基于非线性规划的链路丢包率推理算法

针对目前大多数链路丢包率推理算法不能兼顾精度和速度的问题,该文提出一种新的覆盖网链路丢包率推理算法,算法通过将链路丢包率推理问题转换为求解非线性规划的最优化解问题,从而较准确地计算出所有链路的丢包率。该算法仅需对每条端到端路径进行一次测量,且没有额外部署成本。通过软件模拟和Internet实验对算法性能进行了验证,实验结果证明了算法的可行性及优越性。     

基于子树丢包模式的链路丢包率快速推断算法

为提高网络链路丢包率的测量速度,本文提出一种基于子树丢包模式的链路丢包率推断算法.该算法通过选择合理的链路丢包率初始值以减少迭代次数;根据端到端测量结果将网络拓扑划分为传输状态确定性区域和非确定性区域,避免确定性区域冗余分解造成的时间开销;通过对非确定性区域子树丢包模式按层分解,以子树丢包模式为基本计算单元,减少非确定性区域链路丢包的重复分解过程,提高链路丢包率计算速度.仿真结果表明,该算法能在不损失测量精度的前提下,减少链路丢包率测量总时间,提高测量速度.     

单源多径路由网络拥塞链路识别

针对多径路由带来的端到端测量路径不确定性以及布尔模型不能很好地解决多拥塞链路的问题,该文在识别端到端测量路径的基础上,提出一种基于扩展状态空间的网络拥塞链路识别算法。首先基于探测流时延相关性进行自适应聚类,进而得到各路径与探测流之间的映射关系。其次采用多门限的方式,将具有不同丢包程度的拥塞路径赋予不同的拥塞状态。最后将拥塞链路识别问题转化为一个约束最优化问题,并提出基于扩展状态空间的拥塞链路识别算法(ESSCLI)算法求解该问题。仿真结果表明,ESSCLI算法能够在多种不同网络场景下取得比当前算法更高的拥塞链路检测率。     

基于k阶马尔可夫链的单播网络丢包层析成像

该文针对时域相关的网络链路丢包估计问题,提出一种基于k阶马尔可夫链的单播网络丢包层析成像方法。该方法首先引入k阶马尔可夫链描述网络链路丢包过程,然后用最大伪似然方法估计k阶马尔可夫链链路丢包模型的状态转移概率。当k足够大时,该文方法可以根据单播端到端测量数据,准确地估计出网络链路上每个数据包丢失的概率。ns-2仿真验证了该文方法的有效性。     

一种非平稳网络链路丢包率层析成像方法

现有网络链路参数估计方法大都假设网络链路状态在测量周期内是平稳的,不能获得网络链路参数的时变特征。该文提出了一种非平稳的网络链路丢包率层析成像方法。假定在一个相对较小的时窗内,丢包率随时间变化的曲线可用一个k阶可导的函数来描述;用网络层析成像的方法求得这些函数的k阶泰勒展开式;然后根据各时窗内的逼近结果,用反比距离加权估计整个测量周期内链路的时变丢包率。NS2仿真验证了该方法能有效追踪链路丢包率的变化,且优于现有的网络链路丢包率层析成像方法。     

一种网络总可用带宽测量方法

可用带宽测量对于网络行为分析、网络业务质量保证、网络负载均衡、流媒体的速率控制、服务器的动态选择、覆盖网络（overlaynetwork）的路由选择、拥塞控制等网络应用有很重要的意义。现有的可用带宽测量方法主要对端到端路径进行测量。由于网络总可用带宽不能由路径的可用带宽简单相加获得,而且路径上的瓶颈链路不一定是网络的瓶颈链路,文章提出了一种网络总可用带宽测量方法,仿真实验验证了方法的有效性。     

四表集抄通信网络虚拟化方案及组网算法研究

为了实现四表(水,电,气,热)集抄行业之间的业务数据隔离,提升本地网络的稳定性和覆盖能力,该文提出四表集抄通信网络虚拟化方案。该方案采用虚拟接入点名称(APN)技术以及软件定义网络(SDN)切片技术构成端到端隔离的业务数据采集通道;采用微功率无线和低压电力线载波构成实时可靠的本地双模虚拟网络,进一步提出基于全局链路状态和分层迭代的组网算法。仿真及现场验证结果表明,该方案降低了采集数据的丢包率和传输时延,提高业务支撑能力,保障行业之间的业务数据隔离,提升通信网络基础设施复用能力。     

AODV带宽估计和链路稳定度的QoS扩展研究

在AVAODV协议的基础上增加带宽估计选项,提出了一种基于带宽估计和链路稳定度的QVAODV路由协议。QVAODV协议在路径寻找的过程中,通过带宽估计和链路稳定度的计算,从众多备选路径中选择出一条满足带宽需求和链路稳定度最好的路径来提供QoS保证。仿真实验结果表明,在相同实验条件下QVAODV协议在数据丢包率、平均端到端分组时延和平均路由开销性能方面与AVAODV协议相比均有提高。     

