Design and evaluation of an efficient traffic control scheme for integrated voice,video, and data over asynchronous transfer mode networks: Explicit allowed rate algorithm

Asychronous transfer mode (ATM) networks are high‐speed networks with guaranteed quality of service. The main cause of congestion in ATM networks is over utilization of physical bandwidth. Unlike constant bit‐rate (CBR) traffic, the bandwidth reserved by variable bit‐rate (VBR) traffic is not fully utilized at all instances. Hence, this unused bandwidth is allocated to available bit‐rate (ABR) traffic. As the bandwidth used by VBR traffic changes, available bandwidth for ABR traffic varies; i.e., available bandwidth for ABR traffic is inversely proportional to the bandwidth used by the VBR traffic. Based on this fact, a rate‐based congestion control algorithm, Explicit Allowed Rate Algorithm (EARA), is presented in this paper. EARA is compared with Proportional Rate Control Algorithm (PRCA) and Explicit Rate Indication Congestion Avoidance Algorithm (ERICA), in both LAN and WAN environments. Simulations of all three algorithms are conducted under both congestion and fairness configurations with simultaneous generation of CBR, rt‐VBR, nrt‐VBR and ABR traffic. The results show that, with very small over‐head on the switch, EARA significantly decreases the required buffer space and improves the network throughput. Copyright © 1999 John Wiley & Sons, Ltd.     

基于整数规划的优化拥挤度的增量式布局算法

提出了一种降低走线拥挤的标准单元增量式布局算法C- ECOP.首先通过一种新型的布线模型来估计芯片上的走线情况,然后构造一个整数线性规划问题来解决可能出现的相邻拥挤区域冲突问题.实验结果表明该算法能够有效地降低走线拥挤,保证初始布局的质量,并且具有很高的效率     

基于整数规划的优化拥挤度的增量式布局算法

提出了一种降低走线拥挤的标准单元增量式布局算法C-ECOP.首先通过一种新型的布线模型来估计芯片上的走线情况,然后构造一个整数线性规划问题来解决可能出现的相邻拥挤区域冲突问题.实验结果表明该算法能够有效地降低走线拥挤,保证初始布局的质量,并且具有很高的效率.     

A congestion reduction mechanism using D2D cooperative relay for M2M communication in the LTE‐A cellular network

The Long Term Evolution‐advanced cellular network is designed for human‐to‐human communication. When a large number of machine‐to‐machine (M2M) devices are trying to access the network simultaneously, it leads to a low random access (RA) successful rate and high congestion problem, which may cause the waste of radio resources, packet loss, latency, extra power consumption, and the worst, M2M service error. There is an urge to propose an efficient method for M2M communication on the LTE‐A network to resolve the congestion problem. In this paper, we propose a congestion reduction mechanism, which can analyze and model the RA procedure on the Long Term Evolution‐advanced network, to find out the collapse point in the RA procedure and then design a scheme named device‐to‐device cooperative relay scheme to relieve the congestion problem. Meanwhile, this work also adds a relay access barring algorithm to improve performance and an RA resource separation mechanism for human‐to‐human communication. The proposed method can effectively reduce the network congestion problem. Simulation results show that the network throughput and the congestion can be significantly improved using the proposed mechanism. Copyright © 2016 John Wiley & Sons, Ltd.     

一种基于校园网的流媒体拥塞控制路由策略

文章针对6PE校园网的特点,提出一种基于节点拥塞度约束的拥塞控制路由算法,在保证用户流QoS请求的同时,通过调整节点拥塞度来进行负载均衡,从而达到拥塞避免的目的.仿真实验结果表明,该策略能从一定程度上提高网络吞吐量及减少请求包的阻塞率,有利于流媒体传输.     

