Optimal phase searching of PTS using modified genetic algorithm for PAPR reduction in OFDM systems

In this paper,a novel genetic algorithm assisted partial transmit sequence(NGA-PTS)is proposed to reduce the peak-to-average power ratio(PAPR)of orthogonal frequency division multiplexing(OFDM).However,the search complexity of the optimum PTS(OPTS)scheme is too large for the typical number of sub-blocks.Therefore,some artificial intelligence methods,such as genetic algorithm technique,and particle swarm optimization,are introduced to reduce the complexity.As traditional GA-PTS(TGA-PTS)technique risks finding a suboptimal solution,how to avoid this disadvantage of TGA-PTS is an interest topic.In order to obtain a better suboptimal solution,a phase factor optimal pair technique and an abandon/introduction new chromosome technique are proposed in GA here.Simulation results show that the proposed scheme achieves a significant improvement over the TGA-PTS scheme in PAPR.Furthermore,by use of the inherent diversity of constellation for each OFDM candidate,in the receiver part,the proposed scheme enables data recovery without any side information.Simulation results show the efficiency of the proposed scheme.     

基于路由机制的变权网络路径快速生成算法

在大规模交通流仿真中,车辆个体路径生成环节存在着大量重复计算。为避免重复计算及提高车辆个体路径生成速度,将计算机网络中的路由机制引入到交通流仿真中,提出一种基于路由机制的变权网络路径快速生成算法,即把每个道路路口节点作为路由器,分解并存储原本与车关联的路径作为指路信息。仿真车辆通过访问该指路信息获取下一步行车方向,并且当路网权值发生变化时,能及时响应路网的动态变化,从而给出求实时路况下仿真车辆行驶路径的一种方法。     

Two memetic algorithms for heterogeneous fleet vehicle routing problems

The vehicle routing problem (VRP) plays an important role in the distribution step of supply chains. From a depot with identical vehicles of limited capacity, it consists in determining a set of vehicle trips of minimum total length, to satisfy the demands of a set of customers. In general, the number of vehicles used is a decision variable. The heterogeneous fleet VRP (HFVRP or HVRP) is a natural generalization with several vehicle types, each type being defined by a capacity, a fixed cost, a cost per distance unit and a number of vehicles available. The vehicle fleet mix problem (VFMP) is a variant with an unlimited number of vehicles per type. This paper presents two memetic algorithms (genetic algorithms hybridized with a local search) able to solve both the VFMP and the HVRP. They are based on chromosomes encoded as giant tours, without trip delimiters, and on an optimal evaluation procedure which splits these tours into feasible trips and assigns vehicles to them. The second algorithm uses a distance measure in solution space to diversify the search. Numerical tests on standard VFMP and HFVRP instances show that the two methods, especially the one with distance measure, compete with published metaheuristics and improve several best-known solutions.     

Route Maintenance in IEEE 802.11 wireless mesh networks

In this paper, we propose a novel Route Maintenance scheme for IEEE 802.11 wireless mesh networks. Despite lack of mobility and energy constraints, reactive routing protocols such as AODV and DSR suffer from frequent route breakages in 802.11 based infrastructure wireless mesh networks. In these networks, if any intermediate node fails to successfully transmit a packet to the next hop node after a certain number of retransmissions, the link layer reports a transmission problem to the network layer. Reactive routing protocols systematically consider this as a link breakage (and therefore a route breakage). Transmission failures can be caused by a number of factors e.g. interference or noise and can be transient in nature. Frequent route breakages result in significant performance degradation. The proposed mechanism considers multiple factors to differentiate between links with transient transmission problems from those links which have permanent transmission problems and takes a coherent decision on link breakage. The proposed mechanism is implemented in AODV for single-radio single-channel mesh network and an extension is incorporated in multi-radio multi-channel scenarios. Simulation results show substantial performance improvement compared to classical AODV and local route repair schemes.     

A planning model and solution algorithm for multi-trip split-delivery vehicle routing and scheduling problems with time windows

This study proposes a daily vehicle routing model for minimizing the total cost of replenishing inventory within a supply chain. The first major contribution of this research is to allow multiple use of vehicles in a split delivery vehicle routing problem with time windows (SDVRPTW), which is more realistic for various real-life applications. The multi-trip SDVRPTW (MTSDVRPTW) is formulated using the time–space network technique, which provides greater flexibility for formulating the complicated interactions between vehicles and products when multi-trip, split delivery, and delivery time windows are simultaneously considered. The resulting formulation of the MTSDVRPTW can be categorized as an integer multi-commodity network flow problem with side constraints. A two-step solution algorithm is proposed to solve this NP-hard problem, which is the second major contribution of this research. Finally, a real-world scale numerical example is performed to demonstrate and to test the methodology. The results indicate that these vehicle routing problems can be solved effectively and efficiently and that the proposed methodology has great potential for inventory replenishment scheduling where split deliveries and multiple trips for a single vehicle are allowed and time window constraints are imposed.     

