机场特种车辆监控系统中低能耗路由的研究

针对原有ZigBee路由方法应用于机场特种车辆监控系统中节点能量消耗大的缺点，提出了基于ZigBee的低能耗路由算法——LEZR（low—energy ZigBee routing）。该算法通过让节点尽量处于休眠状态来节省能量，从而延长网络生命周期。仿真结果表明，基于此方法设计的系统网络较原路由方法在节能和延长网络生命周期方面都有显著提高。     

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.     

基于最小跳数的无线传感器网络跨层设计

传统的严格分层参考模型无法实现对无线传感器网络资源的有效管理和运用,跨层设计是提高网络整体性能的一种有效方法。针对无线传感器网络能量、计算资源、存储资源和带宽资源有限的特点,提出一种基于最小跳数的路由层和MAC层的跨层协议设计方案。MAC层和路由层通过共享sensor节点到sink节点的最小跳数信息,在MAC层建立时间梯度,解决多个节点共享无线信道的问题;并在路由层建立路由表,解决路由选择问题。仿真结果表明,该方案在降低网络能耗的同时,在降低传输延迟,提高数据投递率方面也取得了良好的性能。     

LEACH协议的改进与仿真研究

无线传感器网络由能量受限的节点组成,高效节能的路由算法是路由设计的关键问题。在LEACH算法的基础上,提出了一种新的分簇式路由策略,从簇头个数的确定、簇头选举方法对LEACH算法进行了改进,数据传输方式允许采用多跳方式与基站节点通信,仿真结果表明该算法具有降低网络能耗、延长网络生命周期的优点。     

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。     

基于蚁群优化的能量均衡自适应路由算法

基于蚁群优化的WSNs路由算法具有蚁群优化自组织性、正反馈性和并行性的特点,在构造无线传感器网络中的最优路由时有很好的性能。但是蚁群优化构造最优解时带来的网络开销十分可观,不适合在路由维护阶段反复使用蚁群优化重构路由。考虑到蚁群优化的上述特点,同时针对无线传感器网络能量受限的特点,提出了一种基于蚁群优化的能量均衡白适应路由算法。该算法使用了新的信息素更新算子,算子中包含了网络能量水平因子,能够均衡网络能量消耗。在路由维护阶段,该算法使用了新的基于侦测蚂蚁的自适应路由维护机制,很好地降低了网络开销。     

Cooperative Routing for Maximizing Network Performance of Wireless Networks

To greatly increase spectral efficiency and improve network performance in wireless networks,a novel cooperative routing algorithm,namely maximum throughput cooperative routing(MTCR) algorithm,is proposed.According to cooperative link model,throughput analysis is presented to evaluate performance improvement in the process of exploiting cooperative commu-nication from physical layer to higher layer.Taking the throughput improvement as performance metric,a cooperative relay se-lection scheme is developed.Finally,based on the route constructed by adaptive forwarding cluster routing(AFCR) algorithm,each node on the route selects the optimum cooperative node from all the potential cooperative nodes to construct the coopera-tive link with maximum throughput so that cooperative route with maximum network throughput from source to destination can be set up.Simulation results show that compared with the noncooperative routing algorithm and minimum power selection de-code-and-forward(MPSDF) routing algorithm,the proposed algorithm can obviously improve network throughput in the pres-ence of low transmission power,large number of nodes and high spectral efficiency.     

混合SDN的多目标路由优化算法

为充分利用SDN(Software Defined Network,软件定义网络)节点的优势来优化网络性能,混合SDN的流量工程成为当前的研究热点,而路由优化是实现流量工程目标的重要策略之一.但是,当前混合SDN的流量工程中未考虑网络整体的负载均衡以及SDN节点的处理能力.针对上述问题,提出了一种多目标路由优化算法——MCS(Minimum Cost Sum,最小化代价和),综合考虑整个网络的传输延迟与链路利用率,同时保证SDN节点的处理能力满足实际约束,最终实现全网综合性能的最优化.实验结果表明,当网络整体负载较轻,MCS与现有的SOTE(SDN/OSPF Traffic Engineering,软件定义网络/开放最短路径优先流量工程)算法性能相近;而当网络负载加重时,MCS相比于SOTE,可将网络负载降低约9％,因此,MCS算法具有更高的优化能力.     

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.     

基于最短路径和负载动态的改进路由策略

随着计算机通讯技术的发展和网络的普及,信息资源日益膨胀,随时导致网络拥塞的发生,甚至造成网络崩溃。为了对网络拥塞进行控制,提出了基于最短路径和局部负载动态的改进路由策略。采用基于距离优先和度优先连接的复杂网络演化模型构建现实网络的模拟网络,并在此基础上再对所提出的改进路由策略进行仿真实验,仿真结果充分说明提出的改进路由策略在网络拥塞控制上效果更优。     

Aerial-ground collaborative routing with time constraints

The advancement of autonomous technology makes electric-powered drones an excellent choice for flexible logistics services at the last mile delivery stage. To reach a balance between green transportation and competitive edge, the collaborative routing of drones in the air and trucks on the ground is increasingly invested in the next generation of delivery, where it is particularly reasonable to consider customer time windows and time-dependent travel times as two typical time-related factors in daily services. In this paper, we propose the Vehicle Routing Problem with Drones under Time constraints (VRPD-T) and focus on the time constraints involved in realistic scenarios during the delivery. A mixed-integer linear programming model has been developed to minimize the total delivery completion time. Furthermore, to overcome the limitations of standard solvers in handling large-scale complex issues, a space-time hybrid heuristic-based algorithm has been developed to effectively identify a high-quality solution. The numerical results produced from randomly generated instances demonstrate the effectiveness of the proposed algorithm.     

