Distributed resolution of network congestion and potential deadlock using reservation-based scheduling

Efficient and reliable communication is essential for achieving high performance in a networked computing environment. Finite network resources bring about unavoidable competition among in-flight network packets, resulting in network congestion and, possibly, deadlock. Many techniques have been proposed to improve network performance by efficiently handling network congestion and potential deadlock. However, none of them provide an efficient way of accelerating the movement of network packets in congestion toward their destinations. In this paper, we propose a new mechanism for detecting and resolving network congestion and potential deadlocks. The proposed mechanism is based on efficiently tracking paths of congestion and increasing the scheduling priority of packets along those paths. This acts to throttle other packets trying to enter those congested regions - in effect, locking out packets from congested regions until congestion has had the opportunity to disperse. Simulation results show that the proposed technique effectively disperses network congestion and is also applicable in helping to resolve potential deadlock.     

A family of mechanisms for congestion control in wormhole networks

Multiprocessor interconnection networks may reach congestion with high traffic loads, which prevents reaching the wished performance. Unfortunately, many of the mechanisms proposed in the literature for congestion control either suffer from a lack of robustness, being unable to work properly with different traffic patterns or message lengths, or detect congestion relying on global information that wastes some network bandwidth. This paper presents a family of mechanisms to avoid network congestion in wormhole networks. All of them need only local information, applying message throttling when it is required. The proposed mechanisms use different strategies to detect network congestion and also apply different corrective actions. The mechanisms are evaluated and compared for several network loads and topologies, noticeably improving network performance with high loads but without penalizing network behavior for low and medium traffic rates, where no congestion control is required.     

基于SDN架构的高性能网络拥塞避免策略

拥塞管理是高性能网络领域的重要研究方向,网络拥塞会对网络的全局性能产生较大影响。现有的拥塞管理多采用分布式拥塞避免策略,能够在一定程度上解决网络的拥塞问题,但其处理过程基于局部信息,不能充分利用网络资源,处理效率偏低。近期,人们提出软件定义网络(SDN)架构,该架构采用集中控制器和多层网络技术,能够较好地获取网络的全局信息。在原有工作的基础上提出了一种基于SDN架构的全局拥塞避免策略OSCP,该策略在拥塞信息获取和控制信息的传输上,改进了原有的解决方案,并结合自适应传输进行网络路由。实验结果表明,该策略可以较好地避免和解决网络中存在的拥塞问题,降低网络延迟并提高饱和吞吐率。     

基于源区域路径选择的层次化片上网络路由算法

针对较大规模片上网络(NoC)远端节点和邻近节点之间的通信问题,提出一种基于区域划分的层次化簇状分层网（CHM）结构。在此基础上,针对中间节点拥塞严重导致网络性能降低的问题,提出一种基于源区域路径选择的自适应算法。该算法利用CHM结构区域特性将路由决策由源节点移至源区域,同时在原有底层和上层节点对的基础上增加自适应节点对,并增加该部分节点对路由选择性,从而缓解网络拥塞状况。仿真实验表明,与最短路径算法相比,在合成流量和局部化流量模式下,该算法下的CHM结构饱和注入率最多可分别提升约51%和31%,因此该算法可有效提升网络整体吞吐性能。     

EasiCC:一种保证带宽公平性的传感器网络拥塞控制机制

实用的传感器网络拥塞控制方案不仅需要满足多项网络性能指标,而且必须控制开销很小,提出了一种满足上述要求的拥塞控制机制EasiCC(EasiNet congestion control mechanism).在EasiCC中,数据流源节点将数据报文按比例划分到各优先等级中,各网络节点根据网络拥塞程度动态地、同步地调整报文过滤标准,结合报文过滤标准和报文优先级来调节网络流量,保证了无线信道带宽分配上的公平性;将网络准入控制和队列丢包手段相结合来调整网络流量,保证了网络综合性能指标.EasiCC控制开销很少,已在实际传感器网络平台中实现.模拟验证和实验测试结果显示,EasiCC能够公平地为各数据流分配发报速度和网络带宽,并且在报文传输成功率、传输延迟等性能指标上均有良好的表现.     

基于MAC层信息的OLSR改进方案

针对移动Ad Hoc网络通信节点共享通信介质且易受网络负荷影响的特点，提出了一种基于MAC层信息的OLSR协议改进方案。该方案通过对HELLO消息、TC消息的修改来获取并传输MAC层的拥塞信息，对路径选择算法进行改进以评估节点的网络负荷，选择出一条网络负荷和冲突较轻的路由，从而减少数据在MAC层和物理层的丢包。方案改进了TC消息源头节点的发送方式，采用源节点二次发送机制以降低对路由性能有重要影响的信令信息丢失的概率，稳定路由协议的性能，减少数据在网络层的丢包。仿真实验表明改进后的方案在网络负荷较重时，在不同的移动速率下均能提高数据传输的成功率，增强网络承受负荷的能力，提高其路由传输的性能。     

