应用网络仿真技术进行网络评价

阐述了应用网络仿真技术进行网络性能评价和预测的方法,包括性能指标选取、仿真试验设计、仿真性能参数计算、仿真结果处理与分析的方法,并给出了对一个具体的多媒体网络进行性能评价的应用实例。     

基于三角模糊数层次分析法与网络仿真的网络整体性能评价研究

结合模糊理论提出了改进的模糊AHP算法——基于三角模糊数层次分析法(Triangular Fuzzy Number Analytic Hierarchy Process,TFAHP),使得结论更加客观、合理,同时简化了AHP算法的步骤。在提出基于THAHP网络整体性能评价模型的基础上,阐述了应用网络仿真技术进行网络整体性能评价的方法。包括性能指标选取、仿真试验设计、仿真性能参数计算和仿真结果处理与分析的方法,并给出了对一个具体的多媒体网络进行网络整体性能评价的应用实例。     

基于FAHP的网络性能综合评价的研究*

针对工业现场对有线/无线异构网络的性能要求,提出了一种基于模糊层次分析法( FAHP)的网络性能综合评价方法,着重分析了网络的综合性能指标参数的获取和利用FAHP算法确定各指标权重的过程。通过对不同业务和参数的多媒体仿真网络的性能评价验证算法的准确性,最后针对一个具体的有线/无线异构仿真网络进行评价,比较了不同用户要求下得到的网络性能综合评价值。实验结果表明,采用基于FAHP的网络性能评价算法对于工业异构网络的性能评价是准确有效的。     

蓝牙Ad hoc网络形成算法的性能评价

评价一个蓝牙Adhoc网络形成算法的优劣可以用不同方法和性能指标来衡量。文中首先介绍了蓝牙Adhoc网络的拓扑结构,然后讨论了评价蓝牙Adhoc网络形成算法的主要手段和性能指标,对目前主要的蓝牙Adhoc网络形成协议的性能进行了总结和比较。此外,还对树型散射网形成(Tree Scattemet Formation,TSF)协议的部分性能指标进行了仿真,给出了相应的性能仿真曲线。最后总结现有网络形成协议存在的问题,分析业界关注的重点及今后可能的研究方向。     

基于神经网络的计算机网络性能评价

为多媒体网络定义一个合理有效的性能分析模型,以描述基于神经网络的计算机网络性能评价过程,其中包括评价指标测量值的预处理、神经网络结构设计、评价仿真以及仿真结果分析4个部分。仿真实验结果表明,基于神经网络的评价方法无须建立复杂的数学模型,能够对多个网络性能指标进行综合考虑,从而实现在给定输入负载下的网络性能判定。     

网络性能分析评价方法及其计算机仿真方法讨论

网络性能分析评价的一般方法包括解析法、数值法和仿真法。仿真法是目前计算机通信网络系统性能分析的主流方法。该文讨论了网络性能分析评价的般方法和局域网网络性能的计算机仿真分析方法,并简要介绍了一个专用网络仿真分析软件。     

基于网络模拟的VOIP性能评价方法

结合一个实际的网络工程，采用网络模拟的方法对VOIP性能进行了分析和评价，并且针对不同网络方案的情况进行了对比，同时，详细介绍了VOIP的评价指标以及WWW业务，VOIP业务的流量模型。通过文中所述的网络模拟试验，可以对多种网络设计方案进行综合比较，为网络工程方案的选择提供定量依据，使网络系统设计更接近实际，更经济有效。     

无线传感器网络路由评测工具的设计与实现

无线传感器的路由评测很难通过实验获得,实践中上百个节点的实验已经难以管理和维护,包含大量节点的无线传感器网络更是难以通过实验进行评测。通过计算机对无线传感器网络进行模拟,并对路由协议的性能进行评价成为一个无线网络研究中的一个难题。在分析现有无线网络模拟平台的基础上,设计了一个针对无线传感器网络路由协议的评测工具,并用该工具成功对LEACH协议算法进行了评测。     

传感器网络中拓扑控制与网络干扰性分析

本文分析比较几种衡量干扰的典型方法,提出了一个新的干扰模型,能够描述整个网络的干扰性。根据不同的干扰标准,在计算机上对几种拓扑结构干扰特性进行模拟,给出并分析了模拟仿真结果。     

局域网性能分析与评价技术研究

研究了网络性能量度,并介绍对性能分析和评价的方法。该文还对性能模型的建立及分析和评价的步骤进行了论述,最后文章给出一个令牌环形网的例子及计算机模拟结果。     

改进的广义预测流量控制策略在多媒体网络中的应用*

针对计算机网络多媒体数据业务传输过程中存在的大时延问题,在对广义预测流量控制机制进行分析研究的基础上,提出了一种改进的广义预测流量控制算法。仿真结果表明,该算法能够快速有效地调节业务分组发送速率和缓冲区队列,提高链路利用率,有效地克服了时延影响。该算法实现简单,适合计算机控制系统实现,在多媒体网络中具有实际应用价值。     

多媒体通信中的一种视频平滑方案

多媒体通信中一个很重要的服务质量指标就是视频数据传输的平滑度,但平滑度往往是与网络传输流量相矛盾的.文章正是针对这一矛盾,通过引入控制论的思想并利用神经网络预测流量的特征参数,提出了一种解决多媒体通信中视频数据流平滑的方案.通过实验模拟,证明了该方案能很好地解决多媒体通信中的这一矛盾,使视频流量和平滑度折衷后达到最优效果.     

