基于强化学习的大规模多模Mesh网络联合路由选择及资源调度算法

为了平衡新型电力系统中大规模多模Mesh网络的传输可靠性和效率,该文在对优化问题进行描述和分析的基础上提出一种基于强化学习的大规模多模Mesh网络联合路由选择及资源调度算法,分为两个阶段。在第1阶段中,根据网络拓扑结构信息和业务需求,利用一种多条最短路径路由算法,输出所有最短路径。在第2阶段中,提出一种基于多臂老虎机(MAB)的资源调度算法,该算法基于得到的最短路径集合构建MAB的摇臂,然后根据业务需求计算回报,最终给出最优的路由选择及资源调度方式用于业务传输。仿真结果表明,所提算法能够满足不同的业务传输需求,实现端到端路径的平均时延和平均传输成功率的高效平衡。

软件定义无线Mesh网络多目标路由优化算法

无线Mesh网络(Wireless Mesh network, WMN)中,链路拥塞会导致较长的传输时延和排队时间,因此将链路负载均衡与服务质量结合起来一直是研究热点.本文针对多目标路由优化管理的关键问题,将路由问题表述为整数线性规划(Integer linear programming, ILP)模型,并将无线Mesh网络与软件定义网络(Software defined network, SDN)结合,设计了适应于SD-WMN架构的多目标函数、约束条件以及整体的网络优化模型,此外,由于该整数线性规划模型是NP完全的,本文将改进的人工蜂群的启发式优化算法引入到路由优化算法中,以获得源节点和目的节点之间传输流量的理想路径.本文所提出方法在Mininet网络模拟工具中的仿真结果证明了该算法的有效性,与OSPF、SDNR以及遗传蚁群优化(G-ACO)相比,所提出方法在丢包率、往返时间和负载均衡方面均有不错的改善.

Modelling a Learning-Based Dynamic Tree Routing Model for Wireless Mesh Access Networks

Link asymmetry in wireless mesh access networks(WMAN)of Mobile ad-hoc Networks(MANETs)is due mesh routers’transmission range.It is depicted as significant research challenges that pose during the design of network protocol in wireless networks.Based on the extensive review,it is noted that the substantial link percentage is symmetric,i.e.,many links are unidirectional.It is identified that the synchronous acknowledgement reliability is higher than the asynchronous message.Therefore,the process of establishing bidirectional link quality through asynchronous beacons underrates the link reliability of asym-metric links.It paves the way to exploit an investigation on asymmetric links to enhance network functions through link estimation.Here,a novel Learning-based Dynamic Tree routing(LDTR)model is proposed to improve network performance and delay.For the evaluation of delay measures,asymmetric link,interference,probability of transmission failure is evaluated.The proportion of energy consumed is used for monitoring energy conditions based on the total energy capacity.This learning model is a productive way for resolving the routing issues over the network model during uncertainty.The asymmetric path is chosen to achieve exploitation and exploration iteratively.The learning-based Dynamic Tree routing model is utilized to resolve the multi-objective routing problem.Here,the simulation is done with MATLAB 2020a simulation environment and path with energy-efficiency and lesser E2E delay is evaluated and compared with existing approaches like the Dyna-Q-network model(DQN),asymmetric MAC model(AMAC),and cooperative asymmetric MAC model(CAMAC)model.The simulation outcomes demonstrate that the anticipated LDTR model attains superior network performance compared to others.The average energy consump-tion is 250 J,packet energy consumption is 6.5 J,PRR is 50 bits/sec,95%PDR,average delay percentage is 20%.

基于Mesh网络的集群式照明管理系统设计

目前的mesh网络中若使用电池供电的传感器,则设备的频繁通信和控制会导致额外的能源消耗。因此,本文基于mesh网络设计了一款集群式照明管理的系统,通过对该系统总框架的设计,将系统所具备的功能分成了数据采集、网络拓扑结构、集群控制等三个模块。通过实验分析,验证出该系统在数据传输效率、控制精准度以及节能效果等方面均具有显著优势。

