控制器故障下的软件定义机载网络数据平面迁移策略

软件定义网络（SDN）为突破机载网络功能僵化所造成的瓶颈提供了新的契机。针对软件定义机载网络控制域内控制节点故障问题,提出一种基于时延和负载均衡的传输节点迁移策略,将故障控制节点所管控数据平面中的传输节点迁移至其他正常控制节点,恢复网络的正常管控。以迁移时延和负载均衡率为目标,建立迁移优化模型,提出基于时延和负载均衡的传输节点迁移算法,指导数据平面中的迁移动作,最终对两个性能目标进行综合权衡。实验结果表明,与距离就近迁移（DCM）策略和分布式逐跳（DHA）策略相比,所提策略在迁移时延和负载均衡率2个方面进行了合适的折中,避免出现迁移时延过大或控制节点负载失衡的情况,有效解决机载网络故障恢复问题。     

网络化综合化的天地一体化信息系统探讨

针对天地联网中空间与地面网络节点的信息高效互通、交换及应用需求,利用电子信息综合化技术实现高度综合化的多功能通用平台,构建天基以及地面系统"资源池",结合SDN(Software Defined Network,软件定义网络)架构、网络协议与路由网关,将有效解决网络中由于物理界限造成的信息阻隔,实现物理资源与边界虚拟化、信息流程智能化的天地一体化天基信息系统,提高天基信息资源利用率、信息按需定制及高效共享能力.结合天基信息系统发展趋势,探讨了天地一体化信息系统的网络化、综合化应用建议和研究重点,梳理了天、地节点综合化、网络化的关键技术方向.     

一种基于时空等级的LEO卫星网络路由策略

随着5G技术的发展和6G技术的研究，低轨卫星网络在未来空天地一体化网络中的地位越发重要，而作为网络核心技术的路由策略仍面临一些挑战，如卫星网络拓扑高动态变化、链路频繁切换、节点计算处理能力有限以及负载流量分布不均衡等。针对卫星所覆盖区域负载不均衡且与时间因素有关，以及星上用户多业务服务质量需求的问题，设计了一种基于时空等级的业务分类负载均衡路由算法。算法考虑了卫星网络流量的分布与时空等级的关系。卫星节点需先根据当前时刻及其所覆盖的地面区域计算其时空等级，并在路由算法的下一跳实时调整阶段加入时空等级作为选路条件之一，同时改进了阈值的计算方式，并在路由时考虑了不同的链路代价以满足多业务服务质量需求。仿真结果表明，相较于DSP、TLR和RMLBR算法，所提算法虽然在总吞吐量表现不及TLR和RMLBR算法，但在时延以及链路利用率方面有所改进，有效降低了平均端到端时延，较好地满足不同业务服务质量需求，均衡网络负载。     

卫星网络动态资源图多QoS约束路由算法

针对高动态卫星网络拓扑变化导致的网络更新期间可用路径失效，QoS需求难以满足的问题，提出了一种基于软件定义网络（SDN）架构的虚拟节点动态资源图多QoS约束路由算法（DRGVN-QR）。根据节点的切换状态、缓存以及链路的剩余带宽、时延等信息，结合虚拟节点的网络拓扑方式，建立虚拟节点动态资源图模型。根据资源图模型，建立最小路径代价的优化模型，利用蚁群算法（ACO）并发地为每个连接请求找到一段时间范围内的最优路径集合，并对信息素挥发系数的取值问题进行了讨论，以提升路径质量和算法性能。最后，为了适应卫星网络的时变性，设计一种幂数加权公式求出一段时间范围内的最优路径。仿真结果表明：DRGVN-QR算法能够规避路径失效带来的传输中断问题，提高网络QoS，与其他算法相比，该算法降低了平均端到端时延、网络丢包率和时延抖动。     

基于OPNET的低轨卫星网络路由仿真与优化

针对业务高速化、多样化背景的LEO(低地球轨道)卫星通信网络传输问题,提出一种复合分组调度策略和基于拥塞控制的备份路由方法相结合的路由算法,既保证了不同业务的服务质量,也在网络部分卫星节点因负载较重发生拥塞时实现业务分流,避免低优先级业务因资源竞争力较弱而"饿死",保证各业务的吞吐率,提高网络的性能。最后,以OPNET(优化网络工程工具)软件搭建了LEO卫星网络仿真平台,对文中提出的路由协议进行仿真,验证了算法的有效性。     