IPTV architecture for an IMS environment with dynamic QoS adaptation

This paper describes the development, implementation and evaluation of a SIP based IPTV architecture with a new dynamic QoS adaptation method and signaling structure. The implemented QoS adaptation method allows dynamic updates of session parameters, maximizing the QoE and turning the solution suitable for live multimedia streaming, independently of the cast mode (unicast or multicast). The new SIP signaling structure, for session and media control, was developed following an All-SIP approach and a hybrid SIP+RTSP approach, both suited for an IMS environment, in order to compare the system behavior and performance using either approach. The details of both the IPTV Application Server and the IPTV Client prototypical implementations are described, as well as the results of field tests carried out across different Fixed and Mobile access networks for each of the signaling structures. The proposed IPTV architecture revealed to be suitable for scalable converged networks, due to its flexible multimedia delivery of personalized streams over a variety of network infrastructures, namely, Mobile radio networks.     

Learning Based Neural Similarity Metrics for Multimedia Data Mining

Multimedia data mining refers to pattern discovery, rule extraction and knowledge acquisition from multimedia database. Two typical tasks in multimedia data mining are of visual data classification and clustering in terms of semantics. Usually performance of such classification or clustering systems may not be favorable due to the use of low-level features for image representation, and also some improper similarity metrics for measuring the closeness between multimedia objects as well. This paper considers a problem of modeling similarity for semantic image clustering. A collection of semantic images and feed-forward neural networks are used to approximate a characteristic function of equivalence classes, which is termed as a learning pseudo metric (LPM). Empirical criteria on evaluating the goodness of the LPM are established. A LPM based k-Mean rule is then employed for the semantic image clustering practice, where two impurity indices, classification performance and robustness are used for performance evaluation. An artificial image database with 11 semantics is employed for our simulation studies. Results demonstrate the merits and usefulness of our proposed techniques for multimedia data mining.     

Cross-layer routing metrics for mesh networks: Current status and research directions

Despite efforts to improve the current IEEE 802.11 standard to fully optimize the physical layer, the performance of wireless mesh networks still depends on the routing process for a correct selection of routes. With regard to this question, several cross-layer routing metrics have been developed to improve wireless multi-hop mesh routing. This paper sets out a new taxonomy that can be used to help understand, classify and compare the state-of-the-art situation with regard to cross-layer routing metrics for wireless mesh networks. A simulation study has been carried out to evaluate the capability of the most recent and promising cross-layer routing metrics to support multimedia applications, such as Voice over IP. The evaluation of the routing metrics has been undertaken from three main perspectives: user perception, network performance, and routing stability. The simulation results show that the impact of routing metrics is more noticeable on the network and routing stability evaluation parameters than on the user-perception parameters. Furthermore, the results show that the routing metrics, the level of stability attained, and the application performance are interdependent. Finally, there is a discussion of the direction that future research might take with regard to some open issues in the design of routing metrics for wireless mesh networks.     

OMNET++与H. 264视频编解码器的联合仿真研究

近年来流行的网络仿真平台OMNET++由于欠缺对应用层视频特性的考虑而不能有效地评估在视频传输等多媒体业务的要求下无线Ad hoc网络中协议算法的性能。为了解决以上问题,提出了一种OMNET++与H. 264视频编解码器联合仿真的方法,它以H. 264编码器作为OMNET++的数据源,并以H. 264解码器作为视频传输质量的检验平台。利用提出的联合仿真方法,对视频在无线Ad hoc网络中的传输进行了仿真,并评估了该网络中IEEE802. 11多址接入协议的性能。实验表明,提出的联合仿真方法能够为无线Ad hoc网络协议算法的设计与改进提供有效的检验平台。     

Multimedia and firewalls: a performance perspective

Firewalls are a well-established security mechanism to restrict the traffic exchanged between networks to a certain subset of users and applications. In order to cope with new application types like multimedia, new firewall architectures are necessary. The performance of these new architectures is a critical factor because Quality of Service (QoS) demands of multimedia applications have to be taken into account. We show how the performance of firewall architectures for multimedia applications can be determined. We present a model to describe the performance of multimedia firewall architectures. This model can be used to dimension firewalls for usage with multimedia applications. In addition, we present the results of a lab experiment, used to evaluate the performance of a distributed firewall architecture and to validate the model.