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。     

高稳定的可扩展覆盖网多播算法

提出了一种高稳定的可扩展覆盖网多播（SOM-HS, scalable overlay multicast with high stability）算法。SOM-HS算法定义了节点稳定度因子以及链路权重,能保证高稳定的节点位于多播树骨干网中。在分层分簇构造过程中,SOM-HS算法限制节点出度,保证节点负载均衡。实验结论表明,与现有其他算法相比,在不同组规模下,使用SOM-HS算法时的最大多播延时都最小。     

基于稀疏密集阵传输机制的WSN数据传输汇聚算法

为了改善无线传感网(WSN)的数据传输汇聚能力,提出了基于稀疏密集阵传输机制的WSN数据传输汇聚算法。引入核生成函数,设计了一种新的传输矩阵,将簇头节点与sink节点之间连通程度及负载程度进行量化,以提升簇头节点传输效果的评估能力;采用特征向量按列排序并结合卷积算法降低簇头节点传输值,以有效减少簇头节点负载;采用树分解模式搜寻可用哈密尔顿回路,构建了基于路径分解优化机制的汇聚稳定方法;通过使用哈密尔顿寻址来优化叶子节点与根节点之间的数据链路,以增强簇头节点覆盖能力与提高数据传输过程的稳定性能。仿真实验表明,与当前常用的基于阈值筛选模糊分簇的WSN数据稳定汇聚算法和面向医疗应用的无线传感器网络多径数据传输方法相比,所提算法具有更为集中的传输报文集中度,以及更高的传输链路抖动控制能力和网络汇聚带宽。     

面向城市环境的角度矢量分簇选择协议

在车载自组织网VANETs(vehicular ad hoc networks)中,高动态的拓扑结构和频繁断裂的链路给车间通信提出挑战。为此,针对VANETs城市场景,提出基于方向矢量角簇群和桥节点的车间通信VAC-BNR(Vector-angle-cluster and bridge nodes-based routing)协议。VAC-BNR协议将城市道路划分为十字路口区域和十字路口间的直线路段区域。在十字路口区域内,选择合适的车辆作为桥节点,并由桥节点连通断裂的链路。而在直线路段区域,利用矢量角将车辆划分不同的簇群,然后计算每个簇群内节点的效用值,并选择效用值最高的车辆传输数据。仿真结果表明,提出的VAC-BNR协议能够有效地降低端到端传输时延、提高数据包传递率。与AMD相比,VAC-BNR协议的平均端到端传输时延下降了约30%,当车流密度大于80辆/km~2时,数据包传递率提高了约50%。     

基于链路效用的3D-VANET可靠路由算法

针对三维车载自组织网络中,高速移动的车辆节点和复杂多变的链路状态导致车辆间通信链路不稳定的问题,通过引入软件定义网络技术实时获取网络状态并预测其变化过程,构建时-空演化图模型,并定义链路效用指标量化无线链路性能,然后建立基于链路效用的加权时-空演化图模型,最后将路由问题转化为多属性决策问题,设计基于链路效用的可靠路由算法.仿真结果表明,相对现有四种路由算法,本文所提路由算法在数据包传输率、端到端时延和路由负载率方面,性能均有明显提升.     

基于相对移动性预测的k跳AdHoc网络分簇算法

针对网络节点随机移动造成的AdHoc网络分簇结构变化和路由失效问题,该文提出一种基于相对移动性预测的k跳分簇算法,分析和预测网络节点运动状态,自适应地调整分簇结构,提高簇结构稳定性。首先,使用多普勒频移计算节点间相对移动速度,预测节点移动性,得到节点间链路保持时间。然后,在簇形成阶段,采用面向节点稳定性的MAX-MIN启发式算法,根据节点的平均链路保持时间对簇首进行选择。进而,在簇保持阶段,提出一种基于节点运动状态的网络自适应调整算法,一方面调整节点信息数据发送周期以平衡数据开销和精确度,另一方面通过预测节点间链路通断情况调整分簇结构,以减少链路失效时的链路重建时间,提高网络运行质量。仿真实验表明,所提算法可以有效延长簇首持续时间,提高簇结构在动态环境下的稳定性。     

一种两跳聚簇的移动自组网拓扑发现策略

基于两跳聚簇的拓扑发现策略可用于解决移动自组网中由于网络拓扑动态变化带来的拓扑发现难题。该策略使用了节点聚簇和双向链路的方法,规定只有簇头节点才能生成路由更新包,通过采用多点传递集抑制了路由更新包在网络中的泛洪;通过相邻簇的簇头协同管理,最大程度地减少了双向链路被重复报告。分析结果显示,相比于使用普通链路状态协议的拓扑发现策略,该策略消除了将近50%的拓扑发现控制负载。     