基于Additive2multipl icative 模糊 神经网的ATM 网络拥塞控制

考虑了模糊神经网络的学习功能，提出利用Additive-multiplicative模糊神经网络(AMFNN)对ATM网络进行拥塞控制的方案．在拥塞控制过程中，利用AMFNN模糊神经网络预测下一个将要到达流的特征，结合当前缓冲区的队列信息预测网络是否发生拥塞．一旦预测出将有拥塞发生，控制器则向源端反馈拥塞控制信息，信源根据拥塞信息适当降低传输速率，从而避免了拥塞的发生．仿真结果表明，该方法可改善网络对拥塞的实时处理能力，提高网络资源的利用率．     

综合式拥塞控制机制的研究

针对无线传感器网络中的SFB拥塞控制算法在网络流量大时,其分类机制受影响而导致TCP流传输性能下降的问题,介绍了一种综合式拥塞控制机制的算法实现,并在NS-2平台上对该机制的性能进行了仿真研究。综合式拥塞控制机制通过建立新路径对数据包分流来解决拥塞问题;当新路径建立失败时,采用公平汇聚算法,按比例减少源节点的发送率,保证每个源节点公平发送数据;对于轻度拥塞情况,采用一种节能算法,即设置拥塞时间阈值,只有当拥塞时间超过阀值时才启动新路径查找机制。仿真结果表明,综合式拥塞控制机制能够减少丢包率,有效缓解拥塞,并能够根据数据权重的不同可靠发送重要数据。     

Adaptive load balancing in learning-based approaches for many-core embedded systems

Adaptive routing algorithms improve network performance by distributing traffic over the whole network. However, they require congestion information to facilitate load balancing. To provide local and global congestion information, we propose a learning method based on dual reinforcement learning approach. This information can be dynamically updated according to the changing traffic condition in the network by propagating data and learning packets. We utilize a congestion detection method which updates the learning rate according to the congestion level. This method calculates the average number of free buffer slots in each switch at specific time intervals and compares it with maximum and minimum values. Based on the comparison result, the learning rate sets to a value between 0 and 1. If a switch gets congested, the learning rate is set to a high value, meaning that the global information is more important than local. In contrast, local is more emphasized than global information in non-congested switches. Results show that the proposed approach achieves a significant performance improvement over the traditional Q-routing, DRQ-routing, DBAR and Dynamic XY algorithms.     

Ad hoc网络中动态阈值岭型函数退避算法*

无线自组织网络(Ad hoc)在MAC层中使用IEEE 802.11 DCF的接入机制来解决节点传输竞争问题,为了解决高负载环境下的网络拥塞状况问题,在退避算法中加入了动态阈值和岭型函数来降低数据传输的冲突概率并利用NS2对改进的退避算法进行网络仿真。仿真结果表明,相对于传统的退避算法,在负载较重的网络中改进后的退避算法大概能够提高网络性能20%左右,优化后网络的时延、吞吐量和公平性均得到明显改善。     

一种新的基于BP神经网络的拥塞控制算法

针对计算机高速互联网中发送端速率调节的问题，在一般网络模型基础上，将BP（Back Propagation神经网络运用到计算机网络的拥塞控制中，提出了一种基于BP神经网络的动态资源管理机制以解决网络的拥塞问题，对所提出的拥塞控制方案，进行了仿真分析，仿真结果显示，控制方案有较好的可扩展性，有效性，并使网络性能表现良好。     

Internet的测量与性能分析

网络测量技术对于网络性能评价和网络业务的预报和控制来说是至关重要的。该文使用多种测量工具，如即Fping、TTCP、Netperf和Pathrate等，以加拿大渥太华大学为中心对包括天津大学等在内的多个国内外站点的网络延迟、丢包率和吞吐率进行了测量。在分析测量结果评价Internet性能的同时，还对比了多种测量工具。     

Globally Adaptive Load-Balanced Routing on Tori

We introduce a new method of adaptive routing on k-ary n-cubes, Globally Adaptive Load-Balance (GAL). GAL makes global routing decisions using global information. In contrast, most previous adaptive routing algorithms make local routing decisions using local information (typically channel queue depth). GAL senses global congestion using segmented injection queues to decide the directions to route in each dimension. It further load balances the network by routing in the selected directions adaptively. Using global information, GAL achieves the performance (latency and throughput) of minimal adaptive routing on benign traffic patterns and performs as well as the best obliviously load-balanced routing algorithm (GOAL) on adversarial traffic.     

一种基于EPN的拥塞价格机制

网络发生拥塞的根本原因在于用户需求大于资源供给。利用价格机制中价格随供求关系而波动，又反过来影响用户需求的原理，可以均衡负载，抑制拥塞。针对网络中价格波动及价格传递的问题，本文提出了一种基于EPN（Explicit Price Notification）的拥塞价格机制，该机制通过路由器的平均队列长度与队列阅值的关系来反映用户需求的变化，并将价格调整的信息快速传递给用户，激励用户做出正确的资源决策，使网络维持在高吞吐量，低拥塞的状态。同时通过仿真试验分析了队列阈值参数对网络性能的影响。     

