Rank-based content updating method in FemtoCaching

Apipong Pingyod, Yuthapong Somchit
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引用次数: 4

Abstract

In the FemtoCaching research, an approximation algorithm to place contents in the cache of femto-cells is proposed. However, this research does not consider changes of content ranking and content popularities that change during time. Hence, contents in femto-cells should be updated with limited number of updated contents. There is a popularity-based updating method that replaces low popularity contents by high popularity contents but its performance is not good in case of high limited threshold. This problem occurs because diversity of contents in distributed caches is decreased. Hence, we propose a new method in this paper called rank-based updating method that attempts to cache diverse contents in distributed caches. It updates contents in femto-cells by considering ranking number of each content in ranking with the same ranking number of each content in femto-cells. A complexity of the proposed method is lower than the algorithm of FemtoCaching and slightly more than the popularity-based updating method. Performance of the proposed method is evaluated by simulation. Experimental results show that the performances of the proposed method are almost the same as the limited FemtoCaching method and better than the popularity-based updating method in case of high limited threshold.
FemtoCaching中基于排名的内容更新方法
在FemtoCaching的研究中,提出了一种将内容放入femtocell缓存中的近似算法。但是,本研究没有考虑内容排名和内容受欢迎程度随时间变化的变化。因此,应该使用有限数量的更新内容来更新单元格中的内容。有一种基于人气的更新方法,用人气高的内容代替人气低的内容,但在限制阈值较高的情况下,其性能不佳。出现这个问题是因为分布式缓存中的内容多样性降低了。因此,本文提出了一种基于排名的更新方法,该方法尝试在分布式缓存中缓存不同的内容。它通过考虑每个内容在排名中的排名数与每个内容在飞单元中的排名数相同来更新飞单元中的内容。该方法的复杂度低于FemtoCaching算法,略高于基于流行度的更新方法。通过仿真对该方法的性能进行了评价。实验结果表明,该方法的性能与有限的FemtoCaching方法基本相同,在高限制阈值情况下优于基于流行度的更新方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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