机会式网络中节点移动模型的研究与实现

针对随机路点移动模型中节点移动趋势是随着时间推移远离边界区域,从而导致网络节点稳态分布不均匀,以及在均匀移动模型中很难选取最佳μ值等问题.提出一种节点在每一移动周期移动距离服从与网径参数有关的均匀分布的移动模型.实验结果表明,网络的分组投递率得到了提升,同时减小了网络时延和路由开销.     

有效的Ka波段移动卫星信道综合模型研究

为了更加准确地描述卫星移动通信信道的衰落特性,提出了一种新的Ka波段卫星移动通信信道综合模型。首先在分析移动卫星信道传播特性的基础上,考虑多径衰落、阴影遮蔽及天气影响等因素,建立了服从Gaussian分布的大气空间模型,推导出服从Rice、Rayleigh和Lognormal联合分布的地面信道模型。然后利用卫星信道环境中大气空间部分与地面部分对信道特性的影响是彼此相互独立的性质,提出了一种在大气空间持续影响下的移动卫星信道衰落特性综合模型。并就不同天气条件和不同阴影遮蔽程度下,综合模型的误码率特征与系统误码率理论上限进行仿真对比,得出了相一致的结果,验证了该信道综合模型的合理性和正确性。     

TD-LTE应急通信中的改进型节点移动模型研究

基于TD-LTE的应急通信系统能够在灾难发生后快速组网,为及时救援提供宝贵信息,而合适的节点移动模型是自组网路由算法的基础。文章通过分析应急场景中移动基站的运动特性,提出一种基于区域稳态分布的改进型随机路点移动模型。该模型能够缓解RWP模型稳态分布不均、节点速度逐渐衰减以及节点重复无效率运动的问题,有利于模拟应急通信中移动基站的运动情况以及后续Ad Hoc路由协议的仿真。     

无线自组网个体移动模型分析

应用Palm积分分析随机点模型、随机方向模型和随机游走模型的平稳速度分布,证明速度衰减问题源于各个移动周期内速度和持续时间的相关性.应用Palm积分和几何概率分析随机点模型和随机方向模型的平稳节点分布,证明这2种模型具有非均匀节点分布特征.应用中心极限定理证明无边界区域随机游走模型的轨迹端点成正态分布.结果表明时间型随机游走模型是最合理的个体移动模型.     

基于量化状态积分的空间目标温度计算

为了加速空间目标温度计算,提高空间目标红外仿真速度,提出了基于量化状态积分的离散形式热平衡方程求解方法,利用节点方程中不同节点温度变化速度不同的特点,动态调节节点方程的计算量.构造节点方程与节点变量及输入向量分量关系链表,利用模型中方程与变量关系的稀疏性简化计算.根据空间目标温度计算有限元模型的一般形式,在对角化热容矩...     

基于边生命周期的短波IP网络随机图模型

针对短波IP网络中物理连接存在生命周期和接收节点选择方式不同对网络拓扑结构和性能产生的影响,提出了一种基于边生命周期和接收节点多种选择方式的随机图模型。模型中节点之间边生命周期服从正态分布,而新边建立的节点选择方式按照随机选择、度值择优选择和度值反择优选择的方式,用来模拟短波IP网络不同的通信过程。理论分析和仿真也发现,接收节点选择方式的不同将会对网络的度分布、平均最短距离、网络总的度值和节点最大度值及聚集系数都产生影响,而小的连接生命周期将显著减少网络中总的度值和节点的最大度值,减少对物理层资源的占用,提升网络的效能。     

基于改进粒子群算法的Ad Hoc网络移动模型研究

 移动模型是研究ad hoc网络路由算法的基础.为解决基本粒子群算法的速度突变问题,使其适用于ad hoc网络移动模型,本文首先在基本粒子群算法的速度和位移更新公式中引入加速度和环境因子的概念,并提出用直角坐标系对其速度和位移进行分解.接着,我们建立了包含障碍物模型、速度初始化函数和无边界仿真区域的改进粒子群算法移动模型.为证实新移动模型的可行性和有效性,我们用Matlab和网络仿真软件OPNET进行仿真实验.结果表明,与传统的随机位点移动模型比较,基于改进粒子群算法的移动模型更贴近实际情景,并能够有效地应用在ad hoc网络中.     

移动自组网上结构化P2P网络Churn问题分析

分析研究了在三种用户行为的指数分布模型、Pareto分布模型和Weibull分布模型下,Churn问题对移动自组网上结构化P2P网络性能的影响.仿真实验研究表明,影响结构化P2P网络在移动自组网上工作性能的主要因素是节点会话时长、网络规模和节点密度、网络层路由协议以及节点移动性,并分析了这些主要因素之间的相互关系.     

