GMPLS网络的流量工程扩展

流量工程技术的目的是优化网络运行性能，实现网络资源的最优化利用。而且随着网络迅速发展，网络流量的激增特别是突发流量的增加都对作为骨干网的光网络的性能提出新的要求。本文首先简要介绍MPLS网络的流量工程机制，然后重点介绍GMPLS路由协议的流量工程扩展，以及两种不同约束路由计算机制，分别是在线进行路径计算的基于约束最短路径优先算法和离线路径计算的基于设计路由算法。     

基于QoS的智能光网络中约束路由算法研究

服务质量QoS作为网络中一项越来越重要的指标,在通信中起着至关重要的作用.通过对智能光网络中基于约束的最短路径优先算法(CSPF算法)的研究,提出了一种基于QoS的CSPF算法.算法在路由计算之后,对路径的QoS系数进行比对,选择能满足更高QoS要求的路径作为工作路径,提高网络安全与利用率.     

GMPLS网络的路由算法研究与仿真

讨论了基于GMPLS的约束路由机制和约束路由算法,提出了一种适用于智能光网络的CSPF算法.该算法通过考虑SRLG约束和负载平衡因子,能够支持业务的保护与恢复,并在一定程度上均衡业务流量,提高全网资源利用率,从而降低业务阻塞率,通过多次仿真实验验证,该算法是可用的和有效的.     

MPLS流量工程中的约束路由技术

传统的IP路由协议采用最短路径算法(SPF),极易造成网络的拥塞.流量工程是目前网络中实现负载均衡和提高网络性能的一个重要技术.文中简要介绍了MPLS流量工程,重点分析了MPLS流量工程中所使用的路由协议约束路由,给出了约束的计算方法以及路由度量选择的准则.     

MPLS流量工程及基于约束路由计算的研究

论述了 MPLS 网络的架构及其对流量工程的支持,研究了基于 MPLS 流量工程要解决的几个主要问题：如何把数据包映射为转发等价类等,并对其中最重要的一个——通过 LSP 把流量中继映射到实际网络拓扑,提出了一种约束最短路径优先算法的实现方法。     

光网络中分离路由算法的研究

光网络比传统的包含节点、链路的图论网络更为复杂,使用分离路径能够有效地改善光网络的可靠性.文章提出了一种基于改进蚁群算法的分离路由算法,通过与最短路径优先算法进行仿真比较可知,该算法在多条分离路径的搜索上具有较明显的优势.     

ASON路由协议OSPF—TE的分析与仿真

自动交换光网络（ASON）通过在传统光传送网络中引入路由协议、信令协议来实现网络的智能化。文章对ASON路由协议——基于流量工程开放最短路径优先协议（OSPF—TE）的基本概念和工作机制进行了分析研究，并仿真了OSPF-TE的一些网络性能，并得到一些有益的仿真结果。     

GMPLS网络中基于约束的最短路径优先算法

对多种基于约束的最短路径优先算法设计思想进行了分析对比,选择了一种适用于GMPLS网络的路由算法,而且阐述了满足我们需求的设计方案。     

神经网络最短路径路由算法

最短路径路由算法一直是分组交换网络的研究热点。飞速发展的计算机网络对路由算法的反应速度提出了更高的要求。神经网络作为一种新的组合优化计算工具,以其固有的并行执行方式以及潜在的硬件实施能力,使其在网络路由方面的应用得到较大关注。对神经网络最短路径路由算法的模型、发展做了较为细致的阐述,并指出了存在的不足和将来的研究方向。     

基于双层递归神经网络的路由优化算法

研究分组交换网的路由选择及流量分配问题,以网络的平均时延为优化目标函数。为使问题的解能实时、可靠地完成,将一种用于最短路径计算的双层递归神经网络应用于路由选择的流量导数法中。仿真结果表明,该算法在收敛的可靠性和计算的实时性方面有所提高。     

Comparison of Routing Procedures for Circuit-Switched Traffic in Nonhierarchical Networks

