在Ad Hoc网络中基于信息调度的QoS保证

提出一个以信息调度为基础的分布式的QoS(DQBI)体系结构。该结构可以在移动Ad Hoc网络中为实时传输和尽力而为传输提供QoS保证。DQBI模型改进了整个系统信息端到端的延迟性能,并且通过使用请求允许接入控制和拥塞控制机制来处理网络的拥塞。最后,仿真比较了MQRD结构和DQBI结构,发现DQBI结构可以更好地确保实时流和尽力而为流实现它们期望的服务水平。     

A policy based framework for quality of service management in software defined networks

Growth in multimedia traffic over the Internet increases congestion in the network architecture. Software-Defined Networking (SDN) is a novel paradigm that solves the congestion problem and allows the network to be dynamic, intelligent, and it centrally controls the network devices. SDN has many advantages in comparison to traditional networks, such as separation of forwarding and control plane from devices, global centralized control, management of network traffic. We design a policy-based framework to enhance the Quality of Service (QoS) of multimedia traffic flows in a potential SDN environment. We phrase a max-flow-min-cost routing problem to determine the routing paths and presented a heuristic method to route the traffic flows in the network in polynomial time. The framework monitors the QoS parameters of traffic flows and identifies policy violations due to link congestion in the network. The introduced approach dynamically implements policy rules to SDN switches upon detection of policy violations and reroutes the traffic flows. The results illustrate that the framework achieves a reduction in end-to-end delay, average jitter, and QoS violated flows by 24%, 37%, and 25%, respectively, as compared to the Delay Minimization method. Furthermore, the proposed approach has achieved better results when compared to SDN without policy-based framework and reduced end-to-end delay, average jitter, and QoS violated flows by 51%, 62%, and 28%, respectively.

     

一种基于QoS的空间延迟/中断容忍网络拥塞控制方法

为缓解网络拥塞对空间延迟/中断容忍网络产生的影响,该文提出一种基于QoS的网络拥塞控制算法。该算法包括接触拥塞判断和基于QoS的数据转发两种机制,分别从接触剩余可用容量和节点剩余存储空间两方面对每一段接触的拥塞程度进行预测,将接触划分为不同的拥塞等级。在计算路由时,以整段路径中所包含接触的最高拥塞等级为该路径的拥塞等级,并根据该拥塞等级发送不同优先级的数据。实验表明,基于QoS的拥塞控制算法可以提高低优先级数据的传递率并在节点存储空间不足时降低最高优先级数据的传递时延。     

Analysis of Distributed DDQ for QoS Router

In a packet switching network, congestion is unavoidable and affects the quality of real‐time traffic with such problems as delay and packet loss. Packet fair queuing (PFQ) algorithms are well‐known solutions for quality‐of‐service (QoS) guarantee by packet scheduling. Our approach is different from previous algorithms in that it uses hardware time achieved by sampling a counter triggered by a periodic clock signal. This clock signal can be provided to all the modules of a routing system to get synchronization. In this architecture, a variant of the PFQ algorithm, called digitized delay queuing (DDQ), can be distributed on many line interface modules. We derive the delay bounds in a single processor system and in a distributed architecture. The definition of traffic contribution improves the simplicity of the mathematical models. The effect of different time between modules in a distributed architecture is the key idea for understanding the delay behavior of a routing system. The number of bins required for the DDQ algorithm is also derived to make the system configuration clear. The analytical models developed in this paper form the basis of improvement and application to a combined input and output queuing (CIOQ) router architecture for a higher speed QoS network.     