车联网中基于分簇结构的多人博弈路由模型的研究

车辆网中车辆的高速移动,网络拓扑频繁变化,运动轨迹多变等特性,为设计高效、可靠、实时的路由协议带来一定的挑战。通过研究和分析车联网环境下路由需要,综合节点间的信任和信号强度等考虑构建分簇结构。引入博弈论的合作与竞争理论对在簇内结点的关系进行分析,从簇内网络的负载均衡性、路由链路的稳定性等网络性能指标综合考虑,提出多人博弈算法构建路由模型。     

支持网络编码的认知无线自组网拓扑控制算法

对认知无线自组网中有限的带宽进行研究,提出支持网络编码的拓扑控制算法。算法分为3个阶段：初始拓扑构建阶段,利用最短路径算法为单播业务构建拓扑,利用基于网络编码的最短路径算法为多播业务构建K冗余拓扑;拓扑优化阶段,通过逐条删除满足一定条件的链路优化拓扑;拓扑恢复阶段,针对关键点失效,利用与失效链路不在同一路径簇且开销最小的链路恢复网络连通。仿真结果表明,算法能够提高无线资源复用率,增强网络抗毁性。     

无线传感器网络LEACH协议的改进与仿真

LEACH路由协议是无线传感器网络中经典的层次型拓扑组织算法。对LEACH协议进行研究和分析,指出LEACH协议在簇的区域分布和簇头负载不均衡等方面问题。文章通过节点剩余能量和与基站的距离对簇头选择、构造分簇以及非簇节点选择簇头进行改进。并利用MATLAB对改进后的算法进行仿真,表明改进后的算法有效地均衡节点能量消耗,并延长网络生存时间。     

面向服务的车辆网络切片协调智能体设计

针对现有研究中缺乏对车辆网络切片的部署和管理，该文设计了车辆网络切片架构中的切片协调智能体。首先基于K-means++聚类算法将车联网通信业务根据相似度进行聚类并映射到对应的切片中。其次，在考虑应用场景间的时空差异导致的无线资源利用不均衡现象，提出了共享比例公平方案以实现对无线资源的高效及差异化利用。最后，为了保证切片服务需求，采用线性规划障碍方法求解最优的切片权重分配，使切片负载变化容忍度最大化。仿真结果表明，共享比例公平方案相比于静态切片方案平均比特传输时延(BTD)更小，在每切片用户数为30的情况下均匀分布用户负载场景中二者的BTD增益为1.4038，且在不同的用户负载分布场景下都能求出最优的切片权重分配。     

基于移动边缘计算的V2X任务卸载方案

移动边缘计算(MEC)通过在移动网络边缘提供IT服务环境和云计算能力带来高带宽、低时延优势,从而在下一代移动网络的研究中引起了广泛的关注。该文研究车载网络中车辆卸载请求任务时搜寻服务节点为其服务的匹配问题,构建一个基于MEC的卸载框架,任务既可以卸载到MEC服务器以车辆到基础设施(V2I)形式通信,也可以卸载到邻近车辆进行车辆到车辆(V2V)通信。考虑到资源有限性、异构性,任务多样性,建模该框架为组合拍卖模式,提出一种多轮顺序组合拍卖机制,由层次分析法(AHP)排序、任务投标、获胜者决策3个阶段组成。仿真结果表明,所提机制可以在时延和容量约束下,使请求车辆效益提高的同时最大化服务节点的效益。     

基于时延—带宽约束的新型层次拓扑聚集算法

针对时延一带宽约束的层次路由问题，提出了楼梯法这一全新的拓扑聚集算法。使用一个规则的楼梯来模拟2个边界节点之间的所有通路支持的QoS属性，将原始拓扑压缩为一个六元组标识的全相连图。然后，根据六元组各参数特性对全相连图分别采用了最大生成树和改进的星型压缩算法进行线性压缩。仿真的结果表明，在聚集后信息空间复杂度同为O（｜B｜）的情况下，楼梯法较其他拓扑聚集算法具有更小的信息失真率。     

Dynamic cache allocation routing strategy of Internet of things satellite node based on traffic prediction

Aiming at the routing problem of low earth orbit (LEO) Internet of things (IoT) satellite systems,a dynamic cache allocation routing strategy based on traffic prediction for IoT satellite nodes was proposed.Firstly,the space-time characteristics of traffic distribution in the LEO coverage area were analyzed,and an end-to-end traffic prediction model was proposed.Then,according to the traffic prediction result,a dynamic cache allocation routing strategy was proposed.The satellite node periodically monitored the traffic load of the inter-satellite link,dynamically allocated the cache resources of each inter-satellite link between the neighboring nodes.The cache allocation process was divided into two phases,initialization and system operation.At the same time,the traffic offload and packet forwarding strategy when the node was congested was proposed.By comparing the queuing delay and the forwarding delay,it was determined whether the data packet needs to be rerouted.The simulation results show that the proposed routing strategy effectively reduces the packet loss rate and average end-to-end delay,and improves the traffic distribution in the whole network.     

