新的数据包字段用于内容感知分类

Radu-Dinel Miruta, Cornelia-Ionela Badoi, E. Borcoci
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引用次数: 2

摘要

本文提出了一种基于数据分组中嵌入与内容相关的新字段的边缘路由器多维分组分类器的解决方案。该技术适用于内容感知网络。该分类算法使用了三个新的分组字段,分别是虚拟内容感知网络(VCAN)、服务类型(STYPE)和U(单播/多播),它们是内容感知传输信息(CATI)报头的一部分。根据媒体服务定义,在服务/内容提供商服务器端将CATI报头插入传输的数据包中,并在新的覆盖内容感知网络层启用内容感知功能。然后分析分类过程中CATI标头的功能。考虑了两种可能性:分别采用朗讯比特矢量算法和元组空间搜索,以响应建议的多字段分类器。结果非常有希望,并且在内容感知的数据包分类中非常有用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
New packet fields for content aware classification
This paper presents a solution for a new multidimensional packet classifier of an edge router, based on content — related new fields embedded in the data packets. The technique is applicable to content aware networks. The classification algorithm is using three new packet fields named Virtual Content Aware Network (VCAN), Service Type (STYPE) and U (unicast/multicast) which are part of the Content Awareness Transport Information (CATI) header. A CATI header is inserted into the transmitted data packets at the Service/Content Provider server side, in accordance with the media service definition, and enables the content awareness features at a new overlay Content Aware Network layer. The functionality of the CATI header within the classification process is then analyzed. Two possibilities are considered: the adaptation of the Lucent Bit vector algorithm and, respectively, of the tuple space search, in order to respond to the suggested multi-fields classifier. The results are very promising and can be very useful in the content-aware packet classification.
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