Cooperative congestion control schemes in ATM networks

One of the basic problems faced in the design of efficient traffic and congestion control schemes is related to the wide variety of services with different traffic characteristics and quality of service (QoS) requirements supported by ATM networks. The authors propose a new way of organizing the control system so that complexity is easier to manage. The multi-agent system approach, which provides the use of adaptative and intelligent agents, is investigated. The authors show, through the two congestion control schemes proposed, how to take advantage of using intelligent agents to increase the efficiency of the control scheme. First, TRAC (threshold based algorithm for control) is proposed, which is based on the use of fixed thresholds which enables the anticipation of congestion. This mechanism is compared with the push-out algorithm and it is shown that the authors' proposal improves the network performance. Also discussed is the necessity of taking into account the network dynamics. In TRAC, adaptative agents with learning capabilities are used to tune the values of the thresholds according to the status of the system. However, in this scheme, when congestion occurs, the actions we perform are independent of the nature of the traffic. Subsequently, we propose PATRAC (predictive agents in a threshold based algorithm for control) in which different actions are achieved according to the QoS requirements and to the prediction of traffic made by the agents. Specifically, re-routing is performed when congestion is heavy or is expected to be heavy and the traffic is cell loss sensitive. This re-routing has to deflect the traffic away from the congestion point. In this scheme, we propose a cooperative and predictive control scheme provided by a multi-agent system that is built in to each node     

基于流媒体的实时网络传输系统中若干问题研究

流媒体在Internet上的实时传输常因其要求高带宽、低延迟而造成网络拥塞。探讨了基于Internet的实时流媒体中视频流的QoS控制策略,并主要论述了基于速率的网络拥塞控制方法并给出一种视频流编码速率调整算法。这些控制技术应用于终端系统并不需要路由器和网络QoS支持,可以较好地提高视频质量。     

Adaptive predictive congestion control of high-speed ATM networks

This paper proposes an auto regressive moving average (ARMAX)-based adaptive control methodology to prevent congestion in high-speed asynchronous transfer mode (ATM) networks. An adaptive controller is developed to control traffic where sources adjust their transmission rates in response to the feedback information from the network switches. Specifically, the buffer dynamics at a given switch is modeled as a nonlinear discrete-time system and an ARMAX controller is designed so as to predict the explicit values of the transmission rates of the sources so as to prevent congestion. Tuning methods are provided for the unknown coefficients of the ARMAX model to estimate the unpredictable and statistically fluctuating network traffic. Mathematical analysis is given to demonstrate the stability of the closed-loop system so that a desired quality of service (QoS) can be guaranteed. The QoS is defined in terms of cell loss ratio (CLR), transmission delay and buffer utilization. We derive design rules mathematically for selecting the parameters of the ARMAX algorithm such that the desired performance is guaranteed during congestion and potential tradeoffs are shown. Simulation results are provided to justify the theoretical conclusions for multiple source/single switch scenarios using both ON/OFF and MPEG data. The performance of the proposed congestion control scheme is also evaluated in the presence of feedback delays for robustness considerations.     

基于功率分配的无线传感器网络拥塞控制协议

由于无线传感器网络的资源受限,相比传统网络其传输过程更容易导致丢包和拥塞。为了避免和控制拥塞,本文提出了一种利用功率分配重新选择路径的拥塞控制算法,首先参考路径传输的多种QoS相关参数度量网络的路径代价和节点可用资源的信息,基于测量得到的网络拥塞水平通过传输功率递增和递减选择不同的路径控制网络拥塞。仿真结果表明所提出的协议减少了网络时延,提高了系统吞吐量和网络生命周期。      

H-CRAN网络下联合拥塞控制和资源分配的网络切片动态资源调度策略

针对异构云无线接入网络(H-CRAN)网络下基于网络切片的在线无线资源动态优化问题,该文通过综合考虑业务接入控制、拥塞控制、资源分配和复用,建立一个以最大化网络平均和吞吐量为目标,受限于基站(BS)发射功率、系统稳定性、不同切片的服务质量(QoS)需求和资源分配等约束的随机优化模型,并进而提出了一种联合拥塞控制和资源分配的网络切片动态资源调度算法。该算法会在每个资源调度时隙内动态地为性能需求各异的网络切片中的用户分配资源。仿真结果表明,该文算法能在满足各切片用户QoS需求和维持网络稳定的基础上,提升网络整体吞吐量,并且还可通过调整控制参量的取值实现时延和吞吐量间的动态平衡。     

改善Internet视频流QoS的途径和方法

在当前Internet的尽力而为的服务模式下，网络拥塞和分组丢失不可避免，视频流必须使用有效的拥塞控制和差错控制来改善性能。本文分析了：Internet视频流QoS影响因素，提出了两种QoS解决方案：基于终端和基于网络。本文着重讨论了基于终端的QoS解决方案，在目前Internet的环境下，基于终端的QoS解决方案更具可行性。