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Performance analysis of server sharing collectives for content distribution

机译:服务器共享集体进行内容分发的性能分析

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Demand for content served by a provider can fluctuate with time, complicating the task of provisioning serving resources so that requests for its content are not rejected. One way to address this problem is to have providers form a collective in which they pool together their serving resources to assist in servicing requests for one another's content. In this paper, we determine the conditions under which a provider's participation in a collective reduces the rejection rate of requests for its content - a property that is necessary for such a provider to justify its participation within the collective. We show that all request rejection rates are reduced when the collective is formed from a homogeneous set of providers, but that some rates can increase within heterogeneous sets. We also show that, asymptotically, growing the size of the collective will sometimes, but not always, resolve this problem. We explore the use of thresholding techniques, where each collective participant sets aside a portion of its serving resources to serve only requests for its own content. We show that thresholding allows a more diverse set of providers to benefit from the collective model, making collectives a more viable option for content delivery services.
机译:由提供者提供的内容的需求会随着时间而波动,这使得提供服务资源的任务变得复杂,因此不会拒绝对其内容的请求。解决此问题的一种方法是让提供者组成一个集体,将他们的服务资源汇集在一起​​,以协助服务对方的内容请求。在本文中,我们确定了提供者参与集体的条件,该条件降低了对其内容的请求的拒绝率,这是此类提供者证明其参与集体的必要条件。我们表明,当集合由同类提供者组形成时,所有请求拒绝率都会降低,但是异构组中某些请求率会增加。我们还表明,渐进地增加集体的规模有时会(但并非总是)解决此问题。我们探索了阈值化技术的使用,其中每个集体参与者都留出一部分服务资源,以仅服务于其自身内容的请求。我们表明,阈值化可以使更多种类的提供商从集体模型中受益,从而使集体成为内容交付服务的更可行选择。

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