In this paper, we compare the use of different types of routing procedures for circuit-switched traffic in nonhierarchical networks. The main performance criterion used is the end-to-end blocking probability. The results show that if the network traffic is light, alternate routing performs better than nonalternate routing, but if the network traffic is heavy, the situation is reversed. To improve the performance of networks using alternate routing, different types of strategies varying from fixed control to dynamic control are introduced. A comparison based on numerical examples shows the improvement in performance attained by using a dynamic control strategy compared to fixed control. Good control techniques result in nonalternate routing under heavy traffic loads; nonalternate routing is the most viable alternative in nonhierarchical networks under heavy traffic conditions.     

任意拓扑结构战术地域分组交换网的性能分析

本文以战术地域分组交换网为基础建立具有不规则拓扑结构网络模型，在给出网络的拓扑结构、网络用户业务量和路由选择算法的条件下，提出了一种计算网络链路传输业务量的方法，并用于分析网络的传输性能。同时，还用计算机仿真方法对同一网络进行模拟。分析结果说明：这类通信网的路由选择算法的设计应更重视网络内部流量的均匀分配     

Oblivious routing in wireless mesh networks

As new network applications have arisen rapidly in recent years, it is becoming more difficult to predict the exact traffic pattern of a network. In consequence, a routing scheme based on a single traffic demand matrix often leads to a poor performance. Oblivious routing (Racke in Proceedings of the 43rd annual IEEE symposium on foundations of computer science 43–52, 2002) is a technique for tackling the traffic demand uncertainty problem. A routing scheme derived from this principle intends to achieve a predicable performance for a set of traffic matrixes. Oblivious routing can certainly be an effective tool to handle traffic demand uncertainty in a wireless mesh network (WMN). However, a WMN has an additional tool that a wireline network does not have: dynamic bandwidth allocation. A router in a WMN can dynamically assign bandwidth to its attached links. This capability has never been exploited previously in works on oblivious routing for a spatial time division multiple access (STDMA) based WMN. Another useful insight is that although it is impossible to know the exact traffic matrix, it is relatively easy to estimate the amount of the traffic routed through a link when the routing scheme is given. Based on these two insights, we propose a new oblivious routing framework for STDMA WMNs. Both analytical models and simulation results are presented in this paper to prove that the performance—in terms of throughput, queue lengths, and fairness—of the proposed scheme can achieve significant gains over conventional oblivious routing schemes for STDMA based WMNs.     

一种基于深度增强学习的智能路由技术

随着网络规模的不断增大以及网络复杂度的不断提高,传统路由算法面对网络流量在时空分布上的剧烈波动难以兼顾计算复杂度和算法效率.近年来,随着软件定义网络和人工智能技术的兴起,基于机器学习的自动路由策略生成逐渐受到关注.本文提出一种基于深度增强学习的智能路由技术SmartPath,通过动态收集网络状态,使用深度增强学习自动生成路由策略,从而保证路由策略能够动态适应网络流量变化.实验结果表明,本文所提出的方案能够不依赖人工流量建模动态更新网络路由,在测试环境下比当前最优方案减少至少10%的平均端到端传输时延.     

Making Routing Robust to Changing Traffic Demands: Algorithms and Evaluation

Intra-domain traffic engineering can significantly enhance the performance of large IP backbone networks. Two important components of traffic engineering are understanding the traffic demands and configuring the routing protocols. These two components are inter-linked, as it is widely believed that an accurate view of traffic is important for optimizing the configuration of routing protocols, and through that, the utilization of the network. This basic premise, however, seems never to have been quantified. How important is accurate knowledge of traffic demands for obtaining good utilization of the network? Since traffic demand values are dynamic and illusive, is it possible to obtain a routing that is "robust" to variations in demands? We develop novel algorithms for constructing optimal robust routings and for evaluating the performance of any given routing on loosely constrained rich sets of traffic demands. Armed with these algorithms we explore these questions on a diverse collection of ISP networks. We arrive at a surprising conclusion: it is possible to obtain a robust routing that guarantees a nearly optimal utilization with a fairly limited knowledge of the applicable traffic demands     

