自组网Random Direction移动模型点空间概率分布的研究

在无线自组网的研究中，研究移动模型点的空间概率分布是研究自组网协议的仿真评价和分析移动自组网许多相关特性(例如网络连通性、最小生成树、平均路径长度、网络容量等)的重要的基础问题．针对自组网经常使用的Random Direction移动模型运动节点的空间分布进行了研究，给出了一维及二维情况下运动节点空间概率分布的精确公式．研究结果为基于Random Direction移动模型的证明、仿真与应用提供了严格的理论依据．     

基于Bezier曲线的移动模型研究

现有的移动模型大多采用简单的、随机的直线运动来描述物体的移动模式,难以描述现实场景下规避障碍物的曲线移动模式.为解决现有移动模型存在的这些问题,提出一种基于Bezier曲线的移动模型.首先从理论上对该模型的应用进行了详细分析,其次提出了曲线场景下的节点概率分布的分析模型和算法,最后从多个场景进行了仿真验证和比较分析.研究结果表明,与典型的Random Waypoint模型相比,该模型不但可描述移动自组网在有障碍物约束的普遍现实应用场景,而且在同样的场景下具有更优的节点概率分布,使移动自组网表现出良好的动态特性,因此可为移动自组网的仿真研究提供现实的应用场景.     

基于圆周运动的自组网移动模型研究

自组网仿真研究大多基于特定的移动模型,而移动模型中节点空间概率分布是研究和评价自组网性能的理论基础.然而,现有的自组网移动模型存在诸多缺陷(如不现实的移动场景、节点的非均匀分布等).在分析和比较现有移动模型的基础上,提出一种基于圆周运动的移动模型,推导出移动节点的二维概率密度函数公式.理论分析和仿真实验表明,该模型能够克服现有移动模型的这些缺陷,为仿真和评估自组网的性能提供了精确的理论模型.     

一种避免Random Waypoint移动模型速度衰减的方法

在被广泛使用自的Random Waypoint移动模型中，随着模拟的进行节点平均速度呈下降趋势．这样自々速度衰减现象对自组网等移动系统的某些时间平均性能评价是不利的。会增加精确分析的复杂性；以结点平均速度在整个模拟过程中保持稳定为前提而得到的试验结论也是不可靠的．本文对速度衰减现象进行了概率分析并证明了它是不可避免的，最后提出了改进的Random Waypoint移动模型iRWP，试验验证iRWP能有效避免了速度衰减的发生．     

基于NS2的规定轨迹的运动模型的实现与性能分析

该文基于仿真工具NS2在随机路点模型RWP(Random Waypoint Protocol)之上探讨了一种MANET环境下节点可沿规定轨迹移动的新的运动模型,对其主要思想及生成方法进行了较细致介绍,并通过仿真实验对其性能进行了评估和分析。     

机器人自组网的运动控制模型仿真研究

机器人自组网具有较高的军事和民用价值;基于机器人通用运动学模型,对传统自组网的节点运动模型——随机路点和随机方向移动模型进行了修改,为机器人自组网中的节点建立了运动控制模型,并建立了机器人自组网的网络模型,对几种运动模型进行了仿真分析;结果表明,在机器人自组网的仿真场景中网络性能有所恶化;达到了较为真实地仿真机器人自组网的目的,得出的结论对机器人自组网的仿真研究具有一定的参考价值。     

具有多出入口区域的节点移动和分布研究

在Ad Hoc网络的仿真研究中,节点移动模型的选择会严重影响到网络的拓扑结构和通信协议的性能.然而,现有移动模型大多是为理想环境设计的,不能适用于真实环境.在理想移动模型RWP(Random Waypoint)的基础上,提出了具有多出入口区域的RWP节点移动模型(RWP with entrances,RWPWE).在该模型中,区域出入口是节点进出区域的必经之地,节点在区域内的移动符合RWP节点移动模型,通过引入域内停留概率来完成节点在区域内外移动的转移,并从节点移动速度、移动时间、移动路程和空间分布概率等几个方面研究了区域出入口的影响.理论分析和实验仿真的结果表明,由于出入口的存在,与RWP模型相比节点的移动更加复杂,节点的空间分布也显著不同,这些差别将会影响到网络的拓扑性能和对网络协议的评价.     

移动自组网病毒传播模型及稳定性分析

考虑移动自组网中节点的移动特性,基于平均场理论提出移动自组网中病毒传播模型,并对建立的方程组进行平衡点存在性和稳定性分析,得出病毒传播的阈值及消亡条件,从而研究节点移动速度、通信半径、免疫成功率和免疫失效率对移动自组网中病毒传播行为和传播临界特性的影响。结果表明:当病毒基本再生数R0<1时,网络全局渐近稳定在无病毒平衡点;当R0>1时,网络全局渐近稳定在地方病平衡点。最后通过数值仿真验证了该模型的正确性。     

基于反弹成簇策略的自组织网络组网模型

提出一种基于反弹成簇和簇合并策略的自组织网络组网模型。借鉴物理学中光的反射原理,确定网络节点的移动方向,实现分布式组网的目标。采用基于细胞自动机的模拟方法分析该模型的组网性能。实验结果表明,与Random Waypoint模型相比,该模型在组网速度方面有明显优势。     

基于行动预测的支持移动自组网QoS的路由方案

从研究高斯-马尔可夫运动模型出发，提出了一个可用于预测移动自组网中节点间最大链路有效时间的模型。从提供Qos路由度量和改进被动路由协议两个方面阐述了提供移动自组网Qos支持的机制。仿真实验表明，新的路由方案具有网络吞吐量大、抖动小和时延可控制的特点。     

随机停留点移动模型下AODV路由协议性能仿真

随机停留点移动模型是无线自组网协议性能仿真中常见且广泛使用的移动模型,在仿真过程中存在节点平均移动速度衰减和节点空间分布边界效应问题.讨论分析了造成问题的主要原因,并给出避免节点平均移动速度衰减的方案.最后通过设置不同的节点最大移动速度和节点停留时问这两个移动参数,借助NS-2仿真分析了AODV路由协议性能的变化.仿真结果表明,节点移动速度的变化对AODV路由协议性能影响大,停留时间越长、移动速度越慢,AODV路由协议的分组投递率越大、分组端到端平均传输延时越小.     

