基于多级分类的网络流量在线识别方法(英文)

Internet traffic classification plays an important role in network management. Many approaches have been proposed to classify different categories of Internet traffic. However, these approaches have specific usage contexts that restrict their ability when they are applied in the current network environment. For example, the port based approach cannot identify network applications with dynamic ports; the deep packet inspection approach is invalid for encrypted network applications; and the statistical based approach is time-consuming. In this paper, a novel technique is proposed to classify different categories of network applications. The port based, deep packet inspection based and statistical based approaches are integrated as a multistage classifier. The experimental results demonstrate that this approach has high recognition rate which is up to 98% and good performance of real-time for traffic identification.     

基于免疫粒子群的P2P协议识别方法

为了解决基于统计特征的P2P协议识别中,因特征选择不当而引起的识别准确率低的问题,采用免疫粒子群算法(Immune-PSO)选取最优特征子集,选择出最能区分P2P协议的特征子集。实验结果表明,该算法较标准粒子群算法具有更高的全局搜索能力,能更准确地找出最优特征子集,该方法能有效地提高协议的识别率,对常见的P2P协议如BitTorrent、eMule等有高达90%的识别率。     

智慧能源及能源互联网技术在综合能源服务中的应用

<正>1技术背景为满足未来能源需求,解决能源环境矛盾,促进经济社会可持续发展,国际上掀起了第三次工业革命,提出了全新的智慧能源及能源互联网的理念。将互联网技术与可再生能源结合在一起,创造一种全新而强大的能源基础设施,为解决能源危机和环境问题提供了新途径。当前,我国正处于能源转型的关键时期,为贯彻落实     

软球模型在全尺度模拟中的验证和分析

针对颗粒流全尺度模拟时的干碰撞问题,在内嵌边界多重直接力全尺度算法中加入软球碰撞模型.通过空气中小球碰撞壁面和小球在粗糙表面上滚动2个典型算例,验证了软球模型在全尺度模拟中对干碰撞作用求解的适用性和准确性.对软球模型各主要参数的敏感度分析表明:时间步长越小,碰撞计算越精确;弹簧刚度系数越小,软球模型的接触特征时间越长,全尺度计算受到的资源限制越小;网格尺度、速度恢复系数对软球模型在全尺度模拟中的求解精度影响不大.实验室尺度气固鼓泡床的全尺度模拟结果表明,耦合方法可用于计算复杂的多颗粒流动体系.     

切削参数对减振镗杆振动性能的影响研究

在深孔镗削加工中,镗杆的减振效果是影响加工质量的关键因素,而镗杆的振动情况会受到切削参数的影响。采用单因素法,通过改变不同的切削参数对减振镗杆的振动性能进行了切削试验研究。对不同切削参数下镗杆径向和切向上的振动信号进行采集,将采集到的振动信号通过信号处理软件进行时域上的波形显示,对比单因素变化下的镗杆实际振动曲线差别,得出切削线速度、进给速度、背吃刀量各自的变化对镗杆振动性能的影响,给出该款减振镗杆的切削参数选用建议,为该款减振镗杆的使用和后续性能改进提供技术参考。     

含POSS的纳米杂化物对环氧树脂改性研究

将笼型八聚倍半硅氧烷(POSS)与对-甲苯基缩水甘油醚(TGE)反应,合成了顶角含有苯环的笼形八聚倍半硅氧烷无机/有机纳米杂化物(PTGE),将该杂化物添加到双酚A型环氧树脂(E44)中对其改性,测定固化后改性环氧树脂复合材料的力学性能和热稳定性能。结果表明,改性后环氧树脂的冲击强度、拉伸强度和断裂伸长率较改性前有了明显的提高,热稳定性大大增强。     

一种动量因子自适应自然梯度的盲分离方法

自然梯度算法是处理盲源分离问题的一个重要方法。基于信号分离度的概念以及BP算法中的动量因子,在自适应步长的基础上加入了基于分离度自适应变化的动量因子,提出了一种改进算法来更好处理速度和分离之间的矛盾;通过仿真验证了改进算法的优越性。     

一种新的基于BPSO和KNN的P2P流量识别算法

Peer-to-Peer technology is one of the most popular techniques nowadays, and it brings some security issues, so the recognition and management of P2P applications on the internet is becoming much more important. The selection of protocol features is significant to the problem of P2P traffic identification. To overcome the shortcomings of current methods, a new P2P traffic identification algorithm is proposed in this paper. First of all, a detailed statistics of traffic flows on internet is calculated. Secondly, the best feature subset is chosen by binary particle swarm optimization. Finally, every feature in the subset is given a proper weight. In this paper, TCP flows and UDP flows each have a respective feature space, for this is advantageous to traffic identification. The experimental results show that this algorithm could choose the best feature subset effectively, and the identification accuracy is improved by the method of feature weighting.