智能变电站站级网络的实时仿真研究

基于OPNET软件,对220kV中等规模智能变电站站级网络进行建模.利用OPNET的客户机/服务器模型来模拟站级网络通信报文的端到端传输,并且在报文不同大小和发送间隔、不同CPU利用率以及采用不同传输协议的情况下,对站级网络的实时性进行仿真研究.结果显示:随着数据包大小从64bytes递增至2 048bytes,端到端延时由0.2 ms增加到了3 ms;随着数据包发送间隔从0.02s递增至3s,端到端延时由1.2ms增加到了1.75ms;随着CPU利用率从10%递增到90%,端到端延时由0.03ms增加到0.2ms;采用UDP协议的延时比TCP协议的延时要小0.02ms左右.有效论证了影响报文传输实时性的因素,为网络设备参数有效配置提供参考.     

自组网中一种可靠的层次路由协议

针对自组网中基于多层有中心分级结构(MCHS)的分级状态路由(HSR)协议存在结构稳定性差、结构维护开销大、可靠性不高和丢包问题严重等问题,提出一种可靠的层次路由协议(RHRP)。它基于一种新的多层无中心分级结构(MCLHS),该结构采用无中心策略,有利于提高结构稳定性和降低结构维护开销,并能进一步提高可靠性和降低路由开销。RHRP采用"高层虚拟链路以群为构成元素"的策略,使高层虚拟链路更稳定,有利于提高可靠性。更稳定的结构和高层虚拟链路可以减少丢包数目和重路由次数,从而降低传输时延和路由开销。通过分析路由可靠度,从理论上证明了RHRP的可靠性较高。通过仿真评价RHRP和HSR的性能,结果表明,RHRP在投递率、平均端到端时延和路由开销等指标上都优于HSR。     

基于移动平台的文件传输策略的设计和实现

提出了一种基于移动平台的文件可靠传输策略:发送节点采用与接收节点约定好的协议将文件内容按特定的长度进行分包,按特定的字段进行组包,按特定的数量进行分组;发送节点每传输一组数据包后都进行丢包的及时检查,只有等到接收节点接收了该组的全部数据包后才允许发送下一组数据包,直到所有数据包发送完毕;在传输过程中采用循环冗余校验(CRC)码对每个数据包进行校验,传输结束后采用哈希算法对整个文件的完整性进行校验,以增加文件传输的可靠性。实验结果表明,该文件传输策略能够同时减小链路开销、丢包率和传输时间。     

基于动态电路的高速发送端设计

为了降低高速串行接口中发送端的延迟,在研究、分析现有发送端结构的基础上,提出了新的数据跨时钟域传输方法并在实际电路中得到实现。此方法可以大幅降低数据跨时钟域传输时用于异步FIFO的延迟。而且,使用动态电路对高速发送端并串转换电路进行了晶体管级的改进,放松了关键路径的时序要求,使发送端整体电路能运行在更高的频率下。发送端电路使用40nm CMOS工艺实现,实际芯片测试数据表明,使用该电路的发送端可以稳定工作在13Gb/s的速率下。     

基于消息调度和喷射等待的车载容迟网络路由算法

车载容迟网络具有间歇性、快速移动的特点,其拓扑结构复杂.车载容迟网络路由协议中,消息在节点间如何有序高效地传输是一个重要问题.根据节点间的传递方式和传递依据,提出了一种基于消息调度和喷射等待的车载容迟网络路由算法MSSW(Vehicle Delay-tolerant Network Routing Algorithm Based on Message Schedule and Spray Wait):采用增量平均的方法,改进投递预测概率的相遇更新公式;采用增强型的方法,改进投递预测概率的衰减更新公式;采用消息调度为动态阈值区分的跳数优先级排序和开销优先级排序机制;传递方式为基于副本控制的喷射和等待两个阶段,喷射阶段采用二叉树的方式传递,以实现多路径转发,等待阶段采用直接传输路由的方式传递;同时加入ACK确认机制.仿真结果表明,本算法能提高投递率,降低网络开销,有效地控制平均时延.     