Evaluation,prediction and reduction of routing congestion

Routing congestion is a critical issue in deep submicron design technology and it becomes one of the most challenging problems in today's design flow. In this paper, various congestion-related metrics were defined and evaluated during placement stage of physical design flow. Our experiments show that the overflow metric results are more accurate than others. In addition, the bend distributions after detailed routing for IBM-PLACE benchmarks were extracted and used to guide a pure probabilistic method. Furthermore, router's behavior for congestion minimization was modeled and used to propose a true congestion prediction algorithm. Experimental results show that the proposed algorithm estimates the congestion more accurately than a commonly used method by about 21% on average. Additionally, a new congestion reduction algorithm is presented based on contour plotting. Our experiments show that our algorithm reduces the peak congestion by about 25% on average. In addition, comparing our results with a recent approach shows that our technique reduces congestion more by about 10% on average. In order to evaluate the results of white space allocations on the quality of our reduction technique, several other experiments were attempted. Various amounts of white space were added to several IBM-PLACE benchmarks and the contour plotting-based reduction technique was used to reduce the peak and average congestion. The experiments show that our technique works better on the benchmarks with more white space as it has more capability to distribute routing congestion evenly.     

基于半马尔科夫决策过程的视频传输拥塞控制算法

针对传输控制协议(TCP, transmission control protocol)的拥塞控制算法未能满足视频传输质量要求的问题,提出了一种基于半马尔科夫决策过程的视频传输拥塞控制算法。首先, 为克服目前基于峰值信噪比的视频质量评估方法实时性低的缺点,设计了一种可在线运行的无参考视频质量评估方法。其次,根据接收端视频质量的反馈,采用半马尔科夫决策过程对拥塞控制进行建模,并通过求解此模型得到拥塞控制参数的调整策略。仿真实验结果表明,与目前典型的拥塞控制算法相比,该算法不但具备更好的TCP友好性,而且有效地提高了解码后视频序列的主观和客观质量。     

Local stability of REM algorithm with time-varying delays

We investigate the local stability in equilibrium for an Internet congestion control algorithm proposed by Low (see IEEE/ACM Transactions on Networking, vol.7, p.861-875,1999). The network consists of multisource and one-bottleneck link with heterogenous time-varying propagation delays. Linear matrix inequality (LMI) stability criteria is presented for discrete congestion control algorithm of TCP/REM dual model, which can be efficiently and easily solved by the LMI toolbox provided by Matlab software. An important feature is to acquire the maximum network delays to guarantee the stability of congestion control algorithm, i.e., the scale stability domain of REM algorithm.     

Convolution Algorithm for the State Probability of Dynamic Networks

1IntroductionTheperformanceevaluationofdynamicnetworkshasbeenatopicingreatdemandsincethenetworkarose.Untiltheyearof1992,peoplehavetriedthemethods[IJ~[3)ofmeanvalueanalysis,Wilkinson'sequivalentsubstitution,blockingprobabilityofnodes,simulationandsoon,butn…     

信道公平分配的局部拥塞控制算法

提出基于信道公平分配的局部拥塞控制算法FCA(fair channel allocation),在缓解局部拥塞的同时增强信道分配的公平性。为减少获取邻居节点实时缓存信息的通信开销和提高以单一节点缓存是否溢出为检测模型的准确性,FCA采用以节点实时缓存长度预测为基础的邻居节点缓存总长度和分组平均传输延迟作为检测指标的拥塞检测模型。为避免使用独立拥塞通告消息增加信道负载,FCA采用在ACK控制帧中增加一个节点地址位携带拥塞信息。在去拥塞阶段,FCA采用基于实时缓存长度和队列优先权值的信道分配机制保证公平传输和防止部分节点因缓存增速过快导致溢出分组丢失。实验结果表明,FCA在碰撞次数、分组传递率、吞吐量和公平性等方面相比802.11、CODA和PCCP具有显著优势。     

