基于递归特性的网络应用流量行为分析

准确刻画不同网络应用流量的行为特征,是识别和控制应用流量以及保证互联网服务质量的关键。该文提出一种基于流量系统状态递归特性的分析方法,研究应用流量的内在动力学行为。针对实际网络中多类不同应用流量的时间序列,首先重构流量序列的高维相空间,然后分析应用流量系统状态运动轨迹的递归特性,揭示其各自固有的内在行为。实验结果表明,流量的非线性动力学特征能够准确地刻画各类网络应用流量的行为,并且不随网络规模或网络协议版本的改变而发生变化。因此,流量的非线性动力学特征有助于提高互联网应用流量识别与控制的性能。

Traffic Labeller： Collecting Internet Traffic Samples with Accurate Application Information

Traffic classification research has been suffering from a trouble of collecting accurate samples with ground truth.A model named Traffic Labeller(TL) is proposed to solve this problem.TL system captures all user socket calls and their corresponding application process information in the user mode on a Windows host.Once a sending data call has been captured,its 5-tuple {source IP,destination IP,source port,destination port and transport layer protocol},associated with its application information,is sent to an intermediate NDIS driver in the kernel mode.Then the intermediate driver writes application type information on TOS field of the IP packets which match the 5-tuple.In this way,each IP packet sent from the Windows host carries their application information.Therefore,traffic samples collected on the network have been labelled with the accurate application information and can be used for training effective traffic classification models.

Online Internet Traffic Identification Algorithm Based on Multistage Classifier

Internet traffic classification plays an important role in network management. Many approaches have been proposed to clas-sify different categories of Internet traffic. However, these approaches have specific us-age contexts that restrict their ability when they are applied in the current network envi-ronment. For example, the port based ap-proach cannot identify network applications with dynamic ports; the deep packet inspec-tion approach is invalid for encrypted network applications; and the statistical based approach is time-onsuming. In this paper, a novel tech-nique is proposed to classify different catego-ries of network applications. The port based, deep packet inspection based and statistical based approaches are integrated as a multi-stage classifier. The experimental results demonstrate that this approach has high rec-ognition rate which is up to 98% and good performance of real-time for traffic identifica-tion.

OpenFIow Based Flow Slice Load Balancing

Today's data center networks are designed using densely interconnected hosts in the data center.There are multiple paths between source host and destination server.Therefore,how to balance traffic is key issue with the fast growth of network applications.Although lots of load balancing methods have been proposed,the traditional approaches cannot fully satisfy the requirement of load balancing in data center networks.The main reason is the lack of efficient ways to obtain network traffic statistics from each network device.As a solution,the OpenFlow protocol enables monitoring traffic statistics by a centralized controller.However,existing solutions based on OpenFlow present a difficult dilemma between load balancing and packet reordering.To achieve a balance between load balancing and packet reordering,we propose an OpenFlow based flow slice load balancing algorithm.Through introducing the idea of differentiated service,the scheme classifies Internet flows into two categories:the aggressive and the normal,and applies different splitting granularities to the two classes of flows.This scheme improves the performance of load balancing and also reduces the number of reordering packets.Using the trace-driven simulations,we show that the proposed scheme gains over 50%improvement over previous schemes under the path delay estimation errors,and is a practical and efficient algorithm.

Design and Implementation of Computer Network Traffic Monitoring

This paper focuses on the key technologies of P2P and network traffic monitoring, research and analyze the traditional P2P flow control technology and the working principle of deployment, discuss on the straight loss and bypass interference control technology, and the reasonable combination of two kinds of technology to design straight bypass joint deployment. On basis of it, we design a new P2P traffic monitoring system. Through the design and implementation of computer network traffic monitoring system based on C/S mode to achieve automatic control, maintenance, and monitor network traffic, which is suitable for the current engineering software to monitor a network application environment. From the network users and network operator＇ s perspective, monitoring of network traffic is scientific, reasonable that improve network management and it has important research value.

SWN: An SDN Based Framework for Carrier Grade WiFi Networks

With the rapid growth of mobile data traffic and vast traffic offloaded from cellular network, Wi-Fi has been considered as an essential component to cope with the tremendous growth of mobile data traffic. Although operators have deployed a lot of carrier grade Wi-Fi networks, but there are still a multitude of arrears for nowadays Wi-Fi networks, such as supporting seamless handover between APs, automatic network access and unified authentication, etc. In this paper, we propose an SDN based carrier grade Wi-Fi network framework, namely SWN. The key conceptual contribution of SWN is a principled refactoring of Wi-Fi networks into control and data planes. The control plane has a centralized global view of the whole network, can perceive the underlying network state by network situation awareness(NAS) technique, and bundles the perceived information and network management operations into northbound Application Programming Interface(API) for upper applications. In the data plane, we construct software access point(SAP) to abstract the connection between user equipment(UE) and access point(AP). Network operators can design network applications by utilizing these APIs and the SAP abstraction to configure and manage the whole network, which makes carrier grade Wi-Fi networks more flexible, user-friendly, and scalable.