基于蜂窝结构的海上风电场无线Mesh网络覆盖优化算法

以往的海上风电场无线Mesh网络覆盖优化算法由于仅计算了单一的优化目标,导致算法的优化效果不佳。因此,设计了基于蜂窝结构的海上风电场无线Mesh网络覆盖优化算法。考虑到蜂窝结构的特性,得到基于蜂窝结构的海上风电场覆盖情况,根据覆盖区域中静态节点的分布情况,制定相应网络节点移动策略,在上述基础上,构建相应的风电场网络覆盖模型,并通过计算节点覆盖率和节点移动距离,得到相应的优化目标函数,通过计算移动节点的适应度,实现对风电场的网络覆盖优化。通过上述的设计,完成对海上风电场无线Mesh网络覆盖优化算法的设计。在实验测试中,和以往的海上风电场无线Mesh网络覆盖优化算法相比,设计的基于蜂窝结构的海上风电场无线Mesh网络覆盖优化算法在实际应用后,网络覆盖率提升到98.12%,优化效果较好。

Mechanical properties of steel mesh in anchor-mesh support for rocky tunnels

Underground geotechnical engineering encounters persistent challenges in ensuring the stability and safety of surrounding rock structures, particularly within rocky tunnels. Rock reinforcement techniques, including the use of steel mesh, are critical to achieving this goal. However, there exists a knowledge gap regarding the comprehensive understanding of the mechanical behavior and failure mechanisms exhibited by steel mesh under diverse loading conditions. This study thoroughly explored the steel mesh's performance throughout the entire loading-failure process, innovating with detailed analysis and modeling techniques. By integrating advanced numerical modeling with laboratory experiments, the study examines the influence of varying reinforcement levels and geometric parameters on the steel mesh strength and deformation characteristics. Sensitivity analysis, employing gray correlation theory, identifies the key factors affecting the mesh performance, while a BP (Backpropagation) neural network model predicts maximum vertical deformation with high accuracy. The findings underscore the critical role of steel diameter and mesh spacing in optimizing peak load capacity, displacement, and energy absorption, offering practical guidelines for design improvements. The use of a Bayesian Regularization (BR) algorithm further enhances the predictive accuracy compared to traditional methods. This research provides new insights into optimizing steel mesh design for underground applications, offering an innovative approach to enhancing structural safety in geotechnical projects.

Understanding of the Relationship between the Properties of Cu(In,Ga)Se_(2) Solar Cells and the Structure of Ag Network Electrodes

The relation between the structure of the silver network electrodes and the properties of Cu(In,Ga)Se_(2)(CIGS)solar cells is systemically investigated.The Ag network electrode is deposited onto an Al:ZnO(AZO)thin film,employing a self-forming cracked template.Precise control over the cracked template's structure is achieved through careful adjustment of temperature and humidity.The Ag network electrodes with different coverage areas and network densities are systemically applied to the CIGS solar cells.It is revealed that predominant fill factor(FF)is influenced by the figure of merit of transparent conducting electrodes,rather than sheet resistance,particularly when the coverage area falls within the range of 1.3–5%.Furthermore,a higher network density corresponds to an enhanced FF when the coverage areas of the Ag networks are similar.When utilizing a thinner AZO film,CIGS solar cells with a surface area of 1.0609 cm^(2)exhibit a notable performance improvement,with efficiency increasing from 10.48%to 11.63%.This enhancement is primarily attributed to the increase in FF from 45%to 65%.These findings underscore the considerable potential for reducing the thickness of the transparent conductive oxide(TCO)in CIGS modules with implications for practical applications in photovoltaic technology.

基于无线Mesh自组网煤矿液压支架压力传感器设计与应用

通过研究现有无线矿山压力监测系统中液压支架传感器应用情况,发现普遍存在数据传输不稳定与传感器功耗高问题,为此利用无线Mesh自组网技术设计煤矿液压支架压力传感器,克服数据传输不稳定及功耗高的问题。以STM32L412单片机为核心处理器,定时采集液压支架压力数据,对压力数据进行处理和存储,并控制数据通过无线Mesh网络传输至监测分站,最终到达地面监测系统。设计中将无线Mesh模块唤醒机制与STM32L412单片机低功耗模式结合设计,保证数据传输可靠性同时,兼顾传感器低功耗。经过现场实际应用,所设计的液压支架压力传感器在矿井下环境中数据传输稳定、传感器功耗低,适合煤矿工作面液压支架压力采集监测。

集群式照明管理中Mesh网络技术研究

面对网络拓扑动态变化、多跳传输带来的延迟问题,文章旨在深入探讨Mesh网络技术在集群式照明管理中的应用要点,以期进一步推动智能照明控制系统的实用化与智能化,为创造绿色、智能的城市生活提供有力的技术支撑。

