基于链路共享的多源选播路由算法

选播（manycast）作为一种新型的通信模式,吸引了研究人员越来越大的兴趣。MSPT（Manycast Shortest Path Tree）算法是一种应用广泛的选播路由算法。但是,它没有考虑整体网络资源的利用;DDMC（Destination-Driven for Manycast）算法较好地解决了单源点选播最小生成树问题,但应用场景只是针对“一个对多个中的任意个”。针对“多个对多个中的任意个”的多源选播路由问题,在DDMC算法的基础上作了一些改进。仿真实验结果表明,改进的选播路由算法MBLS（Manycast Based-Link-Share）基于链路共享机制,在空间复杂度和时间复杂度相同的情况下,在选播森林每源点成本上优于MSPT算法。     

基于最优Path的Ad Hoc网络地理路由算法

对基于地理信息的自组网路由中的凹节点问题做了分析,并提出了一种新的解决方案——PGA算法及其改进算法.算法采用了最优Path的思想,在Path构造、基于Path的最优寻路、路由恢复等多个方面都应用了最优Path的概念,较好地解决了凹节点的问题.通过证明,该算法具有无环性,从而实现了基于局部路由信息的无状态路由,展示了算法的可扩展性和易维护性.实验表明,即使在大型网络中,算法依然可以保持很高的报文投递率、较短的路径长度、可接受的路由表大小及可控的协议带宽开销,同时该路由算法在动态环境中具有较强的鲁棒性.     

MIRA N：一种改进的最小干扰路由算法*

研究动态路由算法,提出了一种改进的最小干扰路由算法（MIRAN）。该算法引入关键链路、次关键链路的定义,将算法分为预处理和在线路由两个过程,降低了算法复杂度影响。仿真结果表明该算法可使网络负载分布更为均衡、提高网络吞吐量,进一步改善最小干扰路由算法的性能。     

MIRA-N:一种改进的最小干扰路由算法

研究动态路由算法,提出了一种改进的最小干扰路由算法（MIRA-N）。该算法引入关键链路、次关键链路的定义,将算法分为预处理和在线路由两个过程,降低了算法复杂度影响。仿真结果表明该算法可使网络负载分布更为均衡、提高网络吞吐量,进一步改善最小干扰路由算法的性能。     

一种快速低代价延迟受限组播路由算法

为满足实时业务的QoS要求,在非延迟受限组播路由算法(Fast Low-cost Shortest Path Tree,FLSPT）的基础上添加了延迟约束,使得生成的组播树上,每条从源到目的地的路径都满足给定的延迟限制,同时保持了原算法计算复杂度低,代价性能优越的特点。仿真结果表明,本文算法的代价和时间性能均优于延迟受限最短路径(Delay-Constrained Shortest Path, DCSP),且更适合用于目的节点分布集中的密集模式下。     

波长连续WDM光网络中新的自适应RWA 算法

在对WDM波长路由光网络的路由和波长分配算法进行研究的基础上，提出了一种新的自适应动态路由算法和考虑路径优先级及网络公平性的波长分配算法，给出了具体分析及实现步骤。该算法能有效地利用网络资源，保证业务分布的均衡，较好地兼顾网络资源分配的合理性，有效地改善了全网的平均阻塞性能。     

农行网络改造的应用方案及网络性能分析

随着农行网络建设及规模的迅速发展，网络结构的复杂性日益增加，需要选用高效率的路由协议，以提高网络的效率和性能。开放式最短路径优先协议（Open Shortest Path First，OSPF）是目前一种使用较为广泛的一种内部路由协议，很多优点使得在农行的网络建设中得到了应用。在分析和比较RIP（Routing Information Protocol）和OSPF协议的基础上，提出了一种针对OSPF协议的网络性能分析系统。     

基于虚拟多任务机制的OSPF-2的设计与实现

OSPF（Open Shortest Path First Protocol）协议是目前Internet上广泛使用的自治系统内部交换路由信息的动态路由协议。文章介绍了在清华大学研制的国产高性能路由器中分布式路由协议OSPF－2的具体实现。为了实现这一复杂的动态协议,文章提出了基于事件驱动的虚拟多任务机制的设计和实现方法。这种机制能够有效支持复杂系统的分解,在实时性要求不高的前提下提供一种简便有效的并行机制,方便基于状态机的软件实现,提高了软件的可移植性。该方法对于其它的Internet高层协议的设计和实现也有一定的参考价值。     

OSPF测试方案设计

OSPF（Open Shortest Path First）协议解决多台三层设备之间的动态路由选路的问题,是单播路由协议中最常用的协议。遵循RFC2328标准,三层的网络设备都普遍具备该功能。尽管根据测试方法划分的测试类型有很多,本文仅仅针对一致性测试、互操作性测试、性能测试来阐述OSPF的测试方案的设计。     

基于多径路由负载均衡的动态源路由协议*

提出了一种DSR的改进多径路由协议（LBDSRM）。采用开销小的综合链路状态路由判据算法,协议具有链路状态实时监控与适时调整路由功能,在链路变化较大的情况下,主动通知有路由冗余的源节点改用或重点使用次选路由;而且协议提出了适时退避算法,解决了多径任务与单径任务争用链路时网络公平性问题。仿真结果表明新协议能有效避免节点拥塞,达到较好的动态负载均衡,实现网络资源的充分利用。     