一种面向航空集群的集中控制式网络部署方法

软件定义网络（SDN）的发展为机载网络构建提供了全新的设计思想。针对航空集群环境下控制平面的可扩展性问题,研究了混合层次式架构下的多控制器部署问题。首先,为实现对底层传输节点的弹性管控,通过扩展控制层级定义了本地控制器资源池。然后,为减少时间复杂度,实现本地控制器的快速部署,将传统的多控制器直接部署转化为子域划分和域内部署两个步骤,提出了基于节点密度排序的子域划分算法和基于改进多目标模拟退火的域内控制器部署算法。实验结果表明：与已有算法相比,所提算法在保证控制器的负载均衡基础上,可以有效减少网络控制链路的平均时延和平均失连率,同时时间复杂度更低,能够适用于大规模及动态网络环境下的控制器部署场景。     

基于缓存的结构化P2P路由算法研究

P2P网络中的资源经常会被不同节点重复查找,有些热门资源被重复查找的概率更高,如何保证资源在重复查找时的效率,提高路由算法对已查找结果的自记忆能力,是一个亟待解决的问题.在分析传统的Pastry路由算法基础上,采用内容缓存机制和路径缓存机制来改善路由性能,重点研究了不同消息重复率下的路由性能.在不同节点个数和不同的消息重复率下进行大量模拟实验,结果表明改进后的路由算法随着消息重复率的升高,算法的路由性能明显改善.     

基于蚁群算法的多路径QoS路由算法研究

针对现代网络通信量不断地增大以及蚁群算法在解决路由问题时存在的一些不足提出了基于改进蚁群算法的路由优化算法。该算法将蚁群系统的特点和流量工程的思想相结合对基本的蚁群算法进行了3方面的改进：将路由器的缓冲队列的利用率加入下一结点选择的标准;采用链路的利用率做为全局更新信息素;选择多条路径来进行数据传输。仿真实验结果表明该算法可以实现网络负载均衡,降低拥塞发生的可能性,提高了网络资源的利用率。     

基于MPLS流量工程综述

传统内部网关协议容易造成网络资源使用的不均衡,导致网络性能下降.流量工程是解决这一问题的有力工具.多协议标签交换则为流量工程的实施提供了便利.在介绍MPLS流量工程基本概念的基础上,对其核心技术基于约束的路由选择进行了系统的分析和综述,重点分析了现有的数学模型和优化算法.并讨论了存在的问题,提出了今后可能的发展方向.     

一种基于最近相遇节点树的DTN多副本路由算法

在网络拓扑无法事先规划、节点运动有一定社区性、节点缓存能力与网络资源受限的DTN典型应用场景中,存在传统多副本路由算法无法完成的数据包多跳递交问题。针对这一问题与应用场景特点,在经典的Spray and Focus与Prophet算法基础上,提出了一种基于最近相遇节点树的DTN多副本路由算法,并使用基于NS-3的DTN仿真软件与4种经典多副本路由算法Epidemic、Spray and Wait、Spray and Focus、Prophet进行网络性能比较。仿真结果表明:最近相遇节点树机制改善了无法间接递交问题,且该路由算法在缓存平均占用量、递交率、网络有效开销比等网络性能指标上,相比4种经典DTN多副本路由算法均有明显提升。研究结果可对未来月表探测、地球社群网络等DTN典型场景的应用提供参考。     

Oscillation suppression for traffic class dependent routing in ISL network

Adaptive per-hop routing in the intersatellite link (ISL) network of a packet-switched, nongeostationary satellite system is addressed. In particular, a traffic class dependent (TCD) routing is proposed with different optimization criteria for different traffic classes. Furthermore, for delay sensitive traffic, performance is enhanced by an exponential smoothing link-cost function, which reduces traffic load oscillations in the network. The performance of the proposed procedures is evaluated in two different traffic scenarios using an appropriate simulation model     

Reinforcement learning based dynamic distributed routing scheme for mega LEO satellite networks

Recently, mega Low Earth Orbit (LEO) Satellite Network (LSN) systems have gained more and more attention due to low latency, broadband communications and global coverage for ground users. One of the primary challenges for LSN systems with inter-satellite links is the routing strategy calculation and maintenance, due to LSN constellation scale and dynamic network topology feature. In order to seek an efficient routing strategy, a Q-learning-based dynamic distributed Routing scheme for LSNs (QRLSN) is proposed in this paper. To achieve low end-to-end delay and low network traffic overhead load in LSNs, QRLSN adopts a multi-objective optimization method to find the optimal next hop for forwarding data packets. Experimental results demonstrate that the proposed scheme can effectively discover the initial routing strategy and provide long-term Quality of Service (QoS) optimization during the routing maintenance process. In addition, comparison results demonstrate that QRLSN is superior to the virtual-topology-based shortest path routing algorithm.     

