): 0
出版歷程
- 收稿日期: 2016-08-03
- 修回日期: 2016-12-30
- 刊出日期: 2017-06-19

Cache Strategy Based on Content Level and Popularity in Content Centric Networking

Funds:

The National Natural Science Foundation of China (61571072, 61371096), Chongqing Base and Cutting-edge Research Projects (cstc2015jcyjA40015, cstc2013jcyjA40052), Chongqing Commission of Science and Technology Research Projects (KJ130515)

摘要

摘要: 網(wǎng)內(nèi)緩存作為內(nèi)容中心網(wǎng)絡(luò)(CCN)的核心技術(shù)，越來越受到關(guān)注。為了提高網(wǎng)絡(luò)的緩存性能以及用戶對數(shù)據(jù)請求的滿意度，該文提出一種基于內(nèi)容等級及流行度的緩存策略(CLPC)。CLPC策略通過設(shè)置不同用戶對內(nèi)容的訪問等級以及統(tǒng)計內(nèi)容的訪問頻率，決定數(shù)據(jù)的緩存位置，并且設(shè)計了數(shù)據(jù)替換方法，在一定程度上保證了不同用戶對不同數(shù)據(jù)的最優(yōu)請求，同時提高了網(wǎng)絡(luò)的性能。實驗證明該策略與CEE+LRU, Prob(0.7)+LRU, Betw+LRU相比，能更好地提高緩存命中率、平均時延及源端命中率等網(wǎng)絡(luò)緩存性能指標(biāo)。
- 內(nèi)容中心網(wǎng)絡(luò) /
- 緩存策略 /
- 內(nèi)容等級 /
- 流行度
Abstract: As the most important core technology in Content Centric Networking (CCN), caching is widely concerned . In order to improve the network performance and enhance the user satisfaction of data request, a Content-based Level and the Popularity of Caching (CLPC) strategies is proposed . The strategy decides the cache position of data and design method of data replacement by setting the request content level of different users and counting the request frequency, to ensure the optimum request of different users for different data and improve the performance of the network. Experimental results show that compared with the CEE + LRU, Prob (0.7) + LRU and Betw+LRU, the CLPC can increase cache hit ratio, reduce the average delay and the content source hit ratio.
- Content Centric Network (CCN) /
- Caching strategy /
- Content level /
- Popularity

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