基于路径到达率和动态广播时延的汇聚树协议

汇聚树路由协议(CTP)是目前无线传感器网络(WSN)中常用的数据采集路由协议。它是基于期望传输次数(ETX)的树型路由协议。但对多跳路径的衡量,简单的ETX相加往往无法良好刻画实际路径质量,致使该协议很难选出最优路径。本文提出了基于端到端的数据到达率(PDR)的CTP改进协议,能更好地衡量多跳路径的网络质量。据此选出的最优路径能构建更优的汇聚树,提高端到端数据传递的成功率,减少平均传递次数和平均传递时间,这样可以节省能耗,提高网络生存时间。同时,本文提出在建树过程中采取动态时延广播策略,可以有效减少建路由树时的广播次数,节省开销。     

基于随机学习的异构蜂窝网络离散功率控制机制

针对宏基站和低功率小基站重叠覆盖共享频谱的异构网络中干扰抑制问题,提出了一种基于随机学习理论的基站下行离散功率控制机制,以便在保证宏基站传输的最低传输质量要求下,最大化网络满足传输质量要求的小基站传输个数。该方法将每个小基站作为随机学习自动机,维持一个概率向量用于传输功率选择。算法迭代过程中,小基站独立地基于自身选择的传输功率以及网络反馈的信息,即满足传输质量要求的小基站传输的个数,来更新概率向量,调整传输功率,直到系统达到均衡状态。仿真结果表明,基于随机学习的离散功率控制方法具有很好的收敛性和寻优性能,能有效提高系统可支持的满足传输质量要求的小基站传输数量,适用实际系统。     

基于统计性QoS保证的数据包延时界调度算法

讨论了调度算法的性能指标，对目前基于业务流的调度算法的技术特点与性能优劣进行了分析和比较．重点研究了基于时延和丢包率的算法，并提出了一种基于数据包延时界（PDB）排列的调度策略，与WFQ及传统EDF算法进行了比较，证明业务端到端超时概率随网络带宽利用率的变化性能优于传统EDF算法．     

一种高效的LEO卫星星座路由算法

针对由小卫星组成的低地球轨道(LEO)卫星星座网络的星上计算能力和存储资源有限,以及传统的星座路由算法虽能很好地适应网络的动态性但对星上计算能力和存储资源的要求都较高的问题,在基于对实际LEO卫星星座网络充分分析的基础上,提出了一种基于离线计算的简洁高效的路由算法.该算法在保证路由有效性的前提下,能够通过使用备份路径来提供流量自适应机制.复杂性分析和仿真结果表明,该算法只需较小的星上存储开销和星上处理开销,而且具有较好的端到端时延性能.该算法简洁、高效的特点使其能作为实际LEO卫星星座网络的实用化路由协议.     

多用户协同无线网络中的中继选择的研究

针对多用户协同无线网络中的中继选择问题,提出了两种基于不同系统开销的半分布式中继选择算法。这两种算法以中断概率为优化目标,充分利用多用户协同无线网络的特点,以较低的系统开销和计算复杂度获取使系统中断概率达到最小的中继选择问题(指派问题)的次优解。仿真结果表明,两种算法均可以较好地逼近中断概率性能的下界,并保证用户公平性,而算法2以较大的系统开销换取优于算法1的容量性能。提出的两种半分布式算法在性能和系统开销之间获得了较好的折衷,可以大幅简化中继选择在实际无线通信系统中的应用,尤其适用于稠密人口地区的应用。     

一种新的基于移动预测的MANET路由协议

移动自组网是一种由一系列可以自由移动的节点主机聚集而成的一个临时性动态网络。它没有固定基站，也没有作为控制管理中心的节点主机，由于其拓扑的动态性，其路由协议与其他传统网络有很大的区别。为了能更有效地移动自组网中实现数据的传送，本文提出了一种基于移动预测下的MANET路由协议，该协议综合考虑了传输路径的延时和稳定性，选择在延时限制下平均拥有最稳特性的传输路径，模拟结果表明，这种方法比基于移动预测量稳路径路由协议的传输时延要短，传送成功概率要高，而控制开销却相关不大。     