A novel mobility model based on semi-random circular movement in mobile ad hoc networks

When simulating a mobile ad hoc network (MANET), it is important to use a realistic mobility model to reflect the actual performance of a mobile system. The spatial distribution of node locations in a mobile model plays a key role when investigating the characteristics of a MANET. However, most existing mobility models with random and simple straight line movement lead to unrealistic scenarios and non-uniform distributions, and can not describe the actual movement of Unmanned Aerial Vehicles (UAVs) connected via a MANET. To address this issue, a novel mobility model based on semi-random circular movement (SRCM) is presented. The approximate node distribution function in SRCM is derived within a 2D disk region. The relationship between application performance and node distribution is investigated for a UAV MANET, with focus on scan coverage and network connectivity. A simulation using the NS2 tool is conducted. It is shown that the presented model with a uniform distribution performs better than the popular Random Waypoint mobility model. The SRCM model with the NS2 simulator provides a realistic way for simulation and performance evaluation of UAV MANETs.     

适用于VANET仿真的车辆合成运动模型

车载自组网(VANET)是移动Ad Hoc网络技术在交通领域的应用,已成为智能交通系统一项非常有前景的技术.准确反映节点运动方式的运动模型对于提高仿真实验准确性至关重要.首次利用了实际的卫星地图信息,在考虑实际道路环境特点基础上实现了新的节点运动模型--车辆合成运动模型,将该模型与随机路点模型和曼哈顿模型进行了对比,并在根据西安城区卫星地图构建的仿真场景中分别采用3种节点运动模型,利用QualNet仿真平台评估了不同节点运动模型对路由协议性能的影响.结果表明,节点运动模型对协议性能影响很大,分析认为合成运动模型更适合于VANET仿真研究.     

Smooth movement and Manhattan path based Random Waypoint mobility

In this paper, we study the stationary node distribution of a variation of the Random Waypoint mobility model, in which nodes move in a smooth way following one randomly chosen Manhattan path connecting two points. We provide analytical results for the spatial node stationary distribution of this model. As an application, we exploit this result to derive an upper bound on the transmission range of the nodes of a MANET, moving according to this model, that guarantees the connectivity of the communication graph with high probability.     

Bio-inspired group mobility model for mobile ad hoc networks based on bird-flocking behavior

In this paper, we propose a novel group mobility model for mobile ad hoc networks (MANETs), named as Bird-Flocking Behavior Inspired Group Mobility Model (BFBIGM), which takes inspiration from the mobility of a flock of birds, flying in a formation. Most existing modeling techniques are deficient in successfully addressing many aspects in terms of the application of realistic forces on the movement of mobile nodes (MNs), the interaction of MNs within a group, and collision avoidance within a group and with environmental obstacles. The results obtained through experiments show that in terms of connectivity metrics, such as link duration, BFBIGM performs around 50% better in comparison to the popular existing mobility models like Random Waypoint (RWP) Model (Johnson et al. in Ad hoc networking, Addison-Wesley, Menlo Park, pp. 139–172,2001) and the Reference Point Group Mobility (RPGM) Model (Hong et al. in: Proceedings of the 2nd ACM international workshop on modeling, analysis and simulation of wireless and mobile systems, Seattle, WA, pp. 53–60,1999).     

Applying location estimation for reliable routing in tactical unmanned ground vehicle networks

An unmanned ground vehicle (UGV) network operates as an ad hoc autonomous tactical network. In this paper, we study the deployment of a UGV network and its ability to use location estimation to provide reliable data forwarding. This analysis involves (1) location estimation to obtain realistic estimates of the node’s (UGV) spatial positions and (2) real-time path planning to obtain reliable routing among nodes using the estimates of the node positions. Conventional approaches commonly use the popular Random Waypoint (RWP) model (or its variants) as the mobility model. The RWP approach uses randomly selected node positions and has no way to cope with nodes moving in and out of transmission range. These deficiencies cause the route reliability to suffer. Our approach (1) uses an Extended Kalman Filter (EKF) for node mobility/location estimation and (2) uses a modified Ad Hoc On Demand Distance Vector (AODV) algorithm for route selection using a new routing parameter called contact time. We refer to this combined approach as the AODV-LocPred algorithm. We compare the AODV-LocPred algorithm with AODV using the RWP model. This is referred to as AODV-RWP. Our simulations show that the AODV-LocPred algorithm significantly outperforms the AODV-RWP algorithm in terms of packet delivery ratio (PDR), because it provides realistic node position estimates and it copes in a reasonable way with nodes moving in and out of transmission range. However, the AODV-LocPred incurs an increase in end-to-end delay. Nonetheless, we expect that in many real-world settings, this tradeoff is acceptable.