无人机集群联合拓扑控制的智能路由规划方法

针对现有无人机集群路由协议拓扑适变能力弱,易产生包重传、能量空洞和高时延,严重恶化了数据路由性能的问题,针对无人机集群中集群拓扑与路由的耦合特性,提出了一种联合拓扑控制的智能路由规划（IRPJTC）方法。该方法由基于虚拟力的自适应拓扑控制（VFATC）和基于近端策略优化的地理路由规划（PPO-GRP）组成。其中,VFATC使各无人机根据邻居运动状态信息自适应调整与邻居的距离,保证集群中链路的稳定连接;进一步,PPO-GRP引入VFATC中的链路稳定性指标,并结合端到端时延与能耗指标,设计多目标奖励函数,采用深度强化学习中的近端策略优化算法训练路由策略。仿真实验结果表明,IRPJTC相比于现有路由方法,能在保证分组传输成功率的同时,使端到端时延降低12.11%,无人机集群能耗降低4.56%,且具备更强的能耗均衡能力。     

QL-STCT：一种SDN链路故障智能路由收敛方法

针对软件定义网络（SDN）链路故障发生时的路由收敛问题,提出了Q-Learning子拓扑收敛技术（QL-STCT）实现软件定义网络链路故障时的路由智能收敛。首先,选取网络中的部分节点作为枢纽节点,依据枢纽节点进行枢纽域的划分。然后,以枢纽域为单位构建区域特征,利用特征提出强化学习智能体探索策略来加快强化学习收敛。最后,通过强化学习构建子拓扑网络用于规划备用路径,并保证在周期窗口内备用路径的性能。实验仿真结果表明,所提方法能够有效提高链路故障网络的收敛速度与性能。     

基于链路失效模型的多级电力业务路由规划

该文从智能电网中电力业务多样性的角度出发,分析不同类型业务对网络的可靠性需求。建立链路失效函数模型,并基于该模型设计面向可靠性的路由规划方法。以网络阻塞率和资源利用率为指标,通过与传统链路失效路由算法的比较分析来验证所提出方法的有效性。传统链路失效路由规划算法忽略了电力业务多样性,对接入网络的业务请求无差别处理,路由规划约束条件相对单一,导致网络阻塞率较高。该文所提路由算法充分考虑了不同业务对网络需求的多样性,依据业务等级调整目标函数并分别进行路由分配,从而降低网络阻塞率,提升网络可靠性和资源利用率。     

具有容错能力的波长路由光网络的拓扑设计

研究了具有容错能力的波长路由光网络的拓扑设计问题.提出了一种基于业务流的初始物理拓扑产生算法,与随机拓扑生成算法相比,该算法产生的物理拓扑更接近于最优拓扑.另外,还提出了一种新的链路拥塞计算方法,它能够更好地反应链路的实际状态.数值结果显示文章提出的物理拓扑设计策略具有更快的收敛速度.     

一个应用于星簇内部的动态重构策略

根据星簇内部网络拓扑动态变化,提出了一种适用于星簇内卫星受损后可自主实现拓扑和动态重构新策略,包括节点和链路的动态重构策略。提高了星簇内部拓扑结构的稳定性,并结合了路由反转算法和按需路由算法来保障通信效率,并充分考虑了星簇内卫星拓扑结构以三角形形成的局域网最为稳定等特点,为星簇内部的动态重构提出了一种新方法。     

多层卫星网络链路中断容忍路由策略设计

链路中断和接续对卫星网络路由有重要影响,该文针对多层卫星网络,设计了链路中断容忍路由策略,利用非均匀时间段内卫星网络拓扑结构的可预测性进行路由表计算,采取动态的拥塞控制机制和洪泛策略,解决由于卫星运动、通信设备故障引发链路中断情况下的路由问题。仿真结果表明,该路由策略具有较高的链路利用率,能够减少动态路由计算中时延信息收集和星上路由表生成给卫星节点带来的时空开销。     

低轨卫星星座快速响应链路损毁路由算法

设计高效弹性的卫星路由算法是未来低轨(Low Earth Orbit, LEO)卫星通信技术的一个重要发展方向。为解决低轨卫星星座网络中星间链路发生故障后存在的传输中断和数据安全问题,提出了一种低轨卫星星座快速响应链路损毁路由算法(Quick-response Link Destruction Routing Algorithm for LEO Satellite Constellation, QRLDRA)。QRLDRA以星座可预测拓扑作为星间路由计算基础,增加星地回传路由设计,快速将星间链路异常回传至地面计算中心处理;引入多优先级动态队列,根据节点链路状态调整星间链路不同数据传输的优先级;综合路由计算、路由上注、链路检测等功能,完成对拓扑变化的及时响应。通过仿真实验与传统算法的比较发现,所提算法有效提高了数据端到端传输的成功率,为用户业务服务质量(Quality of Service, QoS)提供了可靠保障。     