基于组移动模型的链路生存时间预测

战术Ad Hoc网络拓扑结构的动态变化,导致了重复路由操作频繁发生。基于组移动模型的特点,不依赖GPS等辅助设备获得节点相关参数,提出了一种新的链路生存时间预测算法,并将其应用于路径选择,避开生存时间短的链路,选择一条由最长生存时间链路组成的路径,以减轻拓扑变化对路径稳定性的影响。仿真表明,该算法能够有效地降低数据的丢包率和端到端的时延,减少路由的重操作次数,提高了路径的稳定性。     

一种IP网络带宽和时延的有效测量模型

提出了一种同时测量IP网络带宽利用率和路径时延的测量模型,能够有效降低网络测量的开销。以顶点覆盖和边覆盖的相关理论为基础,证明了以最小代价混合覆盖全网的问题是NP难的。同时提出了一种改进两阶段算法,可以有效地确定最小覆盖集。性能仿真结果显示改进后的算法对大范围的网络拓扑有效。     

Multicast topology inference from measured end-to-end loss

The use of multicast inference on end-to-end measurement has been proposed as a means to infer network internal characteristics such as packet link loss rate and delay. We propose three types of algorithm that use loss measurements to infer the underlying multicast topology: (i) a grouping estimator that exploits the monotonicity of loss rates with increasing path length; (ii) a maximum-likelihood estimator (MLE); and (iii) a Bayesian estimator. We establish their consistency, compare their complexity and accuracy, and analyze the modes of failure and their asymptotic probabilities     

基于端到端报文丢失的网络拓扑推测算法研究

在分析现有网络拓扑推测算法的基础上,提出了一种基于端到端报文丢失性能的网络拓扑推测方法,该方法通过比较节点间的Hamming距离和节点接收到的报文数量推测网络拓扑,在推测拓扑过程中不需要网络内部节点的协助。通过理论比较和分析,证明该方法在推测精度上比现有的方法有显著的提高,最后利用仿真实验验证了该方法的有效性和准确性,推测精度比现有方法提高了20%。     

A Geometric Approach to Improving Active Packet Loss Measurement

Measurement and estimation of packet loss characteristics are challenging due to the relatively rare occurrence and typically short duration of packet loss episodes. While active probe tools are commonly used to measure packet loss on end-to-end paths, there has been little analysis of the accuracy of these tools or their impact on the network. The objective of our study is to understand how to measure packet loss episodes accurately with end-to-end probes. We begin by testing the capability of standard Poisson-modulated end-to-end measurements of loss in a controlled laboratory environment using IP routers and commodity end hosts. Our tests show that loss characteristics reported from such Poisson-modulated probe tools can be quite inaccurate over a range of traffic conditions. Motivated by these observations, we introduce a new algorithm for packet loss measurement that is designed to overcome the deficiencies in standard Poisson-based tools. Specifically, our method entails probe experiments that follow a geometric distribution to 1) enable an explicit trade-off between accuracy and impact on the network, and 2) enable more accurate measurements than standard Poisson probing at the same rate. We evaluate the capabilities of our methodology experimentally by developing and implementing a prototype tool, called BADABING. The experiments demonstrate the trade-offs between impact on the network and measurement accuracy. We show that BADABING reports loss characteristics far more accurately than traditional loss measurement tools.     

Multicast-based loss inference with missing data

Network tomography using multicast probes enables inference of loss characteristics of internal network links from reports of end-to-end loss seen at multicast receivers. We develop estimators for internal loss rates when reports are not available on all probes or from all receivers. This problem is motivated by the use of unreliable transport protocols, such as reliable transport protocol, to transmit loss reports to a collector for inference. We use a maximum-likelihood (ML) approach in which we apply the expectation maximization (EM) algorithm to provide an approximating solution to the the ML estimator for the incomplete data problem. We present a concrete realization of the algorithm that can be applied to measured data. For classes of models, we establish identifiability of the probe and report loss parameters, and convergence of the EM sequence to the maximum-likelihood estimator (MLE). Numerical results suggest that these properties hold more generally. We derive convergence rates for the EM iterates, and the estimation error of the MLE. Finally, we evaluate the accuracy and convergence rate through extensive simulations     

Network management agent allocation scheme in mesh networks

In this letter, we propose a scheme for constructing a reliable alarm detection structure in the communication networks. We investigate how to allocate a minimal set of management agents and still cover all alarms in mesh networks under the assumption that alarms are delivered along provisioned paths. We also consider the probabilistic nature of alarm loss and propose an efficient scheme for allocating a minimal set of agents while keeping the overall alarm loss probability below a threshold.     

Optimal partition of QoS requirements on unicast paths andmulticast trees

We investigate the problem of optimal resource allocation for end-to-end QoS requirements on unicast paths and multicast trees. Specifically, we consider a framework in which resource allocation is based on local QoS requirements at each network link, and associated with each link is a cost function that increases with the severity of the QoS requirement. Accordingly, the problem that we address is how to partition an end-to-end QoS requirement into local requirements, such that the overall cost is minimized. We establish efficient (polynomial) solutions for both unicast and multicast connections. These results provide the required foundations for the corresponding QoS routing schemes, which identify either paths or trees that lead to minimal overall cost. In addition, we show that our framework provides better tools for coping with other fundamental multicast problems, such as dynamic tree maintenance