电热微执行器温度分布节点分析模型

针对如何使用具有集总性质的节点分析法仿真非集总的温度分布这一难点问题,本文以平面内运动的热执行器作为研究对象,依据不同坐标的空间温度分布之间相关性较强的特点,利用傅里叶变换使连续的空间温度分布问题集总化,建立了热执行器基本单元的温度分布节点分析法模型.所建立的模型节点数较少,结构清晰.同时为使之能够与控制电路及反馈电路协同仿真,本文还建立了热执行器基本单元的等效电路模型.为证实模型的有效性,本文使用该模型对三种常见的平面内运动热执行器加以分析,由ANSYS验证了其仿真结果的正确性.     

电热微执行器温度分布节点分析模型

针对如何使用具有集总性质的节点分析法仿真非集总的温度分布这一难点问题,本文以平面内运动的热执行器作为研究对象,依据不同坐标的空间温度分布之间相关性较强的特点,利用傅里叶变换使连续的空间温度分布问题集总化,建立了热执行器基本单元的温度分布节点分析法模型.所建立的模型节点数较少,结构清晰.同时为使之能够与控制电路及反馈电路协同仿真,本文还建立了热执行器基本单元的等效电路模型.为证实模型的有效性,本文使用该模型对三种常见的平面内运动热执行器加以分析,由ANSYS验证了其仿真结果的正确性.     

A framework for modeling spatial node density in waypoint-based mobility

User mobility is of critical importance when designing mobile networks. In particular, "waypoint" mobility has been widely used as a simple way to describe how humans move. This paper introduces the first modeling framework to model waypoint-based mobility. The proposed framework is simple, yet general enough to model any waypoint-based mobility regimes. It employs first order ordinary differential equations to model the spatial density of participating nodes as a function of (1) the probability of moving between two locations within the geographic region under consideration, and (2) the rate at which nodes leave their current location. We validate our model against real user mobility recorded in GPS traces collected in three different scenarios. Moreover, we show that our modeling framework can be used to analyze the steady-state behavior of spatial node density resulting from a number of synthetic waypoint-based mobility regimes, including the widely used Random Waypoint model. Another contribution of the proposed framework is to show that using the well-known preferential attachment principle to model human mobility exhibits behavior similar to random mobility, where the original spatial node density distribution is not preserved. Finally, as an example application of our framework, we discuss using it to generate steady-state node density distributions to prime mobile network simulations.     

A unified mobility model for analysis and simulation of mobile wireless networks

We propose a novel mobility model, named Semi-Markov Smooth (SMS) model, to characterize the smooth movement of mobile users in accordance with the physical law of motion in order to eliminate sharp turns, abrupt speed change and sudden stops exhibited by existing models. We formulate the smooth mobility model by a semi-Markov process to analyze the steady state properties of this model because the transition time between consecutive phases (states) has a discrete uniform distribution, instead of an exponential distribution. Through stochastic analysis, we prove that this model unifies many good features for analysis and simulations of mobile networks. First, it is smooth and steady because there is no speed decay problem for arbitrary starting speed, while maintaining uniform spatial node distribution regardless of node placement. Second, it can be easily and flexibly applied for simulating node mobility in wireless networks. It can also adapt to different network environments such as group mobility and geographic constraints. To demonstrate the impact of this model, we evaluate the effect of this model on distribution of relative speed, link lifetime between neighboring nodes, and average node degree by ns-2 simulations.

The random waypoint mobility model with uniform node spatial distribution

In this paper, we tackle the problem of designing a random mobility model generating a target node spatial distribution. More specifically, we solve a long standing open problem by presenting two versions of the well-known random waypoint (RWP) mobility model in bounded regions generating a uniform steady-state node spatial distribution. In the first version, named temporal-RWP, we exploit the temporal dimension of node mobility and achieve uniformity by continuously changing the speed of a mobile node as a function of its location and of the density function of trajectories in the movement region R. In the second version, named spatial-RWP, we instead exploit the spatial dimension and achieve uniformity by selecting waypoints according to a suitably defined mix of probability density functions. Both proposed models can be easily incorporated in wireless network simulators, and are thus of practical use. The RWP models presented in this paper allow for the first time completely removing the well-known border effect causing possible inaccuracies in mobile network simulation, thus completing the picture of a “perfect” simulation methodology drawn in existing literature.     

A Statistical Analysis of the Long-Run Node Spatial Distribution in Mobile Ad Hoc Networks

In this paper, we analyze the node spatial distribution of mobile wireless ad hoc networks. Characterizing this distribution is of fundamental importance in the analysis of many relevant properties of mobile ad hoc networks, such as connectivity, average route length, and network capacity. In particular, we have investigated under what conditions the node spatial distribution resulting after a large number of mobility steps resembles the uniform distribution. This is motivated by the fact that the existing theoretical results concerning mobile ad hoc networks are based on this assumption. In order to test this hypothesis, we performed extensive simulations using two well-known mobility models: the random waypoint model, which resembles intentional movement, and a Brownian-like model, which resembles non-intentional movement. Our analysis has shown that in Brownian-like motion the uniformity assumption does hold, and that the intensity of the concentration of nodes in the center of the deployment region that occurs in the random waypoint model heavily depends on the choice of some mobility parameters. For extreme values of these parameters, the uniformity assumption is impaired.     

