移动自组网应用建模及无线收发器选用策略

移动自组网作为一种特殊的无线网络被越来越广泛的应用,随之也变得越来越复杂.所以不同的应用场景需要采用不同的配置来组建自组网,才能达到网络性能相对最优.其中网络连通性和能源问题成为重点需要考虑的因素.为了更加合理高效地组建自组网,本文定义了一种移动自组网应用模型,并采用此模型对自组网应用场景进行了分类,提出了一种组建自组网的方法,重点对无线收发器的选择进行了研究.     

一种基于802.11 DCF Basic Access机制的移动自组网动态速率控制模型

802.11移动自组网由于其固有的动态拓扑、分布式协作等特点,路由协议普遍采用多播方式以提高无线链接的传输效率,由此带来的拥塞使得移动自组网中多播拥塞控制至关重要。针对移动自组网中节点固有的随机特性,基于802.11 DCF协议,该文提出一种精确描述节点数据产生、排队、发送动态过程的拟生灭模型,并通过矩阵几何方法对其进行稳态分析,得出节点速率阈值方程组,并用OPNET进行了仿真实验,仿真结果与理论值拟合较好,为移动自组网中的拥塞控制提供了一个量化的指标。     

航空自组网节点密度与组网概率分析

随着Ad hoc的发展,人们开始研究它在航空通信领域的应用.应用于航空通信中的Ad hoc有很多特点,如节点运动速度快,节点密度小,通信距离远,频段为超短波波段等.而节点的密度是关系到能否构成航空自组网的首要问题.提出了一种航空自组网的模型,并研究了在该网中节点密度与能否组成Ad hoc网络的关系.利用贝努利试验的思想,推导出了在不同节点密度下一定区域内节点个数与其对应概率的关系式和节点密度与组网概率之间的关系式,并通过随机试验进行了仿真验证.为研究航空自组网提供重要的参考依据.     

基于不同移动模型的移动自组网多播路由协议性能研究

为了研究移动自组网中多播路由协议在不同移动模型下的性能,选取随机路点移动模型、高斯马尔科夫移动模型和参考点组移动模型,将三种移动模型的移动场景加入到NS2中,对基于部分网络编码的实时多播协议PNCRM进行仿真.结果表明,PNCRM协议在随机路点移动模型和高斯马尔科夫移动模型中的数据包投递率明显高于参考点组移动模型,但是参考点组移动模型的总开销和端到端延时是最优的.这样我们就可以根据不同的性能指标要求选择合适的移动模型.     

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.     

飞行自组网路由协议的仿真与分析

飞行自组网是移动自组网的一个新的研究方向,它将移动自组网的思想拓展到空天领域。但由于节点的高动态性和拓扑结构快速变化等特点,飞行自组网对路由协议提出更多挑战,传统移动自组网路由协议的适用性有待验证。文章利用OMNe T++仿真工具,针对飞行器组网的特定场景,对多种路由协议进行仿真,分析对比了各协议性能,探讨了无人机自组网路由协议的优选问题。实验结果表明OLSR_ETX协议综合性能优于其他几类协议,更适用于飞行自组网场景,但它在节点需要动态入网时表现不佳,还需要进一步的优化。     

移动自组网MAC协议的误码性能分析

考虑到节点的定时精度和侦听数据传输的节点带来了网络节点间的干扰（INI）,从而严重影响网络的性能,文中分析了移动自组网误码率性能。采用理论分析与Mento Carlo仿真相结合的方法,仿真结果示出了几种不同参数的取值对系统误码率的影响程度,对加速移动自组网技术的发展与应用具有一定意义。     

随机移动模型下移动自组网无序传输端到端延迟闭解分析

针对移动自组网端到端延迟在封闭形式分析方面的局限性,该文提出一种有效的针对无序传输,单副本两跳中继算法的网络延迟建模方案,并给出其严格的理论延迟上界。首先针对多种随机移动模型,证明了移动节点的相遇间隔时间可归纳为统一表达式。然后,综合分析了媒介竞争、流量竞争、排队延迟等问题,合理划分并精确求解出了各延迟关键时间段,从而构造了数据包排队服务模型。最后推导出移动自组网端到端延迟的封闭形式理论上界。仿真结果表明,该理论延迟与实验数据紧密吻合。     

