基于半监督学习的P2P协议识别

随着P2P技术的发展,网络上充满了大量的P2P应用。协议加密技术的发展,使得P2P应用的识别和管理变得非常困难。描述了如何运用半监督的机器学习理论,根据传输层的特征,用聚类算法训练数据并建立一个高效的在线协议识别器,用于在内核协议层对协议特别是P2P协议进行识别,并对BitComet和Emule进行了实验,得到了很高的识别准确率(80%)。研究并解决了将选取好的特征用于聚类并高效地实现最后的协议识别器。

基于P2P技术的CSRe冷却装置控制系统设计；Design of Control System for CSRe Cooling Equipment Based on P2P Technology

HIRFL-CSR工程对CSRe冷却装置电子冷却部分的控制系统在实时性和可靠性方面提出了非常高的要求。电子冷却工作环境复杂,各种干扰难以预测。从电子冷却的控制系统改进出发,以实现电子冷却的自动调束为目标,以高端FPGA和ARM嵌入式系统为基础,采用P2P通讯技术和神经元网络算法来实现对电子冷却的自动控制。该控制系统对电子冷却控制的完善提供了先进的硬件平台和软件实现方案。

基于半监督学习的P2P协议识别

协议识别是进行有效的网络管理与控制的重要条件，由于新的P2P软件（以Skype,Emule，BitComet，迅雷为代表）开始使用加密协议和协议伪装等技术手段来防止被网管探测、识别、封堵，传统的根据协议特征码来识别的方式已经难以识别这些软件产生的流量。基于流量特征的P2P协议识别的方法是目前研究的主要方向，将机器学习的理论与模型运用到协议识别领域是发展的一个趋势。通过对传输层数据包(包括TCP和UDP数据包)进行分析，并结合P2P系统所表现出来的流量特征，来识别某个网络流是否属于P2P。这类方法包括：TCP/UDP端口识别技术、网络直径分析技术、节点角色分析技术、协议对分析技术和地址端口对分析技术等，但是其准确性和识别率不如特征码识别。本文就基于半监督聚类的模型运用到识别具体P2P应用的可能性进行了分析与实验，提出了一种基于Newton-Raphson方法学习特征权值矩阵的训练的办法，在依据P2P应用特征选取连接特征的基础上进一步提高系统识别准确率和召回率。在本文的实验环境下，针对具体的BitComet和Emule应用的识别器的识别率和召回率均达到了85%左右，在加密协议的识别上取得了不错的效果。如何优化系统的识别准确率和召回率，提高系统效率是本文重点研究并试图解决的问题，主要包括以下三个方面的成果：一、实验并分析了基于半监督学习的聚类模型在加密P2P应用识别上的效果，同时总结了一套分析P2P协议特征的办法。二、将Newton-Raphson方法引入到连接特征的选取上，将特征权值矩阵用于距离的计算，进一步提高了训练和识别的效果。三、基于KD-Tree的识别器的实现使得整个在线识别过程能在内核的协议层高效实现，有效的控制了系统的计算复杂度。

dPAM: A Distributed Prefetching Protocol for Scalable Asynchronous Multicast in P2P Systems

We leverage the buffering capabilities of end-systems to achieve scalable, asynchronous delivery of streams in a peer-to-peer environment. Unlike existing cache-and-relay schemes, we propose a distributed prefetching protocol where peers prefetch and store portions of the streaming media ahead of their playout time, thus not only turning themselves to possible sources for other peers but their prefetched data can allow them to overcome the departure of their source-peer. This stands in sharp contrast to existing cache-and-relay schemes where the departure of the source-peer forces its peer children to go the original server, thus disrupting their service and increasing server and network load. Through mathematical analysis and simulations, we show the effectiveness of maintaining such asynchronous multicasts from several source-peers to other children peers, and the efficacy of prefetching in the face of peer departures. We confirm the scalability of our dPAM protocol as it is shown to significantly reduce server load.

Improving the Performance of Overlay Routing and P2P File Sharing using Selfish Neighbor Selection

A foundational issue underlying many overlay network applications ranging from routing to P2P file sharing is that of connectivity management, i.e., folding new arrivals into the existing mesh and re-wiring to cope with changing network conditions. Previous work has considered the problem from two perspectives: devising practical heuristics for specific applications designed to work well in real deployments, and providing abstractions for the underlying problem that are tractable to address via theoretical analyses, especially game-theoretic analysis. Our work unifies these two thrusts first by distilling insights gleaned from clean theoretical models, notably that under natural resource constraints, selfish players can select neighbors so as to efficiently reach near-equilibria that also provide high global performance. Using Egoist, a prototype overlay routing system we implemented on PlanetLab, we demonstrate that our neighbor selection primitives significantly outperform existing heuristics on a variety of performance metrics; that Egoist is competitive with an optimal, but unscalable full-mesh approach; and that it remains highly effective under significant churn. We also describe variants of Egoist's current design that would enable it to scale to overlays of much larger scale and allow it to cater effectively to applications, such as P2P file sharing in unstructured overlays, based on the use of primitives such as scoped-flooding rather than routing.