WiFace:A Secure GeoSocial Networking System Using Wi-Fi Based Multihop MANET

A number of mobile Online Social Networking （OSN） services have appeared in the market in recent times. While most mobile systems benefit greatly from cloud services, centralized servers and communications infrastructure is not always available. Nor are location-based services offered to mobile devices without GPS. To take advantage of cloud and to address these problems, a Wi-Fi based multihop networking system called MoNet is proposed. On top of MONET we propose a privacy-aware geosocial networking service called WiFace. Where there is no infrastructure, a distributed content sharing protocol significantly shortens the relay path, reduces conflicts, and improves data availability. Furthermore, a security mechanism is developed to protect privacy. Comprehensive experiments performed on MoNet show that the system is more than sufficient to support social networking and even audio and video applications.

基于5G技术的消防Mesh专网基站设计

设计了一款基于5G技术的消防Mesh专网通信基站,基于双向OFDM传输技术、载波聚合、无线感知抗干扰、混合场景下路由算法等关键技术,在不提高基站发射功率的前提下,增大网络通信速率,扩大传输距离,提高抗干扰性能,并进行了实验室环境下网络性能测试和外场应用测试。试验结果表明,专网基站最大通信带宽可达100 Mbps,基站点对点传输距离可达80 km以上,可有效避免同频段其他无用信号的干扰,多跳组网后仍具备较高的数据传输能力且时延与双跳组网基本一致,该基站可以作为数字化战场的核心通信节点,解决传统Mesh设备和技术面临的难题。

基于Q-Learning的动态BLE Mesh网络高能效路由算法

针对动态低功耗蓝牙(Bluetooth Low Energy, BLE)Mesh网络规范采用的管理式泛洪路由机制所导致的数据包冗余和高能耗的问题,提出了动态BLE Mesh网络高能效路由算法。通过建立基于Q-Learning的BLE Mesh网络路由模型,将BLE Mesh网络中节点的剩余能量、转发成本、移动因子以及接收信号强度指示(Received Signal Strength Indicator, RSSI)纳入到奖励函数的设计中。同时对BLE Mesh网络中的心跳机制进行改进,使网络中的节点更加高效地获取环境信息。采用基于探索的路由发现机制来更新网络中节点的Q值,使其能更加准确反映节点移动所导致的网络拓扑变化。仿真结果表明,该算法在节点能耗和网络开销上均优于传统的管理式泛洪路由机制。

A Framework for Multi-Hop Ad-Hoc Networking over Wi-Fi Direct with Android Smart Devices

The wide diffusion of mobile devices that natively support ad hoc communication technologies has led to several protocols for enabling and optimizing Mobile Ad Hoc Networks (MANETs). Nevertheless, the actual utilization of MANETs in real life seems limited due to the lack of protocols for the automatic creation and evolution of ad hoc networks. Recently, a novel P2P protocol named Wi-Fi Direct has been proposed and standardized by the Wi-Fi Alliance to facilitate nearby devices’ interconnection. Wi-Fi Direct provides high-performance direct communication among devices, includes different energy management mechanisms, and is now available in most Android mobile devices. However, the current implementation of Wi-Fi Direct on Android has several limitations, making the Wi-Fi Direct network only be a one-hop ad-hoc network. This paper aims to develop a new framework for multi-hop ad hoc networking using Wi-Fi Direct in Android smart devices. The framework includes a connection establishment protocol and a group management protocol. Simulations validate the proposed framework on the OMNeT++ simulator. We analyzed the framework by varying transmission range, number of hops, and buffer size. The results indicate that the framework provides an eventual 100% packet delivery for different transmission ranges and hop count values. The buffer size has enough space for all packets. However, as buffer size decreases, the packet delivery decreases proportionally.