一种多向链路感知的车载Ad Hoc网络传播协议

为了提高车辆自组织网络（Vehicular Ad Hoc Network,VANET）的数据传输效率,并使车辆间的数据通信能够持续进行,提出一种多向链路感知的车载Ad Hoc网络传播协议。为了保证车辆节点在执行通信任务的过程中实现数据的持续传输,防止通信链路频繁断连影响传输质量,提出了车辆网络的时间关联模型来讨论车辆间的速度差与通信持续时间的关系。为了缩短VANET中用于数据传输任务的总时间,协议基于改进蚁群的方法进行了多向链路感知,从而寻找在保证通信需求时间下的最短传输路径。实验结果分析表明,相比基于改进地理信息路由和基于优化链路状态路由的VANET数据传输算法,该算法的数据传输任务完工时间分别缩短了38.4%和27.3%,平均传输延迟分别降低了25.5%和12.1%。     

移动边缘计算环境下基于改进GPSR的VANET路由算法

针对车辆自组织网络(VANET,vehicular ad-hoc network)中现有路由协议存在的路由选择错误、丢包率较高、服务质量低等问题,提出了移动边缘计算环境下,结合改进贪婪周边无状态路由(GPSR,greedy perimeter stateless routing)和自适应链路质量评估的VANET路由算法;首先,结合边缘计算构建了VANET通信模型,对其车辆位置和速度进行系统的理论分析;将边缘计算架构应用于VANET能够有效缓解计算量大、与车辆有限且不均的资源分布之间的矛盾;然后,提出了基于节点移动速度和节点间距离的改进GPSR协议,通过自适应链路稳定性和链路传递速率评估来选择合适的中继节点,动态更新链路;通过SUMO仿真平台对路由算法的性能进行评估,实验结果表明,相对于其他算法,所提算法受车辆密度、交通流以及车辆相对速度的影响较小,且提高了分组传送率(车辆数为300时传送率达到92%),减少端到端延迟(交通流为5时延迟降低到1.5 s),从而降低了通信开销。     

IGR:面向车载网的基于地理信息的数据传输协议

由于车辆的高速移动和拓扑的动态变化,基于地理信息的数据传输协议被广泛应用于车载网.然而,现存的多数协议在路由决定时并没有考虑链路的质量,导致数据包丢失率升高,增加了传输时延.为此,提出了新的基于地理信息的数据包传输协议(IGR).IGR协议在路由决策时充分考虑车辆的移动方向、位置和链路质量3项信息.其中,利用beacon接收率体现链路质量.将这3项信息融合成节点权值.源节点择优选择权值高的节点作为下一跳转发节点.与同类协议相比,提出的IGR协议具有低的传输时延和高的传输率.     

Waste collection vehicle routing problem with time windows

In this paper, we address a real life waste collection vehicle routing problem with time windows (VRPTW) with consideration of multiple disposal trips and drivers’ lunch breaks. Solomon's well-known insertion algorithm is extended for the problem. While minimizing the number of vehicles and total traveling time is the major objective of vehicle routing problems in the literature, here we also consider the route compactness and workload balancing of a solution since they are very important aspects in practical applications. In order to improve the route compactness and workload balancing, a capacitated clustering-based waste collection VRPTW algorithm is developed. The proposed algorithms have been successfully implemented and deployed for the real life waste collection problems at Waste Management, Inc. A set of waste collection VRPTW benchmark problems is also presented in this paper.Waste collection problems are frequently considered as arc routing problems without time windows. However, that point of view can be applied only to residential waste collection problems. In the waste collection industry, there are three major areas: commercial waste collection, residential waste collection and roll-on-roll-off. In this paper, we mainly focus on the commercial waste collection problem. The problem can be characterized as a variant of VRPTW since commercial waste collection stops may have time windows. The major variation from a standard VRPTW is due to disposal operations and driver's lunch break. When a vehicle is full, it needs to go to one of the disposal facilities (landfill or transfer station). Each vehicle can, and typically does, make multiple disposal trips per day. The purpose of this paper is to introduce the waste collection VRPTW, benchmark problem sets, and a solution approach for the problem. The proposed algorithms have been successfully implemented and deployed for the real life waste collection problems of Waste Management, the leading provider of comprehensive waste management services in North America with nearly 26,000 collection and transfer vehicles.     

