移动自组网(Mobile Ad Hoc Network, MANET)主要应用于军事活动、灾后救援等大规模的活动中,随着节点数的增加、移动速度的加快,网络拓扑变得更加复杂,网络稳定性和性能也随之下降。频繁的网络拓扑变化会导致簇结构变得不稳定并且控制...移动自组网(Mobile Ad Hoc Network, MANET)主要应用于军事活动、灾后救援等大规模的活动中,随着节点数的增加、移动速度的加快,网络拓扑变得更加复杂,网络稳定性和性能也随之下降。频繁的网络拓扑变化会导致簇结构变得不稳定并且控制开销也会增加。为了解决这一问题,提出了一种改进的加权分簇算法,通过仿真表明,该算法可以有效地提高大规模移动自组网的性能。展开更多
Traffic in today’s cities is a serious problem that increases travel times,negatively affects the environment,and drains financial resources.This study presents an Artificial Intelligence(AI)augmentedMobile Ad Hoc Ne...Traffic in today’s cities is a serious problem that increases travel times,negatively affects the environment,and drains financial resources.This study presents an Artificial Intelligence(AI)augmentedMobile Ad Hoc Networks(MANETs)based real-time prediction paradigm for urban traffic challenges.MANETs are wireless networks that are based on mobile devices and may self-organize.The distributed nature of MANETs and the power of AI approaches are leveraged in this framework to provide reliable and timely traffic congestion forecasts.This study suggests a unique Chaotic Spatial Fuzzy Polynomial Neural Network(CSFPNN)technique to assess real-time data acquired from various sources within theMANETs.The framework uses the proposed approach to learn from the data and create predictionmodels to detect possible traffic problems and their severity in real time.Real-time traffic prediction allows for proactive actions like resource allocation,dynamic route advice,and traffic signal optimization to reduce congestion.The framework supports effective decision-making,decreases travel time,lowers fuel use,and enhances overall urban mobility by giving timely information to pedestrians,drivers,and urban planners.Extensive simulations and real-world datasets are used to test the proposed framework’s prediction accuracy,responsiveness,and scalability.Experimental results show that the suggested framework successfully anticipates urban traffic issues in real-time,enables proactive traffic management,and aids in creating smarter,more sustainable cities.展开更多
This paper contributes a sophisticated statistical method for the assessment of performance in routing protocols salient Mobile Ad Hoc Network(MANET)routing protocols:Destination Sequenced Distance Vector(DSDV),Ad hoc...This paper contributes a sophisticated statistical method for the assessment of performance in routing protocols salient Mobile Ad Hoc Network(MANET)routing protocols:Destination Sequenced Distance Vector(DSDV),Ad hoc On-Demand Distance Vector(AODV),Dynamic Source Routing(DSR),and Zone Routing Protocol(ZRP).In this paper,the evaluation will be carried out using complete sets of statistical tests such as Kruskal-Wallis,Mann-Whitney,and Friedman.It articulates a systematic evaluation of how the performance of the previous protocols varies with the number of nodes and the mobility patterns.The study is premised upon the Quality of Service(QoS)metrics of throughput,packet delivery ratio,and end-to-end delay to gain an adequate understanding of the operational efficiency of each protocol under different network scenarios.The findings explained significant differences in the performance of different routing protocols;as a result,decisions for the selection and optimization of routing protocols can be taken effectively according to different network requirements.This paper is a step forward in the general understanding of the routing dynamics of MANETs and contributes significantly to the strategic deployment of robust and efficient network infrastructures.展开更多
移动Ad hoc网络(MANET,Mobile Ad hoc Networks)正得到越来越广泛的应用,相应的网络安全问题也开始得到广泛的关注。研究MANET网络可能遭遇的攻击方式,提出基于机器学习技术的入侵检测性能评估模型,并提出一个综合评价指标,比较了7种机...移动Ad hoc网络(MANET,Mobile Ad hoc Networks)正得到越来越广泛的应用,相应的网络安全问题也开始得到广泛的关注。研究MANET网络可能遭遇的攻击方式,提出基于机器学习技术的入侵检测性能评估模型,并提出一个综合评价指标,比较了7种机器学习算法在MANET网络入侵检测中的性能表现,对于构建安全有效的MANET网络具有重要的意义。使用GloMoSim仿真工具对MANET网络正常行为及黑洞、洪水、丢包3种入侵行为进行模拟,并详细分析了各种攻击情况下,7种机器学习算法的性能表现。分析结果显示,该评估模型能较好地反映出各种机器学习算法的性能,其中,多层感知器、逻辑回归和支持向量机具有较高的检测率及较低的误报率。展开更多
MANET(Mobile Ad Hoc Network)是由一组无线移动主机组成的一个没有任何建立好的基础设施或集中管理设备的临时网络。网络拓扑易变、带宽、能源有限是Ad Hoc移动网络的主要特点。重点介绍了Ad hoc网络的组网关键技术——路由协议,并对...MANET(Mobile Ad Hoc Network)是由一组无线移动主机组成的一个没有任何建立好的基础设施或集中管理设备的临时网络。网络拓扑易变、带宽、能源有限是Ad Hoc移动网络的主要特点。重点介绍了Ad hoc网络的组网关键技术——路由协议,并对现在的具有代表性的协议性能进行了比较,研究了在不同环境下的各自路由协议仿真实验所体现出来的性能差别,对Ad hoc的组网具有指导意义。展开更多
简单介绍MANET(Mobile Ad hoc Network)路由协议后,提出定量评估MANET路由协议性能的六个基本指标。基于网络仿真器NS-2阐述了评估和测试路由协议性能的仿真模型及数据结果的分析方法,并给出仿真实例及其分析。结果表明,模型仿真结果接...简单介绍MANET(Mobile Ad hoc Network)路由协议后,提出定量评估MANET路由协议性能的六个基本指标。基于网络仿真器NS-2阐述了评估和测试路由协议性能的仿真模型及数据结果的分析方法,并给出仿真实例及其分析。结果表明,模型仿真结果接近理论分析和实际情况,该性能评估方法有较强的实用性和通用性。展开更多
文摘移动自组网(Mobile Ad Hoc Network, MANET)主要应用于军事活动、灾后救援等大规模的活动中,随着节点数的增加、移动速度的加快,网络拓扑变得更加复杂,网络稳定性和性能也随之下降。频繁的网络拓扑变化会导致簇结构变得不稳定并且控制开销也会增加。为了解决这一问题,提出了一种改进的加权分簇算法,通过仿真表明,该算法可以有效地提高大规模移动自组网的性能。
基金the Deanship of Scientific Research at Majmaah University for supporting this work under Project No.R-2024-1008.