基于机器学习的移动自组网MAC协议研究综述

MAC协议设计是移动自组网的一项重要关键技术,主要通过有效的多节点协商机制,实现各节点对空间、时间、频率等有限资源的合理共享,完成各节点的随机接入和资源分配功能。随机接入和资源分配问题通常可用最优化和马尔科夫决策问题表述,机器学习可成为提升移动自组网MAC协议性能的有力手段之一。该综述在分析机器学习和移动自组网MAC协议特点基础上,结合现有研究成果,介绍了基于机器学习的关键技术原理和仿真性能,展望了未来研究方向。现有研究成果表明,基于机器学习的MAC协议设计性能改善显著。     

移动自组网组播路由协议的分析

移动自组网是无中心、自组织、可快速展开、可移动的对等式网络,组播作为群组服务在移动自组网中应用广泛。移动自组网具有节点移动频繁、能源和带宽有限等特点,它要求组播协议能在节点频繁移动下具备良好的健壮性,传统的组播协议已不适用。文章介绍了移动自组网组播路由协议,描述了几种组播路由协议的基本运行过程,并对其性能进行了分析和比较,最后论述了组播协议在能源、安全、组播服务(QOS)、利用位置信息等方向的应用前景及面临的问题。     

一种高效的延迟容忍移动传感器网络异步探测机制

针对延迟容忍移动传感器网络(Delay Tolerant Mobility Sensor Network, DTMSN)节点间连接探测开销大、错失率高的问题,该文提出一种高效的DTMSN异步探测机制(Efficient Asynchronous Probing Scheme, EAPS)。该机制面向随机路点(Random Way-Point, RWP)移动模型,在采用互质周期对的时隙睡眠机制基础上,通过对节点运动区域的合理划分和周期对的优化选择,保证了网络连接探测的高成功率和低能耗的特性。仿真结果表明,与现有的异步探测机制相比,该机制能够在低能耗下实现更高的探测成功率与更低的探测延迟。     

The IMPORTANT framework for analyzing the Impact of Mobility on Performance Of RouTing protocols for Adhoc NeTworks

A Mobile Ad hoc Network (MANET) is a collection of wireless mobile nodes forming a temporary network without using any existing infrastructure. Since not many MANETs are currently deployed, research in this area is mostly simulation based. Random Waypoint is the commonly used mobility model in these simulations. Random Waypoint is a simple model that may be applicable to some scenarios. However, we believe that it is not sufficient to capture some important mobility characteristics of scenarios in which MANETs may be deployed. Our framework aims to evaluate the impact of different mobility models on the performance of MANET routing protocols. We propose various protocol independent metrics to capture interesting mobility characteristics, including spatial and temporal dependence and geographic restrictions. In addition, a rich set of parameterized mobility models is introduced including Random Waypoint, Group Mobility, Freeway and Manhattan models. Based on these models several ‘test-suite’ scenarios are chosen carefully to span the metric space. We demonstrate the utility of our test-suite by evaluating various MANET routing protocols, including DSR, AODV and DSDV. Our results show that the protocol performance may vary drastically across mobility models and performance rankings of protocols may vary with the mobility models used. This effect can be explained by the interaction of the mobility characteristics with the connectivity graph properties. Finally, we attempt to decompose the reactive routing protocols into mechanistic “building blocks” to gain a deeper insight into the performance variations across protocols in the face of mobility.     

Analytical Studies of Interaction between Mobility Models and Single-Multi Paths Routing Protocols in Mobile Ad Hoc Networks

Mobile ad hoc networks (MANETs) will play a vital role in civilian and military applications where users move around and share information with each other. The movement of users varies depending on the environment, e.g. people may move randomly in different directions (Random Waypoint and Gauss Markov mobility models); or walk, run and drive in two directions in the street (Manhattan Mobility Model); or move as a group (Reference Point Group Mobility model). The interaction between mobility patterns and routing protocols contributes significantly to vary the overall network performance. We build an analytical framework that shows an analysis structure for the overall network performance test. In this framework, we first compare the properties of the mobility models that are designated for MANETs. Second, we measure single path (proactive and reactive) and multipath (proactive and reactive) routing protocols across the mobility models by tuning into TCP and CBR traffic individually. Finally, we examine the performance of each routing protocol across mobility models and discuss the possibility of interaction between them. Most of the previous findings only evaluate the impact of mobility models and single path routing protocols with CBR traffic, whereas a significant finding of this study is that how the interaction between mobility models and single path and multipath routing protocols varies depending on the usage of traffic (TCP and CBR).     