MF-DLB: Multimetric forwarding and directed acyclic graph-based load balancing for geographic routing in FANETs

Flying ad hoc network (FANET) comprising unmanned aerial vehicles (UAVs) emerges as a promising solution for numerous military and civil applications. Transferring data collected from the environment to the ground station (GS) is a primary concern for meeting the communication demands of most of these applications. However, the highly mobile UAVs with limited communication range, resulting in frequent topology change and intermittent connectivity, make data routing challenging. In such scenarios, geographic routing is a viable solution due to its scalability and robustness. However, the basic forwarding mechanism of geographic routing favors the neighboring UAV nearest to the destination, impacted substantially by link failures and routing holes in a dynamic environment. Additionally, routing decisions ignoring the current load over UAVs contribute to performance degradation due to the high concentration of data traffic near the GS. Thus, to address these issues, a geographic routing protocol named MF-DLB comprising multimetric forwarding (MF) and a directed acyclic graph-based load balancing (DLB) scheme is proposed to enhance packet forwarding in FANETs. MF takes account of multiple metrics related to connectivity, geographic progress, link lifetime, and residual energy to select the next hop with a stable communication link while effectively bypassing the routing holes. The second scheme, DLB, focuses on proactively maintaining routing paths near GS for load distribution among underutilized nodes to address the congestion problem. Simulations performed in network simulator ns-3 confirm the outperformance of MF-DLB over other related routing schemes in terms of different performance metrics.     

面向车载自组织网络路由的轨迹预测算法

在车载自组织网络(vehicular ad hoc network, VANET)(也称车联网)中,基于地理位置的路由协议能够较好地适应网络拓扑的动态性变化和链路质量的不稳定性.由于位置信息需要在邻居节点间采用信标分组进行交互,信标分组间隔内的转发决策可能因车辆节点位置的移动而不准确,需要进行位置预测来修正车辆节点的位置.已有的位置预测算法存在普适性差或预测误差大的问题.针对上述问题,提出了一种新的预测算法,首次通过测量得到车辆加速度服从正态分布的结论,利用线性回归进行预测,并采用反馈机制进行结果修正.利用真实车辆轨迹进行测试,新的预测算法的预测精度大为提高.然后,提出了一种新的基于位置的即时路由协议.在该协议中,发送节点利用邻居节点位置和目的节点位置计算出转发下一跳.将新的位置预测算法加入到即时路由协议中,实时预测和更新车辆的位置.利用SUMO软件生成了基于真实地图道路轨迹的车辆运动模型,结合NS3网络仿真平台进行了仿真实验.实验结果表明：采用新的预测算法后,相比传统的GPSR协议和不带预测的即时路由协议,新方法的收包率提高、延迟下降,并且协议开销显著降低.     

A link availability-based QoS-aware routing protocol for mobile ad hoc sensor networks

With more and more wireless devices being mobile, there is a constant challenge to provide reliable and high quality communication services among these devices. In this paper, we propose a link availability-based QoS-aware (LABQ) routing protocol for mobile ad hoc networks based on mobility prediction and link quality measurement, in addition to energy consumption estimate. The goal is to provide highly reliable and better communication links with energy-efficiency. The proposed routing algorithm has been verified by NS-2 simulations. The results have shown that LABQ outperforms existing algorithms by significantly reducing link breakages and thereby reducing the overheads in reconnection and retransmission. It also reduces the average end-to-end delay for data transfer and enhances the lifetime of nodes by making energy-efficient routing decisions.     

A Motion Planning Framework with Connectivity Management for Multiple Cooperative Robots

This paper proposes a decentralized motion planning algorithm for multiple cooperative robots subject to constraints imposed by sensors and the communication network. It consists of decentralized receding horizon planners that reside on each vehicle to navigate to individual target positions. A routing algorithm which modify the network topology based on the position of the robots and the limited range of transmitters and receivers, enables to reduce the communication link failures. A comparative study between the proposed algorithm and other existing algorithms is provided in order to show the advantages especially in terms of traveling time and communication link failure.     

城市车联网V2V链路时延动态预测

链路时延是决定车联网(vehicular ad hoc networks, VANETs)许多网络性能的重要标准.现存的VANETs基于节点移动性解决链路时延的问题,但是都没有预测的功能,不适合实际VANETs中动态预测车-车(vehicle to vehicle, V2V)链路时延.提出动态预测任意2车链路时延的数学模型DPLD,考虑2车相对速度分布、相对距离变化、交通密度和城市场景中交通灯因素对2车之间链路时延的影响,因为这些因素在链路连接过程中是变化的.通过考虑相对速度的分布,模型能够实时地调整原则自适应车速变化.通过自动调整2车之间相对距离计算方法,DPLD模型能够自适应2车间相对距离的变化.因此该模型能够有效地预测预期要发生的2车之间的链路时延.这个模型实现取决于相对速度分布参数的估计方法、指数移动平均法对车速异常处理以及交通灯对链路时延影响的概率建模并且详细给出2车遇到不同交通灯的具体链路时延预测方法.仿真结果表明:DPLD模型预测的城市环境的2车之间链路时延准确性很高.     

