自适应聚类片选内容分发模型

Adaptive Clustering and Piece Selecting Content Delivery Model

设计了一种内容分发网络中基于聚类算法和片选策略的内容分发模型,以达到适应不同内容类型和提高分发效率的目的,这种模型克服了传统内容分发模型在内容支持上的局限性,可根据模型内参数的自动调整适应不同类型(块式或者流式)内容的分发,并且提高分发的效率;详细描述了这种模型的工作流程、内容传送方式、网络拓扑结构、聚类算法和片选策略等,阐述了其优越性。

Based on the clustering algorithm and piece selecting strategy,this paper describes a content delivery model, which can adapt to different types of content and improve the delivery efficiency in the content delivery network. This model will overcome the limitation of traditional model in the contents support, and it will support not only the delivery of block contents but also that of stream contents. This paper introduces in details how the model works, its transmitting way, its clustering algorithm,piece selecting strategy and advantages.