Air route network optimization in fragmented airspace based on cellular automata

Air route network optimization,one of the essential parts of the airspace planning,is an effective way to optimize airspace resources,increase airspace capacity,and alleviate air traffic con gestion.However,little has been done on the optimization of air route network in the fragmented airspace caused by prohibited,restricted,and dangerous areas (PRDs).In this paper,an air route network optimization model is developed with the total operational cost as the objective function while airspace restriction,air route network capacity,and non-straight-line factors (NSLF) are taken as major constraints.A square grid cellular space,Moore neighbors,a fixed boundary,together with a set of rules for solving the route network optimization model are designed based on cellular automata.The empirical traffic of airports with the largest traffic volume in each of the 9 flight information regions in mainland China is collected as the origin-destination (OD) air port pair demands.Based on traffic patterns,the model generates 35 air routes which successfully avoids 144 PRDs.Compared with the current air route network structure,the number of nodes decreases by 41.67％,while the total length of flight segments and air routes drop by 32.03％ and 5.82％ respectively.The NSLF decreases by 5.82％ with changes in the total length of the air route network.More importantly,the total operational cost of the whole network decreases by 6.22％.The computational results show the potential benefits of the model and the advantage of the algorithm.Optimization of air route network can significantly reduce operational cost while ensuring operation safety.     

Traffic class dependent routing in ISL networks

This work addresses traffic class dependent (TCD) routing, using different link-cost functions, in the intersatellite link (ISL) network of a nongeostationary packet-switched satellite communication system. Three different traffic classes are introduced, each with its particular optimisation criteria. Performance analysis of TCD routing, in terms of average packet delay and average data throughput of a particular traffic class, is evaluated for homogeneous and nonhomogeneous traffic scenarios using a specifically developed simulation model of the ISL network.     

ELGR: An Energy-efficiency and Load-balanced Geographic Routing Algorithm for Lossy Mobile Ad Hoc Networks

Geographic routing is a highly active area of research in mobile ad hoc networks (MANETs) owing to its efficiency and scalability. However, the use of simple greedy forwarding decreases the packet reception rate (PRR) dramatically in unreliable wireless environments; this also depresses the network lifetime. Therefore, it is important to improve delivery performance and prolong MANET lifetime simultaneously. In this article, a novel geographic routing algorithm, named energy-efficiency and load-loalanced geographic routing (ELGR), is presented for lossy MANETs. ELGR combines energy efficiency and load balance to make routing decisions. First, a link estimation scheme for the PRR is presented that increases the network energy efficiency level. Second, a learning method is proposed to adaptively sense local network loads, allowing enhanced whole network load balance. The results of a simulation show that ELGR performs better than several other geographic routing algorithms; in particular it extends network lifetime by about 20%, with a higher delivery ratio.     

Effective local dynamic routing strategy for air route networks

With the rapid development of air transportation, network service ability has attracted a lot of attention in academe. Aiming to improve the throughput of the air route network(ARN), we propose an effective local dynamic routing strategy in this paper. Several factors, such as the routing distance, the geographical distance and the real-time local traffic, are taken into consideration.When the ARN is in the normal free-flow state, the proposed strategy can recover the shortest path routing(SPR) strategy. When the ARN undergoes congestion, the proposed strategy changes the paths of flights based on the real-time local traffic information. The throughput of the Chinese air route network(CARN) is evaluated. Results confirm that the proposed strategy can significantly improve the throughput of CARN. Meanwhile, the increase in the average flying distance and time is tiny. Results also indicate the importance of the distance related factors in a routing strategy designed for the ARN.     

Research of multi-path routing based on network coding in space information networks

A multi-path routing algorithm based on network coding is proposed for combating long propagation delay and high bit error rate of space information networks. On the basis of traditional multi-path routing, the algorithm uses a random linear network coding strategy to code data pack- ets. Code number is determined by the next hop link status and the number of current received packets sent by the upstream node together. The algorithm improves retransmission and cache mechanisms through using redundancy caused by network coding. Meanwhile, the algorithm also adopts the flow distribution strategy based on time delay to balance network load. Simulation results show that the proposed routing algorithm can effectively improve packet delivery rate, reduce packet delay, and enhance network performance.