基于大数据挖掘的精细化流量经营运营平台建设探索

在移动互联网时代,用户的消费行为产生了海量的数据,如何整合大数据,进行数据挖掘,从海量的数据中挖掘出有用的信息,以便对客户作精细化流量经营,这是当前各大运营商面临的主要问题。本文从现状出发,分析了运营商为能做到精细化流量经营,需要如何建设运营平台和进行数据挖掘。     

CNG加气站爆炸燃烧的交通疏散仿真分析

随着石油资源的日益短缺和国家能源战略的调整,环保要求和汽车技术的不断提高,燃气车辆不断增多,与之相对应的车用加气站的数量也越来越多。但是接连发生的加气站燃气泄漏与火灾事故使得加气站的使用安全问题成为日益关注的问题。当加气站出现燃气泄漏与火灾事故时,天然气未立即着火可形成爆炸气体云团,遇火就会发生爆炸,在危险距离以内,人会受到爆炸冲击波的伤害。重点将对CNG加气站爆炸事故后的交通疏散条件制定分级标准,结合实例采用计算机软件仿真疏散分析,对以后进行新建加气站的安全评估分析工作开展提供定量依据。     

QoS二次流量监管实现

流量监管TP（Traffic Policing）就是对流量进行控制,它通过监督进入网络的流量速率,确保进入的流量被限制在一个合理的范围内。为满足网络中多用户多业务对流量监管的要求,通过对QoS流量监管的模式方法CAR（Committed Access Rate,约定访问速率）的分析研究,在路由平台上实现了QoS二次的流量监管功能,经在三层交换机上测试,证明了监管的有效性。     

网络带宽测量技术分析

通过对变包测量算法和包对／包队列测量算法的理论分析,得出其各自在不同环境下可用性、准确性、健壮性、时效性的分析结果,说明其存在的缺陷和问题。将两种算法进行融合,采用传输控制协议封装探测包以解决算法对网际控制报文协议的依赖,利用传输控制协议的反馈机制,测量算法只需在发送端部署软件。     

基于流量特征和载荷特征的P2P流量识别

本文分析了目前的P2P网络流量识别方法及其存在的问题。设计识别P2P流量的数据结构;在流量识别阶段,在传输层捕获TCP和UDP数据包,依据P2P流在传输层表现出来的主要流量特征,进行TCP/UDP流量特征的P2P流量识别;在载荷特征识别阶段,对载荷特征库定期更新,将在流量识别阶段中识别出的P2P流作精确载荷特征识别,并将流量识别阶段中漏掉的流量作载荷特征识别;在模式匹配过程采用比较指印函数值来加快识别速度;进而提出一个可准确识别出新生、加密的P2P流量及其名称的算法。实验结果表明,该算法具有较高识别和分类P2P流量的能力。     

存在自私节点的Ad Hoc网络流量分析

Adhoc网络是一种多跳中继网络,其数据的传输需要依靠中间节点的转发。因此网络中的数据流量便有节点产生流量及节点转发流量之分。由于网络中的自私节点可能会丢弃分组,那么网络中的流量也会受到影响。本文通过对平面六边形网络模型的研究,推导出在节点自私程度不同的条件下节点产生的流量以及节点的转发流量的数学表达式,并且分析了节点自私性对Adhoc网络流量的影响。     

On the complexity of bandwidth allocation in radio networks

We define and study an optimization problem that is motivated by bandwidth allocation in radio networks. Because radio transmissions are subject to interference constraints in radio networks, physical space is a common resource that the nodes have to share in such a way, that concurrent transmissions do not interfere. The bandwidth allocation problem we study under these constraints is the following. Given bandwidth (traffic) demands between the nodes of the network, the objective is to schedule the radio transmissions in such a way that the traffic demands are satisfied. The problem is similar to a multicommodity flow problem, where the capacity constraints are replaced by the more complex notion of non-interfering transmissions. We provide a formal specification of the problem that we call round weighting  . By modeling non-interfering radio transmissions as independent sets, we relate the complexity of round weighting to the complexity of various independent set problems (e.g. maximum weight independent set, vertex coloring, fractional coloring). From this relation, we deduce that in general, round weighting is hard to approximate within n^1−ε$n^{1-\epsilon }$ (n$n$ being the size of the radio network). We also provide polynomial (exact or approximation) algorithms e.g. in the following two cases: (a) when the interference constraints are specific (for instance for a network whose vertices belong to the Euclidean space), or (b) when the traffic demands are directed towards a unique node in the network (also called gathering, analogous to single commodity flow).     

Segment-based adaptive hyper-Erlang model for long-tailed network traffic approximation

Modeling the long-tailedness property of network traffic with phase-type distributions is a powerful means to facilitate the consequent performance evaluation and queuing based analysis. This paper improves the recently proposed Fixed Hyper-Erlang model (FHE) by introducing an adaptive framework (Adaptive Hyper-Erlang model, AHE) to determine the crucially performance-sensitive model parameters. The adaptive model fits long-tailed traffic data set directly with a mixed Erlang distribution in a new divide-and-conquer manner. Compared with the well-known hyperexponential based models and the Fixed Hyper-Erlang model, the Adaptive Hyper-Erlang model is more flexible and practicable in addition to its accuracy in fitting the tail behavior.

基于序贯模式挖掘的宏观网络流量异常检测

基于序贯频繁模式挖掘,提出并实现了一种宏观网络流量异常检测的方法。定义了一个新的频繁模式和相对应的异常度概念。对863-917网络安全监测平台提供的全国流量数据进行了实验,得出对应于“橙色八月”的2006年8月上旬流量严重异常的结论。通过与相关的其他传统算法进行对比,如使用绝对流量的算法和简单使用不同小时流量排名的算法,进一步说明序贯频繁模式对网络流量分析的实用性。