RFID Based Non-Preemptive Random Sleep Scheduling in WSN

In Wireless Sensor Network (WSN), because battery and energy supply are constraints, sleep scheduling is always needed to save energy while maintaining connectivity for packet delivery. Traditional schemes have to ensure high duty cycling to ensure enough percentage of active nodes and then derogate the energy efficiency. This paper proposes an RFID based non-preemptive random sleep scheduling scheme with stable low duty cycle. It employs delay tolerant network routing protocol to tackle the frequent disconnections. A low-power RFID based non-preemptive wakeup signal is used to confirm the availability of next-hop before sending packet. It eliminates energy consumption of repeated retransmission of the delayed packets. Moreover, the received wakeup signal is postponed to take effect until the sleep period is finished, and the waken node then responds to the sending node to start the packet delivery. The scheme can keep stable duty cycle and then ensure energy saving effect compared with other sleeping scheduling methods.     

Mobile agent based approach for QoS routing

A mobile agent based on-demand quality of service (QoS) unicast routing scheme for supporting multimedia applications is proposed that considers bandwidth, delay and packet loss as QoS metrics for feasible path computation. A mobile agent is employed to find multiple QoS paths and select a best path among them to preserve resources so as to increase call success ratio and network bandwidth utilisation as well as adapt to network dynamics. The scheme is simulated in various network scenarios (sparse and dense networks) to verify performance and operation effectiveness, and compared with RSVP-based QoS routing by using an internet routing protocol. The results demonstrate significant improvements in call success ratio and network bandwidth utilisation compared with RSVP-based QoS routing, both in case of sparse and dense networks. Benefits of the agent-based scheme are adaptability, flexibility, and support for component-based software engineering features such as software reuse, customisation and maintainability     

Q-Learning Based Routing Protocol for Congestion Avoidance

The end-to-end delay in a wired network is strongly dependent on congestion on intermediate nodes. Among lots of feasible approaches to avoid congestion efficiently, congestion-aware routing protocols tend to search for an uncongested path toward the destination through rule-based approaches in reactive/incident-driven and distributed methods. However, these previous approaches have a problem accommodating the changing network environments in autonomous and self-adaptive operations dynamically. To overcome this drawback, we present a new congestion-aware routing protocol based on a Q-learning algorithm in software-defined networks where logically centralized network operation enables intelligent control and management of network resources. In a proposed routing protocol, either one of uncongested neighboring nodes are randomly selected as next hop to distribute traffic load to multiple paths or Q-learning algorithm is applied to decide the next hop by modeling the state, Q-value, and reward function to set the desired path toward the destination. A new reward function that consists of a buffer occupancy, link reliability and hop count is considered. Moreover, look ahead algorithm is employed to update the Q-value with values within two hops simultaneously. This approach leads to a decision of the optimal next hop by taking congestion status in two hops into account, accordingly. Finally, the simulation results presented approximately 20% higher packet delivery ratio and 15% shorter end-to-end delay, compared to those with the existing scheme by avoiding congestion adaptively.     

Performance evaluation of shortest multipath source routing scheme

Multipath routing in mobile ad-hoc networks allows the establishment of multiple paths for routing between a source-destination pair. It exploits the resource redundancy and diversity in the underlying network to provide benefits such as fault tolerance, load balancing, bandwidth aggregation and the improvement in quality-of-service metrics such as delay. Previous work shows that on-demand multipath routing schemes achieve better performance under certain scenarios with respect to a number of key performance metrics when compared with traditional single-path routing mechanisms. A multipath routing scheme, referred to as shortest multipath source (SMS) routing based on dynamic source routing (DSR) is proposed here. The mechanism has two novel aspects compared with other on-demand multipath routing schemes: it achieves shorter multiple partial-disjoint paths and allows more rapid recovery from route breaks. The performance differentials are investigated using NS-2 under conditions of varying mobility, offered load and network size. Results reveal that SMS provides a better solution than existing source-based approaches in a truly mobile ad-hoc environment.     