Angels: In Network Support for Minimum Distribution Time in P2P Overlays

This paper proposes the use of in-network caches (which we call Angels) to reduce the Minimum Distribution Time (MDT) of a file from a seeder – a node that possesses the file – to a set of leechers – nodes who are interested in downloading the file. An Angel is not a leecher in the sense that it is not interested in receiving the entire file, but rather it is interested in minimizing the MDT to all leechers, and as such uses its storage and up/down-link capacity to cache and forward parts of the file to other peers. We extend the analytical results by Kumar and Ross [1] to account for the presence of angels by deriving a new lower bound for the MDT. We show that this newly derived lower bound is tight by proposing a distribution strategy under assumptions of a fluid model. We present a GroupTree heuristic that addresses the impracticalities of the fluid model. We evaluate our designs through simulations that show that our Group-Tree heuristic outperforms other heuristics, that it scales well with the increase of the number of leechers, and that it closely approaches the optimal theoretical bounds.

Angels: In-Network Support for Minimum Distribution Time in P2P Overlays

This thesis proposes the use of in-network caches (which we call Angels) to reduce the Minimum Distribution Time (MDT) of a file from a seeder – a node that possesses the file – to a set of leechers – nodes who are interested in downloading the file. An Angel is not a leecher in the sense that it is not interested in receiving the entire file, but rather it is interested in minimizing the MDT to all leechers, and as such uses its storage and up/down-link capacity to cache and forward parts of the file to other peers. We extend the analytical results by Kumar and Ross (Kumar and Ross, 2006) to account for the presence of angels by deriving a new lower bound for the MDT. We show that this newly derived lower bound is tight by proposing a distribution strategy under assumptions of a fluid model. We present a GroupTree heuristic that addresses the impracticalities of the fluid model. We evaluate our designs through simulations that show that our GroupTree heuristic outperforms other heuristics, that it scales well with the increase of the number of leechers, and that it closely approaches the optimal theoretical bounds.

Host-based P2P flow identification and use in real-time

Data identification is a key task for any Internet Service Provider (ISP) or network administrator. As port fluctuation and encryption become more common in P2P traffic wishing to avoid identification, new strategies must be developed to detect and classify such flows. This paper introduces a new method of separating P2P and standard web traffic that can be applied as part of a data mining process, based on the activity of the hosts on the network. Unlike other research, our method is aimed at classifying individual flows rather than just identifying P2P hosts or ports. Heuristics are analysed and a classification system proposed. The accuracy of the system is then tested using real network traffic from a core internet router showing over 99% accuracy in some cases. We expand on this proposed strategy to investigate its application to real-time, early classification problems. New proposals are made and the results of real-time experiments compared to those obtained in the data mining research. To the best of our knowledge this is the first research to use host based flow identification to determine a flows application within the early stages of the connection.

P2P and SOA architecture for digital libraries

In an information-driven society where the volume and value of produced and consumed data assumes a growing importance, the role of digital libraries gains particular importance. This work analyzes the limitations in current digital library management systems and the opportunities brought by recent distributed computing models. The result of this work is the implementation of the University of Aveiro integrated system for digital libraries and archives. It concludes by analyzing the system in production and proposing a new service oriented digital library architecture supported in a peer-to-peer infrastructure

BitTorrent based transmission of real-time scalable video over P2P networks

The number of software applications available on the Internet for distributing video streams in real time over P2P networks has grown quickly in the last two years. Typical this kind of distribution is made by television channel broadcasters which try to make their content globally available, using viewer's resources to support a large scale distribution of video without incurring in incremental costs. However, the lack of adaptation in video quality, combined with the lack of a standard protocol for this kind of multimedia distribution has driven content providers to basically ignore it as a solution for video delivery over the Internet. While the scalable extension of the H. 264 encoding (H.264/SVC) can be used to support terminal and network heterogeneity, it is not clear how it can be integrated in a P2P overlay to form a large scale and real time distribution. In this paper, we start by defining a solution that combines the most popular P2P file-sharing protocol, the BitTorrent, with the H. 264/SVC encoding for a real-time video content delivery. Using this solution we then evaluate the effect of several parameters in the quality received by peers.