Dynamic Network Flow Classification with Hardware offloading
Pieroux, Alexandre
Promotor(s) :
Mathy, Laurent
Date of defense : 7-Sep-2017/8-Sep-2017 • Permalink : http://hdl.handle.net/2268.2/3298
Details
| Title : | Dynamic Network Flow Classification with Hardware offloading |
| Author : | Pieroux, Alexandre
|
| Date of defense : | 7-Sep-2017/8-Sep-2017 |
| Advisor(s) : | Mathy, Laurent
|
| Committee's member(s) : | Barbette, Tom
Leduc, Guy
Donnet, Benoît
|
| Language : | English |
| Number of pages : | 48 |
| Keywords : | [fr] Network classification offloading |
| Discipline(s) : | Engineering, computing & technology > Computer science |
| Target public : | Researchers Professionals of domain Student General public Other |
| Complementary URL : | https://github.com/AlexandrePieroux/DNFC |
| Institution(s) : | Université de Liège, Liège, Belgique |
| Degree: | Master en sciences informatiques, à finalité spécialisée en "computer systems and networks" |
| Faculty: | Master thesis of the Faculté des Sciences appliquées |
Abstract
[fr] Nowadays, network applications and connected devices are calling for a better management of the network infrastructures. With the growth of network load, efficient network classification is playing a key role for providing quality of service.
In this document we present a network classification scheme that allow to contextualize a packet in its flow. The designed classifier is composed of four components: a static classifier, a dynamic classifier, a tag system and queues. The static classifier is responsible for matching the packets to the provided classification rules. The tag mechanism is elaborated to give to the user a mean of retrieving information about the flow of the processed packet. The dynamic classifier associate the packets with their tags and a queue system is used to forward the results to the user.
The implementation is provided under the form of a C library that ease the use of it in network low level applications. The design of it allow a flexible modularity and portability. The results show that our solution give scalability when a large amount of rules is used and allow fast dynamic classification. The use of lock-free algorithms to handle multithreading and concurrency allow to perform the classification of several packets simultaneously with efficiency. The designed tag mechanism allow an easy consultation of the flow of a processed packet. The hardware capabilities offered by advanced network hardware is studied and matched with the need of the solution, enabling possibilities of offloading it for efficiency.
Network classification is a problem hard to solve efficiently, many solutions are available depending on the situation and the requirements. In today's network, portable and scalable solutions are important and need a particular attention. The implementation of our solution give the opportunity for efficient dynamic network classification that ease the processing of packets in their contexts.
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