面向卫星网络的流量工程路由算法

针对卫星网络链路长时延、拓扑时变等特征,将链路传输时延引入并基于MPLS网络中源-目的节点对已知这一先验知识,提出了一种面向卫星网络的MPLS流量工程路由算法。该算法基于卫星网络时变拓扑模型的卫星拓扑快照,定义链路初始权重为链路剩余带宽、传输时延的综合函数,在为当前节点对建路时考虑其余节点对将来建路的可能需求计算链路的关键度,在此基础上通过链路权重的动态调整及延期选用实现流量工程,从而优化卫星网络的链路利用。实验表明,此算法在请求拒绝数、吞吐量、平均跳数及平均时延等方面性能都有较理想的提升。     

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.     

光网络中实现流量工程的负载均衡动态路由算法

提出了一种在光网络中实现流量工程的负载均衡动态路由算法(LBDRO).该算法通过新定义的链路关键度函数和链路当前可用带宽确定链路动态成本,并依据该动态成本运用最短路径优先算法为到达的LSP请求建立动态成本优化路径.该算法的计算复杂度低,仿真实验表明,与MHA、WSP、MIRA算法相比,在光传输网络中,该算法在降低LSP建立请求服务拒绝率、均衡网络负载以及链路失效后重路由等方面有很好的性能.     

Minimum delay algorithm based on time aggregated graph in DTN network

The DTN network has the characteristics of dynamic topology change,thus the routing algorithm of static network can not solve the routing problem of time-varying network,and can not support fast transmission of given tasks.The existing time-variant routing algorithm CGR (contact graph routing) uses the earliest contact to obtain the shortest path,but because of the influence of the order of the connectivity period,the CGR algorithm has low link utilization.To solve this problem,the method of finding the shortest path was proposed.Besides,in order to characterize the relation between the different connect periods of the same link,the time series of node cache was added to the time aggregated graph.Based on this,the end-to-end multi-path shortest delay routing algorithm for the known task requirements was proposed.Finally,the feasibility of the algorithm was proved by an example.     

Dynamic wavelength routing using congestion and neighborhoodinformation

We present two dynamic routing algorithms based on path and neighborhood link congestion in all-optical networks. In such networks, a connection request encounters higher blocking probability than in circuit-switched networks because of the wavelength-continuity constraint. Much research has focused on the shortest-path routing and alternate shortest-path routing. We consider fixed-paths least-congestion (FPLC) routing in which the shortest path may not be preferred to use. We then extend the algorithm to develop a new routing method: dynamic routing using neighborhood information. It is shown by using both analysis and simulation methods that FPLC routing with the first-fit wavelength-assignment method performs much better than the alternate routing method in mesh-torus networks (regular topology) and in the NSFnet T1 backbone network (irregular topology). Routing using neighborhood information also achieves good performance when compared to alternate shortest-path routing     

Calcul des métriques de routage pour Internet

In spite of the development of Internet networks and the important volume of literature dealing with Internet routing, many fundamental topics were not addressed. Traffic is, in principle, routed through shortest paths, in sense of a set of link weights (a metric). These weights do not necessarily have a physical significance and could be modified by the network administrator to change the routing policy and the network cost. In this paper, we give precise answers for the following questions: 1/ Given a network topology, is there a metric such that, first, the shortest path between any pair of vertices is unique and, second, every link belongs to at least one shortest path ? 2/ How can we compute such a metric ? 3/ Can we choose a metric satisfying these constraints and whose values are small integers ? 4/ If the routers of the network have differents functions and caracteristics, is it possibe to determine a metric which allows to route traffic, taking into account these heteregeneous caracteristics ? 5/ If some routing paths are seleceted due to technical or economical reasons, can we find a metric enforcing this given routing policy ? 6/ If this is not possible, what should we do to compute a metric that is as close as possible to the selected routing paths ?     