一种基于动态负载均衡的路由算法

传统IGP仅基于最短路径算法来为数据流选择传输通路，对数据流的需求以及网络资源的动态变化未加以考虑，因此不具备均衡网络负载的能力。文中通过分析IGP的局限性，提出基于动态负载均衡的DLB-OSPF路由算法。该算法依据数据流的带宽需求和网络资源的使用状况来进行路由选择，并通过有效手段将数据流更合理地分配到能满足传输需求的链路上。经过示例分析表明，该算法不仅能减少网络拥塞，并且提高了网络资源利用率。     

服务覆盖网络中一种动态流量工程模型与算法

针对服务覆盖网络中的自私路由造成的网络流量失衡将严重影响网络效率和稳定性的问题, 研究如何在覆 盖层应用动态流量工程的方法进行流量优化分配. 基于随机动态优化配流理论, 提出一种服务覆盖网络的动态流量 工程模型, 并设计了分布式的流量工程算法. 该算法可以折衷控制路由的自私与负载均衡的程度. 模拟实验显示, 所 提出的方法较其他方法具有更好的性能, 尤其对于实时动态流量有着较好的适应性.

     

Management,control, and design of integrated networks with real-time dynamic routing

Integrated real-time dynamic routing (IRR) networks provide dynamic routing features for multiple classes-of-service on an integrated transport network. In this paper it is shown that IRR networks allow reduced network management costs since with real-time dynamic routing a number of network operations are simplified or eliminated. These simplifications include eliminating the storage of voluminous routing tables in the network switches, eliminating the calculation of routing tables in network design, simplifying the routing administration operations which require downloading new routing information to the network, and eliminating the automatic rerouting function in on-line traffic management. A new bandwidth allocation technique is described here which is based on the optimal solution of a network bandwidth allocation model for IRR networks. The model achieves significant improvement in both the average network blocking and node pair blocking distribution when the network is in a congested state such as under peak-day loads. In a paper to appear in the next Journal issue we further describe a new algorithm for the transport design of IRR networks which achieves near-optimal capacity engineering. These optimization techniques attain significant capital cost reductions and network performance improvements by properly modeling the more efficient operation of IRR networks.     

基于人工免疫的工业认知无线网络路由机制

工业互联网（industrial Internet）已成为第四次工业革命的代表技术.根据工业网络数据传输服务的需求,以及针对工业无线网络拓扑相对稳定、流量规律变化等特点,提出了一种基于人工免疫系统（artificial immune system,简称AIS）的工业认知无线网络路由机制,包含基于链路质量的域内静态路由算法和基于多路径的域间动态路由算法,以实现工业网络的可靠路由.根据人工免疫系统特点,将工业网络的拓扑结构进行区域划分：提出了基于链路质量的域内静态路由算法,采用软硬件结合的方式监视网络链路,并根据移动窗口指数加权平均法计算链路丢包率;提出了基于多路径的域间动态路由算法,根据模式距离对节点的流量周期进行预测,防止节点因流量过大而导致丢包.基于OMNET++仿真平台进行仿真实验,结果表明,所提出的路由机制在应对突发流量时与组合定向地理路由算法相比,丢包率及网络开销分别降低1倍;应对链路失效的情况时与图路由算法相比丢包率降低4倍.     

TAP: Traffic-aware topology control in on-demand ad hoc networks

Energy efficiency is crucial to achieve satisfactory network lifetime in ad hoc networks. In order to reduce the energy consumption significantly, a node needs to turn off its transceiver. Many existing energy-saving algorithms are based on constructing a simplified routing backbone for global connectivity. In this paper some problems involved with node sleep in on-demand ad hoc networks are addressed firstly. Then we propose a distributed, cross-layer Traffic-Aware Participation (TAP) algorithm, where nodes make decisions on whether to sleep or not based on both the traffic pattern and local connectivity. Nodes get dynamic traffic characteristics as well as active neighbors within two hops via routing control and data packets periodically. We further present a lightweight algorithm to avoid network partition resulted from node sleeping. Simulation results show that, compared to current sleep-based topology control algorithms, TAP achieves better network service quality and lower delay while allowing comparable energy conservation.     