一种延迟容忍移动传感器网络自适应连接探测机制

连接探测效率对延迟容忍移动传感器网络(Delay-Tolerant Mobility Sensor Network,DTMSN)的性能有着重要的影响。该文在对随机路点(Random Way-Point,RWP)移动模型统计特性研究的基础上,提出一种面向RWP的DTMSN自适应连接探测机制(Adaptive Contact-Probing Scheme,ACPS)。其基本思想是节点根据每次移动过程中连接到达率的不同,自适应地调整连接探测次数和探测时间,通过提高探测效率和探测准确性来降低探测能量开销和连接发现延迟。仿真结果表明,与固定周期探测机制(Fixed-cycle Probing Scheme,FPS)相比,ACPS能够以较低的能量开销取得更高的探测成功率和更短的连接发现延迟。     

Ad Hoc网络移动模型节点空间分布研究

节点空间分布是Ad Hoc网络移动模型研究的重点,也是对移动模型评价的重要指标.对RW,RD,RWP,GM,SMS移动模型分别在不同条件下处于矩形及圆仿真区域中节点空间分布进行了仿真,并对其进行比较研究,得出了不同速度、速度服从不同分布,暂停时间服从不同分布和不同仿真区域对移动模型节点空间分布的影响,为移动模型的选择、仿真区域的选择及模型中各类参数的设置提供了重要的依据.     

CGAM: A community and geography aware mobility model

The advances of localization‐enabled technologies have led to huge volumes of large‐scale human mobility data collected from Call Data Records (CDR), Global Positioning System (GPS) tracking systems, and Location Based Social networks (LBSN). These location data that encompass mobility patterns could generate an important value for building accurate and realistic mobility models and hence important value for fields of application including context‐aware advertising, city‐wide sensing applications, urban planning, and more. In this paper, we investigate the underlying spatio‐temporal and structural properties for human mobility patterns, and propose the Community and Geography Aware Mobility (CGAM) model, which characterizes user mobility knowledge through several properties such as home location distribution, community members' distribution, and radius of gyration. We validate the CGAM synthetic traces against real‐world GPS traces and against the traces generated by the baseline mobility model SMOOTH and assess that CGAM is accurate in predicting the performance of flooding‐based and community‐based routing protocols.     

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。     

基于粒子滤波步行长度预测的移动ad hoc网络路由算法

针对移动ad hoc网络拓扑结构变化大、路由复杂度高、数据传输性能低等问题,提出了一种新的移动通信系统自适应路由算法。为了使得网络拓扑结构更接近移动网络间歇性连接的特点,该算法在网络结构上采用了一种改进的Levy Walk移动模型。采用一种粒子滤波步行长度预测的方法,通过蒙特卡罗抽样得到递归贝叶斯滤波器,并在粒子滤波后进行步行长度预测,确定消息的副本数量,从而减少由于节点转发过多消息副本带来的能量消耗量,提高消息的传递效率。实验仿真结果表明：与基于改进蚁群优化和利润优化模型的路由算法相比,该算法的消息传递成功率分别提高了0.08和0.04,节点平均能量效率提高了17.9%和13.4%,在提升数据传输成功率和节能上具有较好效果。     

A Novel Modelling Technique for Tracing Mobile Users in a Cellular Mobile Communication System

Mobility of users in a cellular mobile communication system has been formulated mathematically under generalized conditions. Based on this model a computer simulation has been developed. This mobility model is used to examine cell residence time distribution in cellular environments defined by different cell sizes and mobility parameters. It is shown that cell residence time can be described by the generalized gamma distribution.     

Combinatorial Mobile IP: A New Efficient Mobility Management Using Minimized Paging and Local Registration in Mobile IP Environments

Combinatorial Mobile IP, a new mobility management scheme for Mobile IP, is proposed and analyzed. We present how to adopt mobility management schemes on cellular networks and adapt them in Mobile IP without disrupting the nature of the Internet. We apply widely used mobility management schemes such as hierarchical architecture and paging in cellular networks to Mobile IP. We restrict paging to the area that has to be paged using local registrations. In this way, we show that the total signaling costs of Combinatorial Mobile IP are reduced compared to other micro-mobility protocols such as Mobile IP Regional Registration and P-MIP. Random walk on a connected graph is used to analyze the performance of Combinatorial Mobile IP.