Congestion control for multimedia applications in the wireless internet

This paper provides a parallel review of two important issues for the next‐generation multimedia networking. Firstly, the emerging multimedia applications require a fresh approach to congestion control in the Internet. Currently, congestion control is performed by TCP; it is optimised for data traffic flows, which are inherently elastic. Audio and video traffic do not find the sudden rate fluctuations imposed by the TCP multiplicative‐decrease control algorithm optimal. The second important issue is the mobility support for multimedia applications. Wireless networks are characterized by a substantial packet loss due to the imperfection of the radio medium. This increased packet loss disturbs the foundation of TCP's loss‐based congestion control. This paper contributes to the ongoing discussion about the Internet congestion control by providing a parallel analysis of these two issues. The paper describes the main challenges, design guidelines, and existing proposals for the Internet congestion control, optimised for the multimedia traffic in the wireless network environment. Copyright © 2004 John Wiley & Sons, Ltd.     

Network traffic prediction method based on wavelet transform and multiple models fusion

Accurate prediction of network traffic is an important premise in network management and congestion control. In order to improve the prediction accuracy of network traffic, a prediction method based on wavelet transform and multiple models fusion is presented. Mallat wavelet transform algorithm is used to decompose and reconstruct the network traffic time series. The approximate and detailed components of the original network traffic can be obtained. The characteristics of approximate components and detail components are analyzed by Hurst exponent. Then, according to the different characteristics of the components, autoregressive integrated moving average model (ARIMA) is chosen as the prediction model for the approximate component. Least squares support vector machine (LSSVM) is used to predict detail component. Meanwhile, an improved particle swarm optimization (PSO) algorithm is proposed to optimize the parameters of the LSSVM model. Gauss‐Markov estimation algorithm is adapted to fuse the predicted values of multiple prediction models. The variance of fusion prediction error is smaller than that of single prediction model, and the prediction accuracy is improved. Two actual datasets of network traffic are studied. Compared with other state‐of‐the‐art models, the case study results indicate that the proposed prediction method has a better prediction effect.     

Low pass filter/over drop avoidance (LPF/ODA): an algorithm to improve the response time of RED gateways

The low pass filter (LPF) algorithm, which is used to calculate the average queue length in the random early detection (RED) algorithm, results in a poor response time when RED recovers from congestion. In this paper, we propose a new algorithm, called low pass filter/over drop avoidance (LPF/ODA), to improve the response time of RED. LPF/ODA is based on reducing the time required by RED to recover from long‐term congestion. Simulation results have been used to show that the proposed LPF/ODA algorithm significantly improves the response time, throughput and delay of RED gateways. Copyright © 2002 John Wiley & Sons, Ltd.     

Infrastructure‐based vehicular congestion detection scheme for V2I

With the increasing number of vehicles, traffic jam becomes one of the major problems of the fast‐growing world. Intelligent transportation system (ITS) communicates perilous warnings and information on forthcoming traffic jams to all vehicles within its coverage region. Real‐time traffic information is the prerequisite for ITS applications development. In this paper, on the basis of the vehicle‐to‐infrastructure (V2I) communication, a novel infrastructure‐based vehicular congestion detection (IVCD) scheme is proposed to support vehicular congestion detection and speed estimation. The proposed IVCD derives the safety time (time headway) between vehicles by using iterative content‐oriented communication (COC) contents. Meanwhile, the roadside sensor (RSS) provides an infrastructure framework to integrate macroscopic traffic properties into the estimation of both the traffic congestion and vehicle safety speed. The main responsibilities of RSS in IVCD are to preserve privacy, aggregate data, store information, broadcast routing table, estimate safety speed, detect traffic jam, and generate session ID (S‐ID) for vehicles. Monte Carlo simulations in four typical Chinese highway settings are presented to show the advantage of the proposed IVCD scheme over the existing Greenshield's and Greenberg's macroscopic congestion detection schemes in terms of the realized congestion detection performance. Real road traces generated by Simulation of Urban Mobility (SUMO) over NS‐3.29 are utilized to demonstrate that the proposed IVCD scheme is capable of effectively controlling congestion in both single and multilane roads in terms of density and speed health with previous schemes in this field.     