多块网格网络并行计算中的负载分配研究

针对CFD中多块网格计算的特点，并使用MPI网络并行系统，对某战斗机绕流进行了基于三维Euler方程的并行计算，主要研究了多块网格并行计算中负载的分配方法，发展了负载自动分配和网格自动重分区程序，计算结果表明：并行计算结果和实验结果完全吻合，8个节点机的并行效率达到了89％。     

基于分区簇头选择簇间多跳的路由协议

针对LEACH协议在能耗方面存在的不足,提出了一种分区簇头选择和簇间多跳的新协议。该协议分区域进行簇头选举、考虑了节点剩余能量、簇间采用多跳的方式传输数据。仿真结果表明,与LEACH协议相比,新协议有效的均衡了节点能耗,提高了能量利用率,延长了网络寿命。     

UMR: A utility-maximizing routing algorithm for delay-sensitive service in LEO satellite networks

This paper develops a routing algorithm for delay-sensitive packet transmission in a low earth orbit multi-hop satellite network consists of micro-satellites. The micro-satellite low earth orbit(MS-LEO) network endures unstable link connection and frequent link congestion due to the uneven user distribution and the link capacity variations. The proposed routing algorithm,referred to as the utility maximizing routing(UMR) algorithm, improve the network utility of the MS-LEO network for carrying flows with strict end-to-end delay bound requirement. In UMR, first, a link state parameter is defined to capture the link reliability on continuing to keep the end-to-end delay into constraint; then, on the basis of this parameter, a routing metric is formulated and a routing scheme is designed for balancing the reliability in delay bound guarantee among paths and building a path maximizing the network utility expectation. While the UMR algorithm has many advantages, it may result in a higher blocking rate of new calls. This phenomenon is discussed and a weight factor is introduced into UMR to provide a flexible performance option for network operator. A set of simulations are conducted to verify the good performance of UMR, in terms of balancing the traffic distribution on inter-satellite links, reducing the flow interruption rate,and improving the network utility.     

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     

网络连接机群上CFD计算的一种负载平衡方法

讨论在网络连接的分布式存储并行机群上进行CFD计算的一种负载平衡方法和相关问题。当数值计算的方法是区域分解法时,各节点机上的负载与其处理的子区域的网格节点数成正比,所以同样大小的子区域可保证负载平衡。采用负载再分配即区域再剖分的方法来达到动态负载平衡,构造了一种对多块网格(每块内为结构网格但各块间的连接关系可以是非结构的)进行近似平均分划的方法,并用一种数据结构和算法保证了剖分出的多个子区之间正确的互联和边界信息传递关系。给出了用这种剖分算法对常见多块网格进行分划的例子,并对三维流场进行了实际计算。结果证明本文方法是正确的,能有效地均衡计算负载,达到较理想的并行效率。     

使用BP神经网络模型研究逆向卸荷膜片式减压器的稳定性能

采用数据挖掘中BP(back propagation)神经网络模型来研究逆向卸荷膜片式减压器的结构参数与稳定性能之间的依赖关系,得到结构参数变化,尤其是多结构参数耦合变化下减压器的稳定性结果.其中稳定性对阻尼孔直径、膜片刚度非常敏感,对弹性元件材料的阻尼系数、低压腔有效长度较为灵敏.由此提出减弱振荡的各种措施:增大阻尼孔直径、增大膜片刚度、在一定范围(标准值的6.5倍)内增大弹性元件材料的阻尼系数、增大低压腔有效长度、减小阀芯质量.数值实验误差分析表明:该模型不存在过拟合、局部最优的情况,其预测结果是可靠的,可为减压器的设计和系统分析提供决策支持.而且,该模型对不同类型的数据集具有通用性,可以用来研究其他部件的结构参数与性能指标的依赖关系.      

无线自组织网的可扩展性仿真

影响无线自组网可扩展性的因素很多,在随机移动模型和按需路由算法的前提下,提出了一个仿真模型,并利用NS2仿真工具对不同结点数组成的平面结构网络端到端时延和报文交付率进行了仿真,得出了AODV路由协议的可扩展性优于DSR协议的结论,并根据仿真结果推断出网络的规模不可能过大.     

非结构网格多区域动态加密及分布式并行计算

针对分布式并行系统,提出一种二维非结构网格多区域动态并行策略,可在计算过程中对各计算区域的网格进行局部自适应网格加密,可在不过多消耗计算机资源的情况下,快速,有效地实现多台同构计算机上的计算网格的动态负载平衡.并针对二维Euler方程,利用已有的高精度MmB有限体积格式,应用提出的并行计算策略,进行了多个数值试验,得到令人满意的效果.     

电能回馈型航空发电机测试用电子负载的研制

论述了一种用于航空发电机测试的电能回馈型电子负载的实现方案。这种电能回馈型电子负载采用电流滞环PWM技术,可实现功率因数无级调节,可模拟阻性、容性、感性等各种航空发电机负载形式,并通过三相逆变器将发电机发出的电能以功率因数1回馈给电网,降低了设备功耗,缩小了设备体积。采用Matlab进行了系统仿真,仿真结果验证了该方案的可行性。