基于丢包率的多播网络拓扑推断算法

在分析现有的网络拓扑推断算法的基础上,提出一种改进的基于丢包率的多播网络拓扑推断算法。结合接收节点的层次信息、汉明距离及节点接收的探测包数量,能够同时推断网络拓扑结构和链路丢包率,并根据链路丢包率的估计值动态地调整拓扑推断的判决门限值,提高了推断的准确性。仿真实验证明,与现有算法相比,该算法具有更好的性能。     

无线传感器网络的能量均衡路由算法

在分析现有的网络拓扑推断算法的基础上,提出一种改进的基于丢包率的多播网络拓扑推断算法。结合接收节点的层次信息、汉明距离及节点接收的探测包数量,能够同时推断网络拓扑结构和链路丢包率,并根据链路丢包率的估计值动态地调整拓扑推断的判决门限值,提高了推断的准确性。仿真实验证明,与现有算法相比,该算法具有更好的性能。     

基于丢包率的多播网络拓扑推断算法

在已有的网络拓扑推断算法的基础上,提出一种改进的基于丢包率的多播网络拓扑推断算法。依据各层次节点及接收节点的层次信息,利用海明距离和节点接收的探测包数目,能够同时推断网络拓扑结构和链路丢包率,并且在计算链路丢包率的估计值时动态地调整拓扑推断的判决门限值,从而提高了推断的准确性。仿真实验证明,与现有算法相比,该算法具有更好的性能。     

一种大规模IP网络多链路拥塞推理算法

基于最小集覆盖理论的拥塞链路推理算法,仅对共享瓶颈链路进行推理,当拥塞路径存在多条链路拥塞时,算法的推理性能急剧下降.针对此问题,提出一种基于贝叶斯最大后验（Bayesian Maximum A-Posterior,BMAP）改进的拉格朗日松弛次梯度推理算法（Lagrange Relaxation Sub-gradient algorithm based on BMAP,LRSBMAP）.针对推理算法中链路覆盖范围对算法推理性能的影响,以及探针部署及额外E2E路径探测发包的开销问题,提出设置度阈值（Degree Threshold Value,DTV）参数预选待测IP网络收发包路由器节点,通过引入优选系数ρ,在保证链路覆盖范围的基础上,兼顾开销问题,确保算法的推理性能.针对大规模IP网络多链路拥塞场景下,链路先验概率求解方程组系数矩阵的稀疏性,提出一b种对称逐次超松弛SSOR（Symmetry Successive Over-Relaxation）分裂预处理共轭梯度法（Preconditioned Conjugate Gradient method based on SSOR,PCG_SSOR）求解链路先验概率近似唯一解的方法,防止算法求解失败.实验验证了提出算法的准确性及鲁棒性.     

基于流量调度的SDN数据中心网络拥塞控制算法

针对采用软件定义网络(SDN)的数据中心网络拥塞的问题,提出一种基于流量调度的数据中心网络拥塞控制算法。当链路发生拥塞时,该算法首先判别拥塞链路中 链路上关键度最大的大流,然后对大流进行重路由计算,选择调度开销最小的流,并进行调度代价计算,最后对调度代价最小的流进行调度。实验结果表明,所提算法能够有效缓解网络拥塞,降低丢包率,提高链路利用率,使得网络性能更为稳定。     

卫星网络中一种改进的TCPW算法

针对卫星网络通信路径改变会引起往返时延剧烈变化,以及长延时环境会引起TCPW校准拥塞窗口精度下降的问题,提出了一种TCPW的改进方案——TCPW-CC。该算法减小了空间链路传播时延对算法性能的影响,利用星上拥塞系数δ作为调整拥塞窗口的依据,同时将窗口调整从每丢包后进行一次修改为每一个RTT进行一次,使得窗口的增长不再激进。仿真实验表明,所提改进方案提高了网络吞吐量,降低了丢包率。     

基于改进Dijkstra算法的配用电通信网流量调度策略

针对配用电通信网中数据汇聚易产生拥塞的问题,提出了一种复合边权值流量调度路由算法。首先,依据跳数建立节点分层模型;然后,划分配用电业务优先级和节点拥塞等级;最后,以跳数、流量负载率和链路利用率为综合指标计算边权值,对需要流量调度的节点根据改进的Dijkstra算法进行路由选择,同时对重度拥塞节点按照配用电业务优先级进行调度。与最短路径（SPF）算法和贪婪背压算法（GBRA）相比,在数据生成率为80 kb/s时,所提算法紧急型业务丢包率分别减少了81.3%和67.7%,关键型业务丢包率分别减少了79%和63.8%。仿真结果表明,所提算法能有效缓解网络拥塞,提高网络有效吞吐量,降低网络端到端时延和高优先级业务的丢包率。     

一种与IPSec兼容的基于有线/无线混合网络的TCP性能优化机制

传统的TCP协议,假设丢包都是由网络拥塞造成的,这不适用于错误丢包比拥塞丢包更容易发生的无线链路,而且现有的很多改进方案无法用于加密通讯中.在分析现有改进算法的基础上,提出一种适用于有线/无线混合网络IPSec兼容的端到端的优化机制.通过接收端数据包到达时间间隔的变化累积来判断无线链路的状况,用ACK标记ELN通知发送端,避免不必要的拥塞控制而导致性能下降.通过NS2仿真实验表明该机制能有效提高TCP传输性能还与现有的安全机制兼容.     