文摘Traffic in today’s cities is a serious problem that increases travel times,negatively affects the environment,and drains financial resources.This study presents an Artificial Intelligence(AI)augmentedMobile Ad Hoc Networks(MANETs)based real-time prediction paradigm for urban traffic challenges.MANETs are wireless networks that are based on mobile devices and may self-organize.The distributed nature of MANETs and the power of AI approaches are leveraged in this framework to provide reliable and timely traffic congestion forecasts.This study suggests a unique Chaotic Spatial Fuzzy Polynomial Neural Network(CSFPNN)technique to assess real-time data acquired from various sources within theMANETs.The framework uses the proposed approach to learn from the data and create predictionmodels to detect possible traffic problems and their severity in real time.Real-time traffic prediction allows for proactive actions like resource allocation,dynamic route advice,and traffic signal optimization to reduce congestion.The framework supports effective decision-making,decreases travel time,lowers fuel use,and enhances overall urban mobility by giving timely information to pedestrians,drivers,and urban planners.Extensive simulations and real-world datasets are used to test the proposed framework’s prediction accuracy,responsiveness,and scalability.Experimental results show that the suggested framework successfully anticipates urban traffic issues in real-time,enables proactive traffic management,and aids in creating smarter,more sustainable cities.
基金supported by Northern Border University,Arar,KSA,through the Project Number“NBU-FFR-2024-2248-02”.
文摘This paper contributes a sophisticated statistical method for the assessment of performance in routing protocols salient Mobile Ad Hoc Network(MANET)routing protocols:Destination Sequenced Distance Vector(DSDV),Ad hoc On-Demand Distance Vector(AODV),Dynamic Source Routing(DSR),and Zone Routing Protocol(ZRP).In this paper,the evaluation will be carried out using complete sets of statistical tests such as Kruskal-Wallis,Mann-Whitney,and Friedman.It articulates a systematic evaluation of how the performance of the previous protocols varies with the number of nodes and the mobility patterns.The study is premised upon the Quality of Service(QoS)metrics of throughput,packet delivery ratio,and end-to-end delay to gain an adequate understanding of the operational efficiency of each protocol under different network scenarios.The findings explained significant differences in the performance of different routing protocols;as a result,decisions for the selection and optimization of routing protocols can be taken effectively according to different network requirements.This paper is a step forward in the general understanding of the routing dynamics of MANETs and contributes significantly to the strategic deployment of robust and efficient network infrastructures.
文摘移动Ad hoc网络(MANET,Mobile Ad hoc Networks)正得到越来越广泛的应用,相应的网络安全问题也开始得到广泛的关注。研究MANET网络可能遭遇的攻击方式,提出基于机器学习技术的入侵检测性能评估模型,并提出一个综合评价指标,比较了7种机器学习算法在MANET网络入侵检测中的性能表现,对于构建安全有效的MANET网络具有重要的意义。使用GloMoSim仿真工具对MANET网络正常行为及黑洞、洪水、丢包3种入侵行为进行模拟,并详细分析了各种攻击情况下,7种机器学习算法的性能表现。分析结果显示,该评估模型能较好地反映出各种机器学习算法的性能,其中,多层感知器、逻辑回归和支持向量机具有较高的检测率及较低的误报率。
文摘MANET(Mobile Ad Hoc Network)是由一组无线移动主机组成的一个没有任何建立好的基础设施或集中管理设备的临时网络。网络拓扑易变、带宽、能源有限是Ad Hoc移动网络的主要特点。重点介绍了Ad hoc网络的组网关键技术——路由协议,并对现在的具有代表性的协议性能进行了比较,研究了在不同环境下的各自路由协议仿真实验所体现出来的性能差别,对Ad hoc的组网具有指导意义。
文摘简单介绍MANET(Mobile Ad hoc Network)路由协议后,提出定量评估MANET路由协议性能的六个基本指标。基于网络仿真器NS-2阐述了评估和测试路由协议性能的仿真模型及数据结果的分析方法,并给出仿真实例及其分析。结果表明,模型仿真结果接近理论分析和实际情况,该性能评估方法有较强的实用性和通用性。