无级电话网非线性单纯形动态路由策略及算法评估方法

无级电话网动态路由技术是充分利用现有设备、提高服务质量的关键技术．为了提高求解速度和求解质量，本文提出一个基于非线性单纯形动态路由策略及其评估方法；介绍了在离散的解空间中根据链路负载均方差构造动态路由最优化问题和算法的具体实现；并根据话务溢出率和网络阻塞率对网络正常或网络异常情况下的算法求解结果进行评估；分析了系统运行情况和话务模拟结果．仿真实验与评估结果说明该策略能够在很短的时间内得到质量较优的全局优化的路由方案，该策略正应用于广东省电话网智能管理系统．     

Design and performance analysis of an inductive QoS routing algorithm

Routing mechanism is key to the success of large-scale, distributed communication and heterogeneous networks. Consequently, computing constrained shortest paths is fundamental to some important network functions such as QoS routing and traffic engineering. The problem of QoS routing with multiple additive constraints is known to be NP-complete but researchers have been designing heuristics and approximation algorithms for multi-constrained paths algorithms to propose pseudo-polynomial time algorithms. This paper introduces a polynomial time approximation quality of service (QoS) routing algorithm and constructs dynamic state-dependent routing policies. The proposed algorithm uses an inductive approach based on trial/error paradigm combined with swarm adaptive approaches to optimize lexicographically various QoS criteria. The originality of our approach is based on the fact that our system is capable to take into account the dynamics of the network where no model of the network dynamics is assumed initially. Our approach samples, estimates, and builds the model of pertinent aspects of the environment which is very important in heterogeneous networks. The algorithm uses a model that combines both a stochastic planned pre-navigation for the exploration phase and a deterministic approach for the backward phase. Multiple paths are searched in parallel to find the K best qualified ones. To improve the overall network performance, a load adaptive balancing policy is defined and depends on a dynamic traffic path probability distribution function. We conducted a performance analysis of the proposed QoS routing algorithm using OPNET based on a platform simulated network. The obtained results demonstrate substantial performance improvements as well as the benefits of learning approaches over networks with dynamically changing traffic.     

Probability based dynamic-alternate routing and the corresponding converter placement algorithm in all-optical WDM networks

This paper proposes a new dynamic-alternate routing algorithm and its corresponding converter placement algorithm in order to reduce the connection blocking probability for all-optical WDM networks. The main idea in the proposed dynamic-alternate routing algorithm is to try to route the traffics according to a predefined optimal probability distribution. The problem for finding the optimal probability distribution was shown as a convex optimization problem. The problem can be solved by flow deviation method or other standard optimization techniques. Simulation results show that the proposed routing algorithm yields lower connection blocking probabilities than the previous works. The proposed routing algorithm produces similar traffic pattern as the optimal traffic pattern. The similarity between the traffic pattern produced by the proposed dynamic-alternate routing algorithm and the optimal traffic pattern can be further employed for solving other network designing problems such as converter placement problem. Since the optimal traffic pattern can be easily predicted, the optimal traffic pattern which minimizes the blocked traffic intensity is utilized for finding the locations of wavelength converters. The key idea is to place the wavelength converters at the nodes where they are needed most. Simulations have been performed to study the performance of the proposed wavelength converter placement method. The simulation results have shown that the proposed placement method combined with the proposed probability based dynamic-alternate routing algorithm yields smaller connection blocking probability than the two converter placement methods with their corresponding alternate routing algorithms.     

基于云网格集成调度的防拥堵车辆路径规划算法

在道路交通路网中,车辆拥堵问题是流量与路网结构之间相互作用的一个复杂动态过程,通过车辆路径规划,实现对路网网格集成调度,从而提高路网通行吞吐量。传统方法采用并行微观交通动态负载平衡预测算法实现车辆拥堵调度和车辆路径规划,不能准确判断路面上的车辆密度,路径规划效益不好。提出一种基于云网格集成调度的防拥堵车辆路径规划算法,即构建基于Small-World模型的云网格路网模型,采用RFID标签信息进行路况信息采集,实现交通网络拥堵评估信息特征的提取,采用固有模态函数加权平均求得各车道的车辆拥塞状态函数,对所有车道内车辆密度取统计平均可获得簇内的车辆密度。设计交通路网拥堵检测算法来对当前个体道路信息进行一维邻域搜索,从而实现车辆路径规划控制目标函数最佳寻优。通过动态博弈的方式求得车辆防拥堵路径的近似最优轨迹,实现路径规划算法的改进。仿真结果表明,该算法能准确规划车辆路径,实现最优路径控制,从而提高严重拥堵路段的车流速度和路网吞吐性能,性能优越。     

A framework for end-to-end deterministic-delay service provisioning in multiservice packet networks

The problem of providing end-to-end delay guarantees for deterministic-delay services in multiservice packet networks is addressed through a combination of dynamic resource reservation and routing. Our model is based on using rate-controlled earliest-deadline-first (RC-EDF) for providing hard bounds on end-to-end delays. With RC-EDF, a certain delay bound has to be allocated for a connection at each node in the selected path. The most commonly used resource reservation policy is uniform allocation which is based on dividing the end-to-end delay bound equally among the nodes in the selected path. This simple allocation policy could lead to nonuniform resource loading and subsequently lead to high blocking rates. Moreover, the most commonly used routing method is shortest-path first routing which is known to lead to network hotspots. We propose a set of dynamic nonuniform resource reservation policies and dynamic routing methods. One of the routing methods is the well-known widest-shortest path method and the other is a dynamic routing method that adaptively adjusts link costs and uses a similar algorithm to shortest-path routing (e.g., Dijkstra's algorithm). We show that for both uniform and nonuniform traffic loading of some example network topologies that the combination of the proposed resource reservation policies and dynamic routing can lead to significant reduction in the connection blocking ratio in all loading conditions except for excessively high loads.