3D-VANET中基于模糊逻辑和Q学习的拓扑感知路由协议

城市三维车载自组网（Three-Dimensional Vehicular Ad-hoc Network,3D-VANET）中往往存在多种道路形式,每种道路网络拓扑变化特点各异,平面路由协议不能根据道路特点动态调整选路策略,不宜直接用于3D-VANET,为此设计了一种基于模糊逻辑和Q学习的拓扑感知路由协议。该协议通过模糊逻辑方法感知网络拓扑变化与网络负载情况动态调整信标间隔,以平衡邻节点信息准确性与控制开销成本。在此基础上,采用Q学习算法对网络建模,根据链路质量以及链路质量变化调整Q学习算法参数,以灵活选择下一跳转发节点,更好适应网络拓扑的频繁变化。仿真结果表明,与对比协议相比,该协议有利于降低控制开销,同时提高包投递率和减少平均端到端时延。     

A stable and reliable data dissemination scheme based on intelligent forwarding in VANETs

Vehicular ad hoc networks (VANETs) have gained incredible attention because of their applications in safety, commercial uses, and traffic management. However, the dynamic topology changes caused by the high speed of vehicles raise many challenges for the effective data dissemination in vehicular applications. In this paper, with the objective to solve the problem of frequent disconnection during data delivery, we propose a novel, intelligent forwarding–based stable and reliable data dissemination scheme. First, link stability is described mathematically, by which vehicle chooses the next forwarding node. Then, a greedy algorithm is presented to transmit the data from source to destination. A separate recovery algorithm is also designed to resolve the intermediate link breakage problem. The performance of the proposed method is analyzed by performing extensive network and traffic simulations with respect to various indexes such as latency, packet delivery ratio (PDR), and throughput. Compared with the state‐of‐the‐art protocols, the proposed method under varying density improves the average PDR and throughput by 31.55% and 25.30%, respectively.     

基于链路可靠性的无线虚拟网络分配方法

针对无线网络链路可靠性差影响无线虚拟网络的分配这一问题,提出了一种基于链路可靠性的无线虚拟网络分配算法（WVNEA-LR）。该算法通过物理网络拓扑预处理和允许同一个虚拟请求中的多个虚拟节点映射到同一个物理节点上的方法,提高了Vn构建成功率和节约了物理链路资源。利用Q因子改善了因拓扑分配稀疏时Vn构建成功率低的问题。此外,WVNEA-LR的节点分配为链路分配作了准备,并通过选择可靠性高的承载路径保证了分配后的Vn具有高可靠性。仿真结果表明, WVNEA-LR获得较好的虚拟网络构建成功率、较高的收益成本比和资源利用率。     

Connectivity analysis of passive cluster with high stability in vehicular wireless network

A passive cluster model with the maximum lifetime was proposed for vehicle to vehicle communication based on the relative velocity. The cluster head was elected based on the average relative velocity and the neighbor list. The cluster lifetime was deduced as the function of the average relative velocity. The traffic safety messages were dissemi-nated to all cluster members by inter-cluster message broadcasting and intra-cluster message relaying in interconnected vehicular network. The link connectivity probability between the cluster head and members were deduced as the function of the vehicle density for inter-cluster broadcasting. The path connectivity probability between the cluster head and the neighbor cluster head was deduced as the function of the vehicle density and intra-cluster distance for on intra-cluster dis-semination. Simulation results show that the connected probability is suitable for vehicular network under the traffic den-sity constraints.     

Dynamic service migration strategy based on MDP model with multiple parameter in vehicular edge network

To handle with the service interruption caused by vehicles’ mobility and limited service coverage of edge servers,a dynamic service migration algorithm based on multi-parameters Markov decision process (MDP) model was put forward for vehicular edge network,which was called as dynamic service migration algorithm based on multiple parameter (DSMMP).Combining delay,bandwidth,server capacity with vehicle motion information,DSMMP constructed a multi-parameters MDP revenue function to remedy the deficiency of distance-based schemes.By using vehicle motion and delay constraints,a candidate server set with several candidate servers was defined,and migration decision through long-term Bellman revenue values was made.In order to improve the dynamic adaptability of the proposed algorithm,the weight values were calculated and updated by leveraging historical information.Simulation results show that our strategy has a good performance in terms of delay,packet loss ratio and service migration times.     

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.