Optimal Routing for Wireless Mesh Networks With Dynamic Traffic Demand

Wireless mesh networks have attracted increasing attention and deployment as a high-performance and low-cost solution to last-mile broadband Internet access. Traffic routing plays a critical role in determining the performance of a wireless mesh network. To investigate the best routing solution, existing work proposes to formulate the mesh network routing problem as an optimization problem. In this problem formulation, traffic demand is usually implicitly assumed as static and known a priori. Contradictorily, recent studies of wireless network traces show that the traffic demand, even being aggregated at access points, is highly dynamic and hard to estimate. Thus, in order to apply the optimization-based routing solution into practice, one must take into account the dynamic and unpredictable nature of wireless traffic demand. This paper presents an integrated framework for wireless mesh network routing under dynamic traffic demand. This framework consists of two important components: traffic estimation and routing optimization. By studying the traces collected at wireless access points, we first present a traffic estimation method which predicts future traffic demand based on its historical data using time-series analysis. This method provides not only the mean value of the future traffic demand estimation but also its statistical distribution. We further investigate the optimal routing strategies for wireless mesh network which take these two forms of traffic demand estimations as inputs. The goal is to balance the traffic load so that minimum congestion will be incurred. This routing objective could be transformed into the throughput optimization problem where the throughput of aggregated flows is maximized subject to fairness constraints that are weighted by the traffic demands. Based on linear programming, we present two routing algorithms which consider the mean value and the statistical distribution of the predicted traffic demands, respectively. The trace-driven simulation study demonstrates that our integrated traffic estimation and routing optimization framework can effectively incorporate the traffic dynamics in mesh network routing.     

Evaluating the impact of stale link state on quality-of-servicerouting

Quality-of-service (QoS) routing satisfies application performance requirements and optimizes network resource usage by selecting paths based on connection traffic parameters and link load information. However, distributing link state imposes significant bandwidth and processing overhead on the network. This paper investigates the performance tradeoff between protocol overhead and the quality of the routing decisions in the context of the source-directed link state routing protocols proposed for IP and ATM networks. We construct a detailed model of QoS routing that parameterizes the path-selection algorithm, link-cost function, and link state update policy. Through extensive simulation experiments with several network topologies and traffic patterns, we uncover the effects of stale link state information and random fluctuations in traffic load on the routing and setup overheads. We then investigate how inaccuracy of link state information interacts with the size and connectivity of the underlying topology. Finally, we show that tuning the coarseness of the link-cost metric to the inaccuracy of underlying link state information reduces the computational complexity of the path-selection algorithm without significantly degrading performance. This work confirms and extends earlier studies, and offers new insights for designing efficient quality-of-service routing policies in large networks     

野战分组交换网的性能分析

本文提出了一种评价野战分组交换性能的分析方法，其基本原理是根据网络的拓扑结构和每个节点产生的业务量计算出每个节点的总业务量以及每条链路上的业务流量，然后依据排队理论计算野战分组交换网的性能，本文对一种规划的栅格状网络进行了理论分析，并分别针对两种路由准则，采用递归方法推导出了评价网络性能的计算公式。     

Dynamic Routing in WDM Grooming Networks

Traffic grooming in optical networks has gained significant importance in recent years due to the prevailing sub-wavelength traffic requirement of end-users. In this paper, a methodology for dynamic routing of fractional-wavelength traffic in WDM grooming networks is developed. To evaluate the performance of routing algorithms, a new performance metric that reflects the network utilization is also proposed. The performances of shortest-widest path, widest-shortest path, and available shortest path routing algorithms are evaluated on a class of WDM grooming networks by considering traffic of different capacity requirements. The effect of dispersity routing, where higher capacity requests are broken into multiple unit capacity requests, is also investigated. The most interesting counter-intuitive result that is observed is that increasing the grooming capability in a network could result in degrading the performance of the widest-shortest path algorithm.