社交媒体内容的智能分发

T. Banditwattanawong, Masawee Masdisornchote, P. Uthayopas
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引用次数: 3

摘要

今天的数据,如社交媒体内容和通过无处不在的设备收集的数字内容存档,已经托管在云上,并以分发方式共享。这将导致网络链路拥塞、云服务延迟以及公共云数据流出费用的增加。仿真结果表明,采用i-Cloud作为云缓存的核心机制可以缓解这些问题,比其他已知的方法节省17.24%的字节命中和成本,节省17.96%的延迟和29.33%的缓存命中。一个主要的发现是,i-Cloud学习单一用户社区模式和i-Cloud学习跨用户社区模式之间没有显著的性能差异。
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The smart distribution of social media contents
Today's data such as social media contents and archive of digital contents gathered via ubiquitous devices have been hosted on cloud and being shared in a distribution manner. This causes network link congestions, delayed cloud services and increases in public cloud data-out charges. Simulations have demonstrated that deploying our approach, i-Cloud, as the core mechanism of cloud cache could alleviate these problems up to 17.24% byte-hit and cost-saving, 17.96% delay-saving and 29.33% cache hit outperforming the other well-known approaches. A main finding was that there is no significant performance difference between i-Cloud learning single-user-community patterns and i-Cloud learning cross-user-community patterns of comparable sizes.
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