Abstract
Currently, the HTTP protocol supports a lot of different applications, with distinct traffic intensities and patterns. The ability to accurately map traffic flows to their corresponding application can be very useful in several operational and management tasks, like service differentiation and personalization, network resources optimization, network management and security. This paper discusses the possibility of performing the identification of HTTP-based applications in an efficient way, using a classification approach based on the multi-scale analysis of the traffic flows: by performing a wavelet decomposition, captured traffic can be fully characterized in terms of its time and frequency components, allowing the identification of differentiating characteristics/behaviours that can be used to discriminate between different applications. The results obtained by applying this methodology to traffic belonging to several Web-based applications show that it is able to achieve good classification results, while being immune to some of the most important drawbacks that limit the applicability of the most popular traffic identification approaches. Finally, the paper reviews the most relevant traffic classification methodologies that have been published so far, including some recent patents.
Keywords: Application identification, multi-scale analysis, wavelet transform.Application identification, multi-scale analysis, wavelet transform.Application identification, multi-scale analysis, wavelet transform.
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