OSPF协议中ABR动态选举研究

在开放式最短路径优先(OSPF)协议网络中,人为指定区域边界路由器(ABR)不能适应网络负荷的动态改变。为此,提出一种依据当前流量需求和链路带宽的动态选举ABR的算法。该算法根据网络流量的改变动态地选择ABR,实现了避免链路拥塞和提高网络性能的目标。NS2仿真结果表明,该算法在端到端时延、丢包率等方面均能获得较好的性能。     

基于DupAck的Ad Hoc网络TCP性能改进

为改进传输控制协议(TCP)在无线网络环境下的性能,分析Ad Hoc网络数据丢失的原因,提出一种区分无线丢包和拥塞丢包的算法。该算法通过在发送端检测返回的重复Ack的相对单向传输时延,探测到网络真实的拥塞状况,以便采取合理的拥塞控制措施。仿真结果表明,该算法能够正确区分无线丢包和拥塞丢包,改善Ad Hoc网络的TCP性能。     

Identify Congested Links Based on Enlarged State Space

When paths share a common congested link, they will all suffer from a performance degradation. Boolean tomography exploits these performance-level correlations between different paths to identify the congested links. It is clear that the congestion of a path will be distinctly intensive when it traverses multiple congested links. We adopt an enlarged state space model to mirror different congestion levels and employ a system of integer equations, instead of Boolean equations, to describe relationships between the path states and the link states. We recast the problem of identifying congested links into a constraint optimization problem, including Boolean tomography as a special case. For a logical tree, we propose an up-to-bottom algorithm and prove that it always achieves a solution to the problem. Compared with existing algorithms, the simulation results show that our proposed algorithm achieves a higher detection rate while keeping a low false positive rate.     

基于粒子群的TCP非凸优化速率控制算法

为了有效地解决网络中拥塞问题,针对实际网络中存在非弹性流的情况,考虑了网络中非凸优化速率控制问题。基于最大化用户效用函数框架,去掉了以往研究中对效用函数的严格假设,利用粒子群方法设计了分布式速率控制算法。算法中链路从网络获知拥塞链路的条数,用户根据对应的效用函数和拥塞反馈信息调整自身速率。仿真结果表明,算法可以很快地收敛到最优速率。     

Congestion control based dynamic routing in ATM networks

In this paper we describe briefly a dynamic multi-path algorithm that has been considered for connection oriented asynchronous transfer mode (ATM) networks. Our scheme takes advantage of a cell multiplexing capability that has particular advantage in networks supporting variable bit rate (VBR) traffic. The fundamental objective of the scheme is to propose a congestion control based scheme that bridges the gap between routing and congestion control as the network becomes congested. The proposed routing scheme works as a shortest path first algorithm under light traffic conditions. However, as the shortest path becomes congested under unbalanced heavy traffic, the source uses multiple paths when and if available to distribute the calls and reduce cell loss. This mechanism will provide good Quality of Service for clients within the given constraints. We compare the performance of the proposed scheme with other competitive schemes. The throughput and cell loss performance are compared via simulations. These have been carried out concentrating on a five node network, each with varying traffic patterns, with the intention of gaining insight into the strengths and weaknesses of the various schemes.     

A Fast Multicast-based Approach to Inferring Loss Performance

A simple bottom-up loss inference approach is proposed in reference [1], which infers the link loss rate from the multicast in the end-to-end measurements. However, the spatial independence is assumed in the loss model. In fact the spatial dependence is present in packet losses, so the loss model assumption is violated. Moreover, with this approach, it is difficult to identify all the cuts of a multi-level tree, which is used to estimate the network-internal link loss rate. To overcome these shortcomings, an improved approach is proposed in this paper. In the proposed approach, the virtual link is employed to infer the network-internal link loss performance without using the concept cuts and the spatial dependence between the links is taken into account. Simulation results show that the inferred results correctly show the loss trend of the links. The proposed approach can also be extended to be the general tree topology.     