Spatial node distribution of the random waypoint mobility model with applications

The random waypoint model (RWP) is one of the most widely used mobility models in performance analysis of ad hoc networks. We analyze the stationary spatial distribution of a node moving according to the RWP model in a given convex area. For this, we give an explicit expression, which is in the form of a one-dimensional integral giving the density up to a normalization constant. This result is also generalized to the case where the waypoints have a nonuniform distribution. As a special case, we study a modified RWP model, where the waypoints are on the perimeter. The analytical results are illustrated through numerical examples. Moreover, the analytical results are applied to study certain performance aspects of ad hoc networks, namely, connectivity and traffic load distribution.     

The node distribution of the random waypoint mobility model for wireless ad hoc networks

The random waypoint model is a commonly used mobility model in the simulation of ad hoc networks. It is known that the spatial distribution of network nodes moving according to this model is, in general, nonuniform. However, a closed-form expression of this distribution and an in-depth investigation is still missing. This fact impairs the accuracy of the current simulation methodology of ad hoc networks and makes it impossible to relate simulation-based performance results to corresponding analytical results. To overcome these problems, we present a detailed analytical study of the spatial node distribution generated by random waypoint mobility. More specifically, we consider a generalization of the model in which the pause time of the mobile nodes is chosen arbitrarily in each waypoint and a fraction of nodes may remain static for the entire simulation time. We show that the structure of the resulting distribution is the weighted sum of three independent components: the static, pause, and mobility component. This division enables us to understand how the model's parameters influence the distribution. We derive an exact equation of the asymptotically stationary distribution for movement on a line segment and an accurate approximation for a square area. The good quality of this approximation is validated through simulations using various settings of the mobility parameters. In summary, this article gives a fundamental understanding of the behavior of the random waypoint model.     

基于人类真实场景的分时段的机会网络移动模型

针对现有移动模型不能有效反映出节点移动过程中的行为特性,提出了一种基于人类真实场景中的分时段的机会网络移动模型,通过建立节点日常移动模型,依据时间段划分节点子移动模型,分析了基于人类真实场景的机会网络移动模型下的节点行为特性,包括节点平均停留时间、不同时段社区节点个数以及目的变换频率等。并与已采集到的真实移动数据和其他移动模型进行仿真比较。仿真结果充分表明,在节点相遇间隔时间等方面,该模型贴近真实场景中节点所表现出的行为特性,并且优于其他节点移动模型。     

Connectivity Probability of Wireless Ad Hoc Networks: Definition, Evaluation, Comparison

The paper presents a new approach investigating mobile ad hoc network connectivity. It is shown how to define and evaluate the connectivity probability of a mobile network where the position of the nodes and the link quality changes over time. The connectivity probability is a measure that can capture the impact of the node movement on the network connectivity. A number of mobility models is considered ranging from the classical Random Direction model to the Virtual World model based on the mobility measurements of a multi–player game. We introduce an Attractor model as a simple way to model non–homogeneous node distribution by incorporating viscosity regions in the simulation area. Methods of ergodic theory are used to show the correctness of the approach and to reduce the computational time. Simulation results show how the node density distribution affects the network connectivity.     

Research on mobile strategy of anchor node based on weighted virtual force model

The existing mobility strategy of the anchor node in wireless sensor network (WSN) has the shortcomings of too long moving path and low positioning accuracy when the anchor node traverses the network voids area.A new mobility strategy of WSN anchor node was proposed based on an improved virtual forces model.The number of neighbor nodes and the distance between the neighbor nodes to the anchor nodes were introduced as their own dense weight attributes.The unknown nodes intensity was used as weights to improve the traditional virtual force model.Meantime the distance-measuring error ε was taken into account.The optimal distribution,direction selection,shift step length and fallback strategy of anchor node could be analyzed by the trilateration.Using the number of virtual beacon received by the unknown node and the distance between the unknown node to the anchor node calculate the virtual force.Then according to the virtual force,the direction was chosen and the anchor nodes were moved.Simulation experiments show that the strategy can make the anchor nodes move according to the specific circumstances of unknown node distribution.It has a high positioning accuracy and strong adaptability.It can successfully shorten the path of the anchor node movement and reduce the number of virtual beacon.Moreover it can effectively avoid the anchor node to enter the network voids area and reduce the number of collinear virtual anchor nodes.