电信cdn中可扩展的基于颜色的缓存方案

Anh-Tu Ngoc Tran, Thanh-Dang Diep, Takuma Nakajima, Masato Yoshimi, N. Thoai
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引用次数: 1

摘要

互联网流量正在迅速增长,这主要是由于视频服务的激增。内容分发网络(cdn)通过在缓存服务器中存储视频副本来减少视频流量。尽管如此,缓存服务器通常位于互联网服务提供商(isp)之外。这意味着cdn不能减少ISP网络内的视频流量。为了缓解这个问题,许多isp建立了自己的cdn,称为telco - cdn。基于遗传算法的缓存被认为是减少流量的最佳方法。然而,这是不实际的,因为即使在使用集群时,生成内容分配的计算时间也非常长。设计了一种基于颜色的方法来帮助克服以增加流量为代价的缺点。然而,在内容类别或请求数量迅速增加的情况下,该方法也有与基于遗传算法的缓存相同的限制。为了解决这一限制,我们提出了两种新的技术来阻止计算时间的增加。一个能够应对内容类别增加的情况,另一个能够应对请求数量增加的情况。实证结果表明,对于5000个内容的问题,前者的计算时间减少了5倍,后者的计算时间减少了7倍,而代价是流量分别增加了1%和12%。
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A Scalable Color-Based Caching Scheme in Telco-CDNs
Internet traffic is growing quickly, and it is majorly contributed by the proliferation of video services. Content Delivery Networks (CDNs) reduce the video traffic by storing replicas of videos in their cache servers. Nonetheless, the cache servers are usually located outside Internet Service Providers (ISPs). This implies that CDNs cannot reduce the video traffic inside ISP networks. To mitigate this issue, many ISPs build their own CDNs called Telco-CDNs. Genetic Algorithm-based caching is deemed the best approach in terms of traffic reduction. However, it is not practical since its computation time to generate content allocations is extremely long even when using a cluster. A color-based approach was devised to help overcome the drawback at the expense of its increase in traffic. Nevertheless, in case the number of content categories or requests proliferates quickly, the approach also has the same limitation like the Genetic Algorithm-based caching. To resolve the limitation, we propose two novel techniques to hamper the increase in the computation time. One is able to cope with the situation when the number of content categories increases while the other can deal with the circumstance when the number of requests rises. The empirical results show that the computation time is reduced 5x for the former and 7x for the latter at the expense of 1% and 12% increase in traffic for a problem of 5,000 contents, respectively.
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