Optimizing routing based on congestion control for wireless sensor networks

Along with the increasing demands for the applications running on the wireless sensor network (WSN), energy consumption and congestion become two main problems to be resolved urgently. However, in most scenes, these two problems aren’t considered simultaneously. To address this issue, in this paper a solution that sufficiently maintains energy efficiency and congestion control for energy-harvesting WSNs is presented. We first construct a queuing network model to detect the congestion degree of nodes. Then with the help of the principle of flow rate in hydraulics, an optimizing routing algorithm based on congestion control (CCOR) is proposed. The CCOR algorithm is designed by constructing two functions named link gradient and traffic radius based on node locations and service rate of packets. Finally, the route selection probabilities for each path are allocated according to the link flow rates. The simulation results show that the proposed solution significantly decreases the packet loss rate and maintains high energy efficiency under different traffic load.     

一种基于模糊逻辑的主动队列管理算法

主动队列管理 (ActiveQueueManagement,AQM)技术作为Internet拥塞控制的一种有效方法 ,对于提高In ternet的服务质量具有十分重要的作用 .本文根据TCP拥塞控制算法基于数据包丢失的窗口变化机制 ,设计了一种基于模糊逻辑的主动队列管理算法 .该算法依据路由器中队列长度的变化情况 ,根据一定的模糊自校正原则来调整数据包的丢弃概率 ,从而使路由器中的队列长度稳定在参考值附近 .仿真结果表明该算法不但十分有效 ,而且对不同的网络状况具有很好的适应能力 .     

Application of a new explicit‐rate ABR traffic controller

In broadband integrated communication systems, the classical method of max–min fair‐rate allocation for traffic control does not support the weighted‐rate guarantee. The weighted‐rate guarantee is necessary for available‐bit rate (ABR) service models. This fact motivates that the weighted max–min (WMM) fair‐rate allocation for the ABR traffic is widely studied. However, the combination of close‐loop feedback control with WMM algorithm has not appeared in the previous research. In this paper, a practical WMM fair‐rate allocation model is proposed. This scheduling scheme combines and integrates the congestion avoidance using proportional control (CAPC) and the weighted max–min fair‐rate allocation. This model is designed to achieve higher utilization and also bounded delay for ABR traffic flow control. In the system under analysis, the performance of this new weighted traffic scheduler is evaluated. The system presented in this paper is also compared with WMM and CAPC methods. Copyright © 2001 John Wiley & Sons, Ltd.     

基于卡尔曼滤波和小波的网络流量预测算法研究

流量预测是流量工程,拥塞控制和网络管理的核心问题。该文针对网络流量的特点,将卡尔曼滤波和小波分析混合的预测算法引入到网络流量预测领域中,对其进行了理论证明。仿真结果表明,该算法与传统的算法相比,具有较高的预测精度和较好的实时性与广谱性。     

Protecting TCP from a misbehaving receiver

This study presents the design and implementation of a robust TCP congestion control algorithm. TCP was originally designed for cooperative environments, and its evolution over the years has been built on the same basis. TCP expects the end hosts to cooperate with the TCP senders in implementing end‐to‐end congestion control. Therefore, misbehavior of a TCP receiver may result in an unfair division of the available bandwidth between the conforming flows and the irresponsible flows. Accordingly, this study examines the issues arising when conforming TCP connections are obliged to coexist with misbehaving connections. A modification to the TCP protocol is proposed to deal with various types of TCP misbehavior. Copyright © 2006 John Wiley & Sons, Ltd.     

基于梯度加速算法的LSP流量分配算法

本文在MPLS系统模型中提出了一种基于加速梯度算法的LSP流量分配算法。仿真结果表明,它可以减少由传统路由算法引起的网络拥塞和包丢失率;随着LSP请求数的增加减少了LSP的拒绝数,优化网络资源的利用率,降低了资源占用率,提高了系统的稳定性。