基于位置信息的水声传感器网络路由协议

由于水下环境与地面环境不同,无线传感器网络中的协议不能直接应用于水下传感器网络中。针对水下环境的特点,提出了一种适用于水下传感器网络的路由协议。它是一种可扩展的、能量高效的路由协议。仿真结果显示:网络节点的移动速率不是很大时,该协议具有能量利用率高、数据传输成功率高和传输延时低等优点。     

A comparative QoS survey of mobile ad hoc network routing protocols

A mobile ad hoc network (MANET) is a wireless, dynamic, infrastructure-less, self-organized, multi-hop, and decentralized network. Each node in MANET can act as a router as well as a work station. Many routing protocols have been developed to increase the efficiency of MANET. The primary objective of this paper is a detailed QoS comparison of reactive (AODV), proactive (DSDV), and hybrid (ZRP) routing protocols of MANET in order to find which routing protocol works best in a particular network scenario. The analysis was made for TCP-based traffic patterns. The performance differentials were analyzed on the basis of normalized routing overhead, packet loss, packet delivery ratio, control packets, end-to-end delay, packet received, and packet sent with a variation of nodes density and mobility. The results were obtained using the NS-2 simulator.     

随机需求下半开放式冷链物流车辆路径优化

目的 降低冷链物流配送成本的同时,保证客户体验及碳排放达到企业要求。方法 综合考虑运输距离、客户软时间窗约束、碳排放、生鲜变质等因素,以制冷成本及对配送时间惩罚成本在内的总成本最低、碳排放量最低、生鲜产品新鲜度最高为目标,建立多目标生鲜配送路径优化模型,并设计模拟退火算法,以北京某冷链物流企业为例进行求解验证。结果 得出生鲜配送方案,通过配送模式对比表明多中心半开放式在降本和缩短路径长度方面更具优势,其中运输总费用和车辆行驶总距离相比于单中心独立配送模式分别降低了8.41%和36.36%。结论 需求不确定下,合理决策路由可在达到企业对生鲜产品新鲜度及碳排放标准的同时,有效降低配送成本。     

The QKD network: model and routing scheme

Quantum key distribution (QKD) technology can establish unconditional secure keys between two communicating parties. Although this technology has some inherent constraints, such as the distance and point-to-point mode limits, building a QKD network with multiple point-to-point QKD devices can overcome these constraints. Considering the development level of current technology, the trust relaying QKD network is the first choice to build a practical QKD network. However, the previous research didn’t address a routing method on the trust relaying QKD network in detail. This paper focuses on the routing issues, builds a model of the trust relaying QKD network for easily analysing and understanding this network, and proposes a dynamical routing scheme for this network. From the viewpoint of designing a dynamical routing scheme in classical network, the proposed scheme consists of three components: a Hello protocol helping share the network topology information, a routing algorithm to select a set of suitable paths and establish the routing table and a link state update mechanism helping keep the routing table newly. Experiments and evaluation demonstrates the validity and effectiveness of the proposed routing scheme.     

自组网中一种基于跨层负载感知的蚁群优化路由协议

将蚁群优化和跨层优化方法结合起来,提出了一种基于跨层负载感知和蚁群优化的路由协议(CLAOR)。协议将整个路径中各节点MAC层的总平均估计时延和节点队列缓存的占用情况结合起来,共同作为路由选择和路由调整的重要度量标准进行按需路由发现和维护,通过拥塞节点丢弃蚂蚁分组以及借助部分兼具蚂蚁功能的数据分组实现正常路由表的维护等方法,减少了控制开销,增加了算法的可扩展性,较好地解决了自组网中现有基于蚁群优化的路由协议中普遍存在的拥塞问题、捷径问题和引入的路由开销问题。仿真结果表明,CLAOR在分组成功递交率、路由开销以及端到端平均时延等方面具有优良性能,能很好地实现网络中的业务流负载均衡。