应用驱动宽带Mesh与广电5G混合专网解决方案

面对海域、空域、河流、偏远山区和矿区等复杂场景的立体专网通信覆盖需求,存在建设成本高、可靠性低、传输链路困难等诸多瓶颈与挑战,需要构建更加合理、灵活和韧性强的混合专网系统以应对。本文分析了广电700 MHz频段5G网络的优势特点,研究了宽带Mesh无线自组网的特性,建设应用驱动下的宽带Mesh无线自组网与广电5G的混合专网系统,构建基于混合专网系统与MEC边缘计算的智慧管理平台,为智联、物联等多种行业应用提供整体解决方案。

基于ZigBee Mesh网络的智能防误判系统自动开锁设计

自动开锁过程中若出现误判情况,会导致用户出现经济财产损失,甚至会危害生命安全,所以提出基于ZigBee Mesh网络的智能防误判系统自动开锁设计方案。通过子节点、路由器以及网络协调器构建ZigBee网络树形结构,利用网络矢量路由完成各设备间的数据信息传输,结合无线Mesh网络,在ZigBee Mesh网络平台中接入现象控制器、防误主机、通信网络、网络接口设备以及闭锁节点,构建智能防误判系统,凭借电脑钥匙连接信息通信和防误判系统,以管理软件和解锁钥匙管理机制实现自动开锁。实验证明:所设计系统能有效避免防误开锁情况发生,且口令正确时自动开锁精准度高。

Mesh网络技术在电梯应急通信中的应用

传统的电梯应急通信系统基于有线传输,存在通话质量差、布线成本高等问题。Mesh网络属于无线通信,有效覆盖范围可达1000 m,将该网络技术应用于电梯应急通信,能够提高通信质量、降低运营成本。Mesh网络技术通过高级多带激励进行信号编解码,降低了对带宽的要求,研究设计并开发相应的通信终端和控制软件。经测试,在有障碍条件下,其有效传输距离满足设计要求,通话质量良好且丢包率较低,具有较强的实用性。

基于索道信息化设备的无线自适应智能Mesh网络

随着索道信息化的快速发展,吊厢/吊椅上的无线通信设备之间的网络通信成为了一项关键技术。由于吊厢/吊椅在运行过程中需要采用电池供电,并且所有通信设备需要将数据回传到索道站,无线通信距离达3 km左右,需要消耗较多电量,故索道吊厢/吊椅上无线通信设备减小电池电量消耗的技术显得尤为重要。文中提出一种索道吊厢/吊椅上的无线通信设备的自适应智能Mesh网络,在保证数据传输稳定和效率的前提下,使整个网络电量消耗效率最高,并且均衡每台信息化设备的综合功耗。

基于LoRaMesh组网技术的果园土壤参数监测系统的研究与设计

立足我国西北地区果园面积广阔且多位于山地、丘陵等地形复杂区域的实际情况,针对传统灌溉方式存在水分利用率、果品产量较低的问题,设计了一种基于LoRa扩频技术与Mesh网络结构的山地果园土壤参数实时监测系统,利用粒子群算法优化部署无线节点的数量并确定节点的坐标位置。以LoRaMesh模块与STM32L052K8低功耗处理器组成无线节点,将采集数据传输并汇聚至上位机进行统计分析。结果表明,该系统具有系统稳定性好、网络可靠性高的特点,实现了水果种植的无线数据采集、远程实时监控、灌溉过程调控,可确保果树的高产优质。

基于改进麻雀搜索算法的无线Mesh网络信道分配优化

文章在考虑网络信道分配优化模型的约束条件时,由于缺少对资源分配公平性的约束,导致信道分配后利用率较低,优化效果有限,为此,文章提出基于改进麻雀搜索算法的无线Mesh网络信道分配优化。文章采用数学模型描述网络中的信道分配问题,构建信道分配模型,结合Mesh网络的结构与特性,设计约束条件,包括网络连通性约束、信道容量约束和资源分配公平性约束。文章通过引入新的搜索策略和局部优化机制优化麻雀搜索算法,实施模型求解得到最佳信道分配方案。实验结果表明,在文章所提研究方法的应用下,Mesh网络信道的利用率得到了很大提升。

家庭Wi-Fi mesh组网技术

Wi-Fi mesh是一种适用于大面积或复杂户型的Wi-Fi自组网解决方案,为用户提供全覆盖、自切换、易安装的优质无线网络。Wi-Fimesh具备自组网、自管理、自修复和自平衡等诸多优点,但现有Wi-Fimesh产品实现方案存在标准不统一、实现复杂、终端能力要求高、无法互通的问题。首先讨论了现有家庭网络中多热点AP协同工作的实现情况,接着对当前Wi-Fimesh主流技术进行了分析,重点探讨了家庭Wi-Fimesh的技术方案和对比。进而面向家庭应用场景,为运营商提出了一种模块化、易实现、终端能力需求低且互通性好的Wi-Fi mesh技术实现方案。