Efficient Loss Inference Algorithm Using Unicast End-to-End Measurements

We address the problem of loss rates inference from end-to-end unicast measurements. Like other network tomography problems, it requires solving a system of equations that involve measurement values and the loss rates of links. However, the equations do not have a unique solution in general. One kind of method imposes unrealistic assumption on the system, e.g. the uniform prior probability of a link being congested. Other methods use multiple probe measurements to acquire more information about the system that may generate many additional overhead costs. In this paper, we demonstrate that a considerable portion (more than 95 %) of links could be uniquely identified by current measurements directly. Then we utilize the information of these determined links to acquire the global distribution of the system that can help to infer the rest loss rates. Moreover, we derive an upper bound on the accuracy of a congestion localization problem using the Bayesian network that provides a necessary condition for achieving the 0—error diagnosis. Finally, we evaluate our new method and a former representative method by both the simulation and the real implementation in the PlanetLab network. The results show that our method not only makes a great improvement on the accuracy, but also reduces the probe costs and the running time to an extremely low level. Furthermore, our method can also perform well in large and more congested networks.     

基于资源整合的节能虚拟网络重配置算法

针对虚拟网络映射中能耗过高、接收率偏低和负载不够均衡等问题,提出一种基于虚拟资源整合的综合性重配置算法——HEAR算法。该重配置算法分为两个阶段:节点重配置阶段优先将映射虚拟节点最少的物理节点上的虚拟节点及其相连虚拟链路迁移,挂起或关闭空负载的物理节点来达到节能的目的;此外对这些迁移节点的目标物理节点进行筛选,避免选择过度拥塞的物理节点达到提高接收率和均衡负载的目的。链路重配置阶段采用能耗感知的方法选择可用于迁移的物理链路集合,再用Dijkstra算法选择最短物理路径并将相关路径迁移过去。实验结果表明,HEAR算法比启发式重配置算法平均能耗下降约20%,接收率提高约10%。     

路网信息不完备条件下的动态最短路搜索

针对路网信息不完备性、路网结构特征和驾驶员习惯等因素,研究最短路搜索问题。提出以全局规划和局部规划相结合的动态最短路混合规划方法：全局规划中,基于参数d/l（起终点距离d与平均路段长度l之比）,确定路径搜索区域的椭圆方程,运用Dijkstra算法生成静态的全局最短路径;局部规划中,结合路网结构特征、突发事件影响范围,提出改进Bug算法,以避免车辆进入全局最短路径上发生的紧急事件或严重堵塞区域,实现动态诱导。仿真实验结果表明,混合规划方法能在路网信息不完备条件下实现最短路径动态诱导,有效避开拥堵区域。     

A Two-Stage Approach for Network Monitoring

A goal of network tomography is to infer the status (e.g. delay) of congested links internal to a network, through end-to-end measurements at boundary nodes (end-hosts) via insertion of probe signals. Because (a) probing constitutes traffic overhead, and (b) in any typical scenario, the number of congested links is a small fraction of the total number in the network, a desirable design objective is to identify those (few) congested links using a minimum number of probes. In this paper, we make a contribution to solving this problem, by proposing a new two-stage approach for this problem. First, we develop a binary observation model linking end-to-end observations with individual link statuses and derive necessary and sufficient conditions for whether at least one link in the network is congested. Stage I of the proposed method shows that achieving 1-identifiability with a minimum number of probes is equivalent to the familiar minimum set covering problem that can be efficiently solved via a greedy heuristic. A sequential algorithm is described, leading to a significantly lowered computational complexity vis-a-vis a batch algorithm. Next, a binary splitting algorithm originally developed in group testing is used to identify the location of the congested links. The proposed scheme is evaluated by simulations in OPNET and experiments on the PlanetLab testbed to validate the advantages of our 2-stage approach vis-a-vis a conventional (batch) algorithm.     

Can high-speed networks survive with DropTail queues management?

It has been observed that TCP connections that go through multiple congested links (MCL) have a smaller transmission rate than the other connections. Such TCP behavior is a result of two components (i) the cumulative packet losses that a flow experiences at each router along its path; (ii) the longer round trip times (RTTs) suffered by such flows due to non-negligible queueing delays at congested routers. This double “bias” against connections with MCLs has been shown to approximate the so-called minimum potential delay fairness principle in the current Internet. Despite the recent proliferation of new congestion control proposals for TCP in high-speed networks, it is still unclear what kind of fairness principle could be achieved with such newly proposed congestion control protocols in high-speed networks with large-delays. Studies already show that some high-speed TCP variants may cause surprisingly severe RTT unfairness in high-speed networks with DropTail routers.This paper studies the problem of unfairness in high-speed networks with some well-known high-speed TCP variants in presence of multiple congested links and highlights the severity of such unfairness when DropTail queue management is adopted.Through a simple synchronized loss model analysis, we show how synchronized losses with DropTail in high-speed networks could lead to severe RTT unfairness and drop probability (DP) unfairness; while random marking AQM schemes, which break the packet loss synchrony mitigate such unfairness dramatically by ensuring that the packet loss probability of a flow is the sum of the loss probabilities on the congested routers it crosses.Extensive simulations are carried out and the results support our findings.