一种基于遗传算法的QoS多播路由算法

深入研究基于遗传算法的QoS多播路由算法,建立支持QoS的多播路由模型.对已有的QoS多播路由算法进行优化,提出适用于下一代网络的基于遗传算法的QoS多播路由算法.采用定长的染色体编码和预处理机制降低算法复杂度.仿真试验表明,该算法收敛速度快,可靠性高,能够更好地满足多播业务的需要.     

基于车流密度的VANETs路由协议

在节点高速移动的车载自组织网络(VANETs)中,道路交通状况极大地影响着网络中的数据传输性能。在贪婪周边无状态路由(GPSR)协议的基础上加以改进,提出了基于车流密度的VANETs由协议。考虑了车流密度以及节点运动速度、方向等影响因素,设计车流密度的计算方法,利用新的转发策略替代GPSR的贪婪转发策略,能够选择车流密度较好的路径进行数据转发,避免因车流密度分布不均匀而产生的局部最大现象。同时能够对由于节点高速运动引起的链路中断进行预测,提出有效的修复机制,从而建立链路稳健的VANETs路由。采用Matlab仿真平台进行仿真实验,与已有的GPSR,GPCR协议进行比较分析。仿真结果表明:提出的路由协议相比于其它2种路由协议在时延和分组转发率方面得到显著改善,性能优越,非常适合在城市场景中。     

自适应随机化链路状态路由算法

目前使用的两种IP路由算法－距离矢量和链路状态，都基于局域最优思想：每个路由器为其转发的包选择某种距离测试下的最短路径尽力发送，但是由于网络业务量具有无特征尺度的突发性，带宽资源经常可能处于相对稀缺的临界状态，在这种情况下，基于局域最优的路由策略通常并不对应于全局的最优，一个明显的例子是由局域最优算法所导致的路由振荡，提出的自适应随机化链路状态路由算法利用自适应随机化方法协调，限制各路由器的局域最优要求，有效地解决了路由振荡问题，仿真表明新算法显著提高了以包平均传输延迟和包丢失率为测度的网络的整体传输性能，此外，新算法的协调机制仍是局域性的，因而不显著地增加通信和计算开销。     

基于多描述编码和距离的车载网DSR路由技术研究

研究了车载自组网中基于多描述编码技术和车载节点间通信距离的按需路由DSR技术.针对车载自组网络拓扑的动态变化、车辆高速运动、车辆运行方向及其速度不可预知等特点,基于Ad Hoc网络按需路由协议DSR,研究了一种能较好地应用于车载自组网路由技术.该技术采用多描述编码技术和车载节点剩余能量改进了DSR的路由发现和回复过程....     

TinyOS路由协议原理及性能评估

LEPS是TinyOS的多跳路由协议,适用于数据聚集型传感器网络。LEPS路由建立一个以汇聚节点为根节点的树型拓扑,每个节点向自己的父节点发送传感数据,并沿最短路径传送到汇聚节点。LEPS协议将跳数和链路质量作为选择父节点的依据,具有一定的传输可靠性保证。该文对LEPS的原理以及在TinyOS中的实现机制进行了分析,在实际的传感器网络中进行了性能实验。LEPS路由协议可以形成并维护一个树型拓扑,但是节点间链路不够稳定,拓扑变化比较频繁。     

A network transformation heuristic approach for the deviation flow refueling location model

In the early stages of development, alternative-fuel vehicles will tend to have shorter driving ranges than conventional vehicles, and the availability of stations will be limited. Given these conditions, it is important to consider the willingness of drivers to deviate to some extent from their shortest paths in order to refuel their vehicles and complete their trips. Previously, we proposed the deviation-flow refueling location model (DFRLM) for locating a given number of refueling facilities to maximize the total alternative-fuel vehicle flows that can be refueled by drivers traveling on or deviating from their shortest paths. On a real-world problem, however, the large number of possible deviations from each path and of combinations of facilities that can cover each path would make it extremely difficult to generate and solve the mixed-integer formulation. This paper develops heuristic algorithms for the DFRLM that overcome this difficulty through network transformation. Specifically, a greedy heuristic constructs and edits an artificial feasible network in which each node represents a station, origin, or destination, and each arc represents a feasible path between two nodes given the assumed driving range of vehicles. At each step of the greedy and greedy-substitution algorithms, the feasible network is edited and a shortest path algorithm is run, which determines whether each origin–destination round trip can be completed. This method allows any possible detour to be taken (up to some user-defined maximum) while also ensuring that drivers take the smallest possible detour. Computational experiments on a simple network and a real-world network for Florida show the heuristics to be efficient in solving the problems. Comparisons between the results of the DFRLM and the FRLM indicate that taking driver deviations into account in the model can have a significant effect on the locations chosen and demand covered.