Transient flow of rarefied gas through a short tube

A transient rarefied gas flow through a short tube is studied on the basis of the direct simulation Monte Carlo method. The mass flow rates through both inlet and outlet cross sections are calculated as a function of the time in the free-molecular, transitional and hydrodynamic regimes with respect to the gas rarefaction. Two values of the pressure ratio, i.e. 0.1 and 0.5, and two values of the aspect ratio, i.e. 1 and 5, are considered. A characteristic time equal to that needed to cross the tube radius with the most probable molecular speed is defined. A typical interval of time to establish the steady flow rates was calculated. It was found that this time is about ten and forty characteristic times for the shorter and longer tubes, respectively. The flow field for the longer tube is analyzed in details.     

An approximation method of origin–destination flow traffic from link load counts

Traffic matrix (TM) is a key input of traffic engineering and network management. However, it is significantly difficult to attain TM directly, and so TM estimation is so far an interesting topic. Though many methods of TM estimation are proposed, TM is generally unavailable in the large-scale IP backbone networks and is difficult to be estimated accurately. This paper proposes a novel method of TM estimation in large-scale IP backbone networks, which is based on the generalized regression neural network (GRNN), called GRNN TM estimation (GRNNTME) method. Firstly, building on top of GRNN, we present a multi-input and multi-output model of large-scale TM estimation. Because of the powerful capability of learning and generalizing of GRNN, the output of our model can sufficiently capture the spatio-temporal correlations of TM. This ensures that the estimation of TM can accurately be attained. And then GRNNTME uses the procedure of data posttreating further to make the output of our model closer to real value. Finally, we use the real data from the Abilene Network to validate GRNNTME. Simulation results show that GRNNTME can perform well the accurate and fast estimation of TM, track its dynamics, and holds the stronger robustness and lower estimation errors.     

Adaptive Frequency-Domain Equalization with Narrowband Interference Suppression

Frequency-domain equalization (FDE) is an effective technique that exhibits the property of relatively low complexity which grows with increasing the number of symbols of dispersion in multipath propagation environments for broadband wireless communications compared with the conventional time-domain equalization. However, in practical broadband wireless communications, there exists not only multipath but also narrowband interference (NBI). The conventional FDE methods do not consider NBI and their performance degrades obviously in such case. In this paper, we propose a new optimization criterion which can effectively suppress NBI to obtain the maximum decision signal-to-noise ratio. The proposed scheme employs a conventional adaptive algorithm such as least-mean-square or recursive-least-square and operates in the spatial-frequency domain, which is concerned with the use of FDE and space diversity within block transmission schemes jointly. The simulation results show that the proposed schemes have better error-rate performance with low complexity and can be used even in the presence of strong NBI, compared to other existing adaptive FDE algorithms.     

一个恒价的IP网络实时记费管理机制

提出了一个IPDiffServ实时记费管理机制，它通过在拥塞时执行优化的业务量工程，可以在保持业务类价格不变的情况下快速解除拥塞. 该机制不但可以提高网络的服务质量（QoS）保证能力，而且可以提高网络的抗拥塞能力，也可提高网络提供业务的性能价格比. 仿真结果证明了该机制的优越性.     

电力无线专网中面向安全风险的分布式资源分配方法

针对电力无线专网中强干扰、高故障风险等场景下保障终端通信的问题，提出了一种面向安全风险的高能效分布式资源分配方法。首先，分析基站的能耗组成，建立系统能效最大化的资源分配模型；然后，采用K-means++算法对网络中的基站进行分簇，从而将整个网络划分成多个独立区域，并在各个簇内单独处理高风险基站；其次，在每个簇内，基于基站的风险值对高风险基站进行休眠，并把高风险基站下的用户转移连接到同一簇内的其他基站；最后，在各个簇内进一步优化正常工作基站的传输功率。理论分析和仿真实验结果表明，基站分簇操作大幅降低了基站休眠和功率优化分配的复杂度，并且在关闭了高风险基站之后，整体网络的能效从0.158 9 Mb/J提升至0.195 4 Mb/J。所提的分布式资源分配方法能够有效提高系统的能量效率。     

相关衰落信道下的一种层间联合自适应SR-ARQ传输机制

传统自适应传输机制在相关慢衰落信道下有较差的系统性能.针对相关衰落信道,提出了一种层间联合自适应传输机制.利用有限状态马尔可夫链来描述相关衰落信道,同时通过构建一个多状态马尔可夫系统模型来分析系统吞吐性能,并对调制方式和传输分组大小进行优化.另外,推导了系统平均吞吐性能的表达式.仿真结果显示所提出的自适应传输机制在相关衰落信道上能获得更好的系统性能.     

基于软交换的集群媒体服务器高可用性系统建模与分析

在研究基于软交换的集群媒体服务器的系统结构基础上,提出了一个高可用性系统方案。利用广义随机Petri网理论对高可用性方案进行了建模和仿真实验。实验结果表明,该方案可以显著提高系统的可用性,是一个有效方案。基于可用性模型分析了系统修复速率、请求处理机数量、以及请求处理机故障特征对集群可用性的影响,分析结论对基于软交换的集群媒体服务器的可用性设计具有重要参考价值。     

3G中增强的3层动态位置管理建模与分析

基于3G网络中由HLR(home location register)、GLR(gateway location register)、VLR(visitor location register)构成的3层数据库结构,提出了基于移动的增强动态位置管理策略,重点分析了该策略下位置更新和寻呼的代价模型。并使用该代价模型对3G网络中基于移动的增强动态位置管理策略、基于移动的基本动态位置管理策略和静态位置管理策略进行了评价,计算结果显示增强动态位置管理策略要优于基于移动的基本位置管理策略和静态位置管理策略。     

信息隐写与隐写分析研究框架探讨

文章分析了广义信息隐藏研究中存在的问题，提出引入全信息理论和模糊信息处理的思想进行研究-对信息空间从三个层面上进行了分类，将隐写和隐写分析问题放在信息空间中进行研究，建立了隐写分析研究框架.     

基于NetFlow的网络异常流量检测

NetFlow可以提供网络中IP流的信息。这些流的信息有多种用途，包括网管、网络规划、ISP计费等。在网络安全领域，NetFlow提供的IP流信息可以用来分析网络中的异常流量，这是对现有的基于特征的NIDS的很好的补充。本文介绍了Net—Flow—based Anomaly Traffic Analyzer，一个基于NetFlow的网络异常流量检测系统，并通过一些实验证明了该系统的有效性。