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ERPC: An Edge-Resources Based Framework to Reduce Bandwidth Cost in the Personal Cloud

机译:ERPC:一种基于边缘资源的框架,可降低个人云中的带宽成本

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Personal Cloud storage and file synchronization services, such as Dropbox, Google Drive, and Baidu Cloud, are increasingly prevalent within the Internet community. It is estimated that subscriptions of personal cloud storage are projected to hit 1.3 billion in 2017. In order to provide high rates of data retrieving, cloud providers require huge amounts of bandwidth. As an attempt to reduce their bandwidth cost and, at the same time, guarantee the quality of service, we propose a novel cloud framework based on distributed edge resources (i.e., voluntary peers in P2P Networks and edge servers in Content Delivery Networks). P2P technique is well considered as an efficient way to distribute contents, but not all of contents are applicable for it. Thus we first present an approach to select the contents which are more profitable to be placed in P2P networks. Considering the unreliability of P2P networks, we utilize CDN servers to dynamically cache the contents which can not be well served by P2P peers. The proposed caching algorithm takes the state of P2P peers into account and considers replacement and allocation policies simultaneously. According to trace-driven simulations, the ERPC achieves an impressive performance of saving bandwidth for cloud system and guaranteeing download rates for users.
机译:个人云存储和文件同步服务,例如Dropbox,Google Drive和百度云,在Internet社区中越来越普遍。据估计,2017年个人云存储的订阅量将达到13亿。为了提供高速率的数据检索,云提供商需要大量的带宽。为了降低带宽成本并同时保证服务质量,我们提出了一种基于分布式边缘资源(即P2P网络中的自愿对等方和Content Delivery Networks中的边缘服务器)的新型云框架。 P2P技术被公认为是分发内容的有效方法,但并非所有内容都适用。因此,我们首先提出一种方法来选择更有利可图的内容以放置在P2P网络中。考虑到P2P网络的不可靠性,我们利用CDN服务器来动态缓存P2P对等不能很好地服务的内容。提出的缓存算法考虑了P2P对等体的状态,并同时考虑了替换和分配策略。根据跟踪驱动的模拟,ERPC在节省云系统带宽和保证用户下载率方面取得了令人印象深刻的性能。

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