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Performance Improvement of Traffic Classification Based on Application Traffic Locality

机译:基于应用流量局部性的流量分类性能改进

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摘要

Application-level traffic classification is an essential requirement for stable network operation and resource management. The payload signature-based classifier is considered a reliable method for Internet traffic classification. However, with this system, processing speeds are slower when high volumes of traffic are being classified in high-speed networks in real time. In this paper, we propose a method for server IP-port pair cache based traffic classification, with the aim of increasing the processing speed and completeness of payload signature-based traffic classification. This approach takes application traffic locality into consideration. Moreover, we propose a cache data management method that has the purpose of minimizing the utilization of cache memory and processing speed and maximizing level of completeness. When our proposed method was applied to a campus network, we observe 10 times improvement in processing speed and 10% increasing in completeness against the payload signature-based classifier without a server IP-Port pair cache.
机译:应用程序级别的流量分类是稳定网络运行和资源管理的基本要求。基于有效负载签名的分类器被认为是Internet流量分类的可靠方法。但是,使用此系统,当在高速网络中实时分类大量流量时,处理速度会变慢。本文提出了一种基于服务器IP端口对缓存的流量分类方法,旨在提高基于有效载荷签名的流量分类的处理速度和完整性。这种方法考虑了应用程序流量的局部性。此外,我们提出了一种高速缓存数据管理方法,其目的是最小化高速缓存存储器的利用率和处理速度以及最大化完整性级别。当我们提出的方法应用于校园网络时,与没有服务器IP端口对高速缓存的基于有效负载签名的分类器相比,我们观察到处理速度提高了10倍,完整性提高了10%。

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