基于局部拓扑控制的认知网络路由方法

针对认知网络研究一种融合主、次用户多因素优化的局部拓扑控制和路由方法。该方法综合考虑主用户频谱使用情况以及次用户对主用户干扰影响,预测认知链路的稳定性,结合链路功耗,定义一种联合链路代价,提出链路代价最小的局部认知拓扑控制路由 (LCTCR)算法,优化网络拓扑,并在优化后的拓扑上进行网络路由的选择。算法分析和仿真实验证明,在进行认知网络路径选择时,链路功耗和链路稳定性均为重要参数,需联合优化以保证选择更优的实际路由。     

Performance evaluation of adaptive routing algorithms in packet‐switched intersatellite link networks

This paper addresses the performance evaluation of adaptive routing algorithms in non‐geostationary packet‐switched satellite communication systems. The dynamic topology of satellite networks and variable traffic load in satellite coverage areas, due to the motion of satellites in their orbit planes, pose stringent requirements to routing algorithms. We have limited the scope of our interest to routing in the intersatellite link (ISL) segment. In order to analyse the applicability of different routing algorithms used in terrestrial networks, and to evaluate the performance of new algorithms designed for satellite networks, we have built a simulation model of a satellite communication system with intersatellite links. In the paper, we present simulation results considering a network‐uniform source/destination distribution model and a uniform source–destination traffic flow, thus showing the inherent routing characteristics of a selected Celestri‐like LEO satellite constellation. The updates of the routing tables are centrally calculated according to the Dijkstra shortest path algorithm. Copyright © 2002 John Wiley & Sons, Ltd.     

Performance Analysis of an Adaptive Link Status Update Scheme Based on Link‐Usage Statistics for QoS Routing

In the global Internet, a constraint‐based routing algorithm performs the function of selecting a routing path while satisfying some given constraints rather than selecting the shortest path based on physical topology. It is necessary for constraint‐based routing to disseminate and update link state information. The triggering policy of link state updates significantly affects the volume of update traffic and the quality of services (QoS). In this letter, we propose an adaptive triggering policy based on link‐usage statistics in order to reduce the volume of link state update traffic without deterioration of QoS. Also, we evaluate the performance of the proposed policy via simulations.     

New dynamic algorithms for shortest path tree computation

The open shortest path first (OSPF) and IS-IS routing protocols widely used in today's Internet compute a shortest path tree (SPT) from each router to other routers in a routing area. Many existing commercial routers recompute an SPT from scratch following changes in the link states of the network. Such recomputation of an entire SPT is inefficient and may consume a considerable amount of CPU time. Moreover, as there may coexist multiple SPTs in a network with a set of given link states, recomputation from scratch causes frequent unnecessary changes in the topology of an existing SPT and may lead to routing instability. We present new dynamic SPT algorithms that make use of the structure of the previously computed SPT. Besides efficiency, our algorithm design objective is to achieve routing stability by making minimum changes to the topology of an existing SPT (while maintaining shortest path property) when some link states in the network have changed. We establish an algorithmic framework that allows us to characterize a variety of dynamic SPT algorithms including dynamic versions of the well-known Dijkstra, Bellman-Ford, D'Esopo-Pape algorithms, and to establish proofs of correctness for these algorithms in a unified way. The theoretical asymptotic complexity of our new dynamic algorithms matches the best known results in the literature     

Load balance in hierarchical routing network

In this article, the problem of load balance in hierarchical routing network is studied. Since conventional shortest path first (SPF) algorithm over aggregated topology in hierarchical routing network may result in worse routing performance, a traffic sharing path selection algorithm and a variable weight scheme are put forward for hierarchical routing network, which can equilibrate the utilities of link resources and reduce the blocking probability of connections with the improvement on survivability. Simulations are conducted to evaluate proposed variable weight and traffics balance (VWTB) algorithm, which combines traffic sharing and variable weight. From the simulation results, it can be found that the proposed VWTB algorithm can balance the traffics and equilibrate the utilities of link resources significantly.     

Simulation and theoretical results on cluster management anddirectory management in dynamic hierarchical networks

A cluster management scheme for dynamic networks, the purpose of which is to maintain the cluster structure of the hierarchical network as a balanced-tree topology is presented. The theoretical time complexity bounds of the cluster management scheme for node birth and death are derived. The effects of the cluster management on gate-connected fixed-node networks under heavy intercluster traffic situations are discussed. In order to show that the scheme can handle realistic communication networks, routing tables and OD pair shortest path routing are used. The settle-down time, throughput, and end-to-end link delays of a network that uses cluster management and a network of the same topology that only uses flooding are compared     

一种新的基于混沌神经网络的动态路由选择算法

针对通信网的路由选择问题,提出了一种动态路由选择的混沌神经网络实现方法。所提出的此方法具有许多优良特性,即暂态混沌特性和平稳收敛特性,能有效地避免传统Hopfield神经网络极易陷入局部极值的缺陷。它通过短暂的倒分叉过程,能很快进入稳定收敛状态。实验证明了本算法能实时、有效地实现通信网的路由选择,并且当通信网中的业务量发生变化时,算法能自动调整最短路径和负载平衡之间的关系。