不同信息共享程度下交通拥塞控制研究

信息共享程度是影响交通通行效率的重要条件。分析了信息闭塞、局部信息共享和全局信息共享三种信息共享模式下的交通拥塞现象及其传播特征,并对网络节点行为进行动力学分析,采用概率母函数、分支过程和协调博弈的方法建立了交通拥塞传播模型,解析分析了交通拥塞传播的临界值,比较了不同信息共享模式下的交通拥塞控制策略。仿真实验表明,信息闭塞和局部信息共享下的拥塞控制在交通网络流量较小时更为有效,全局信息共享有利于抑制大规模的拥塞传播,但其可控难度较大。     

3GPP中基于拥塞控制的协作DSR路由协议研究

针对现行的3GPP网络路由协议在路由选择时存在的可靠性低、路由开销大等问题,分析了网络中通信节点的工作状态,综合考虑协同合作方式的DSR路由机制和拥塞控制策略对3GPP网络性能的影响,提出了一种基于拥塞控制的增强型协作DSR路由协议,并通过3GPP网络系统级仿真验证改进后的协作路由协议的通信性能。仿真结果表明,所提的协作DSR协议显著提高了3GPP网络通信性能,在提高网络资源利用率的同时改善了数据传输的可靠性。     

Performance bounds for rate envelope multiplexing

In QoS guaranteed communication networks, such as ATM, several classes of traffic streams with widely varying characteristics share common transmission resources. To achieve high utilization of these networks, while providing appropriate grade of service for all connections, the development of powerful traffic management algorithms is a central issue. Due to scalability reasons traffic control functions like flow, congestion and admission control often need simple and efficient characterization of traffic using mainly aggregate characteristics instead of using information about all the individual flows. In this paper, the saturation probability as a possible performance measure of aggregate traffic on a communication link is discussed. This performance metric, also referred to as the tail distribution of aggregate traffic, is essential in traffic control and management algorithms of high-speed networks including also the prospective QoS Internet. In this paper, using the Chernoff bounding method, efficient closed-form bounds have been derived for the saturation probability for the case when little information is available on the aggregate traffic. The performance of these estimates is also shown by means of numerical examples.     

Actuator saturation and anti-windup compensation in event-triggered control

Event-triggered control aims at reducing the communication load over the feedback link in networked control systems by sending information only if certain event conditions, which guarantee a desired control performance, are satisfied. This article investigates the consequences of actuator saturation on the behavior of the event-triggered control loop in terms of its stability and information exchange. Stability properties are derived using linear matrix inequalities (LMIs) which show how the stability of the event-triggered control loop depends on the selection of the event threshold. Moreover, it is shown that a lower bound on the minimum inter-event time exists being likewise affected by the event threshold. As actuator saturation might severely degrade the performance of the event-triggered closed-loop system, the scheme is extended by incorporating an anti-windup mechanism in order to overcome this problem. The results are illustrated by simulations and experiments.     

网络拥塞控制模型Hopf分岔的PD控制

网络拥塞会导致信息丢失,时延增加,甚至系统崩溃。由于无线接入网络中的时变衰落和分组错误率,使得TCP协议在网络拥塞控制更加复杂。TCP Westwood是专门为高速无线网络设计的,大大提高了网络带宽的利用率,改善了网络性能。TCP Westwood/AQM拥塞控制的连续流体流模型被引用,源端采用TCP Westwood拥塞控制协议,路由器端采用主动队列管理(AQM)机制中的随机早期检测(RED)算法。为了延迟无线接入网络拥塞控制模型中霍普夫(Hopf)分岔现象的发生,采用比例微分(PD)控制器,通过选择通信延迟作为分岔参数,分析无线网络系统中的Hopf分岔行为,并由理论分析得知当分岔参数超过临界值时系统发生Hopf分岔。利用中心流形和规范型理论,推导得出系统发生Hopf分岔的条件和反映Hopf分岔性质,方向和周期的参数,数值仿真验证理论分析的准确性,表明PD控制器的有效性。     

A new congestion control algorithm for improving the performance of a broadcast-based multiprocessor architecture

Congestion occurring in the input queues of broadcast-based multiprocessor architectures can severely limit their overall performance. The existing congestion control algorithms estimate congestion based on a node’s output channel parameters such as the number of free virtual channels or the number of packets waiting at the channel queue. In this paper, we have proposed a new congestion control algorithm to prevent congestion on broadcast-based multiprocessor architectures with multiple input queues. Our algorithm performs congestion control at the packet level and takes into account the next input queue number which will be accessed by the processor, which form the fundamental differences between our algorithm and the algorithms based on the idea of virtual channel congestion control. The performance of the algorithm is evaluated by OPNET Modeler with various synthetic traffic patterns on a 64-node Simultaneous Optical Multiprocessor Exchange Bus (SOME-Bus) architecture employing the message passing protocol. Performance measures such as average input waiting time, average network response time and average processor utilization have been collected before and after applying the algorithm. The results show that the proposed algorithm is able to decrease the average input waiting time by 13.99% to 20.39%, average network response time by 8.76% to 20.36% and increase average processor utilization by 1.92% to 6.63%. The performance of the algorithm is compared with that of the other congestion control algorithms and it is observed that our algorithm performs better under all traffic patterns. Also, theoretical analysis of the proposed method is carried out by using queuing networks.