DNBP-CCA:A Novel Approach to Enhancing Heterogeneous Data Traffic and Reliable Data Transmission for Body Area Network

The increased adoption of Internet of Medical Things (IoMT) technologies has resulted in the widespread use ofBody Area Networks (BANs) in medical and non-medical domains. However, the performance of IEEE 802.15.4-based BANs is impacted by challenges related to heterogeneous data traffic requirements among nodes, includingcontention during finite backoff periods, association delays, and traffic channel access through clear channelassessment (CCA) algorithms. These challenges lead to increased packet collisions, queuing delays, retransmissions,and the neglect of critical traffic, thereby hindering performance indicators such as throughput, packet deliveryratio, packet drop rate, and packet delay. Therefore, we propose Dynamic Next Backoff Period and Clear ChannelAssessment (DNBP-CCA) schemes to address these issues. The DNBP-CCA schemes leverage a combination ofthe Dynamic Next Backoff Period (DNBP) scheme and the Dynamic Next Clear Channel Assessment (DNCCA)scheme. The DNBP scheme employs a fuzzy Takagi, Sugeno, and Kang (TSK) model’s inference system toquantitatively analyze backoff exponent, channel clearance, collision ratio, and data rate as input parameters. Onthe other hand, the DNCCA scheme dynamically adapts the CCA process based on requested data transmission tothe coordinator, considering input parameters such as buffer status ratio and acknowledgement ratio. As a result,simulations demonstrate that our proposed schemes are better than some existing representative approaches andenhance data transmission, reduce node collisions, improve average throughput, and packet delivery ratio, anddecrease average packet drop rate and packet delay.

Reliability Analysis of Controller Area Network Based Systems—A Review

This paper reviews the research work done on the Reliability Analysis of Controller Area Network (CAN) based systems. During the last couple of decades, real-time researchers have extended schedulability analysis to a mature technique which for nontrivial systems can be used to determine whether a set of tasks executing on a single CPU or in a distributed system will meet their deadlines or not [1-3]. The main focus of the real-time research community is on hard real-time systems, and the essence of analyzing such systems is to investigate if deadlines are met in a worst case scenario. Whether this worst case actually will occur during execution, or if it is likely to occur, is not normally considered. Reliability modeling, on the other hand, involves study of fault models, characterization of distribution functions of faults and development of methods and tools for composing these distributions and models in estimating an overall reliability figure for the system [4]. This paper presents the research work done on reliability analysis developed with a focus on Controller-Area-Network-based automotive systems.

M/S Controller Area Network(CAN) System Using Shared-Clock Scheduler

The Controller Area Network (CAN) is a well established control network for automotive and automation control applications. Time-Triggered Controller Area Network (TTCAN) is a recent development which introduces a session layer,for message scheduling,to the existing CAN standard,which is a two layer standard comprising of a physical layer and a data link layer. TTCAN facilitates network communication in a time-triggered fashion,by introducing a Time Division Multiple Access style communication scheme. This allows deterministic network behavior,where maximum message latency times can be quantified and guaranteed. In order to solve the problem of determinate time latency and synchronization among several districted units in one auto panel CAN systems,this paper proposed a prototype design implementation for a shared-clock scheduler based on PIC18F458 MCU. This leads to improved CAN system performance and avoid the latency jitters and guarantee a deterministic communication pattern on the bus. The real runtime performance is satisfied.

Availability evaluation of controller area networks under the influence of intermittent connection faults

Controller area networks(CANs),as one of the widely used fieldbuses in the industry,have been extended to the automation field with strict standards for safety and reliability.In practice,factors such as fatigue and insulation wear of the cables can cause intermittent connection(IC)faults to occur frequently in the CAN,which will affect the dynamic behavior and the safety of the system.Hence,quantitatively evaluating the performance of the CAN under the influence of IC faults is crucial to real-time health monitoring of the system.In this paper,a novel methodology is proposed for real-time quantitative evaluation of CAN availability when considering IC faults,with the system availability parameter being calculated based on the network state transition model.First,the causal relationship between IC fault and network error response is constructed,based on which the IC fault arrival rate is estimated.Second,the states of the network considering IC faults are analyzed,and the deterministic and stochastic Petri net(DSPN)model is applied to describe the transition relationship of the states.Then,the parameters of the DSPN model are determined and the availability of the system is calculated based on the probability distribution and physical meaning of markings in the DSPN model.A testbed is constructed and case studies are conducted to verify the proposed methodology under various experimental setups.Experimental results show that the estimation results obtained using the proposed method agree well with the actual values.

Error Control Strategy in Ultrasonic Body Area Networks

Recently,ultrasonic waves had been introduced as the transmission medium in Body Area Networks(BANs) to reduce the incalculable damage caused by radio waves. However,the communications based on ultrasonic waves suffer from poor propagation of signals in air and consume too much energy. To address these limitations,firstly,we make the theoretical analysis to ensure ultrasonic waves could be used in BANs(UBANs). Then,we propose an error control strategy in UBANs to dynamically adjust the error control scheme and the Max-Retries based on the current channel state,which is called UECS. The UECS is based on IEEE 802.15.6 standards and considering the characteristics of ultrasonic waves in BANs. Simulation results show that UECS achieves better performance in terms of packet delivery ratio and energy consumption compared with the traditional strategies.

A Game Theoretic Approach for Inter-Network Interference Mitigation in Wireless Body Area Networks

Wireless Body Area Network(WBAN) is an emerging technology to provide real-time health monitoring and ubiquitous healthcare services. In many applications, multiple wireless body area networks have to coexist in a small area, resulting in serious inter-network interference. This not only reduces network reliability that is especially important in emergency medical applications, but also consumes more power of WBANs. In this paper, an inter-network interference mitigation approach based on a power control algorithm is proposed. Power control is modeled as a non-cooperative game, in which both inter-network interference and energy efficiency of WBANs are considered. The existence and uniqueness of Nash Equilibrium in the game are proved, and an optimal scheme based on best response is proposed to find its Nash Equilibrium. By coordinating the transmission power levels among networks under interference environment, the total system throughput can be increased with minimum power consumed. The effectiveness of the proposed method has been illustrated by simulation results, where the performance of the proposed approach is evaluated in terms of overall utility and power efficiency and convergence speed.

A novel strategy of smart manipulation by micro-scale oscillatory networks of the reactionary zones for enhanced extreme thrust control of the next-generation solid propulsion systems

The main aim of this research is to get a better knowledge and understanding of the micro-scale oscillatory networks behavior in the solid propellants reactionary zones. Fundamental understanding of the micro-and nano-scale combustion mechanisms is essential to the development and further improvement of the next-generation technologies for extreme control of the solid propellant thrust. Both experiments and theory confirm that the micro-and nano-scale oscillatory networks excitation in the solid propellants reactionary zones is a rather universal phenomenon. In accordance with our concept,the micro-and nano-scale structures form both the fractal and self-organized wave patterns in the solid propellants reactionary zones. Control by the shape, the sizes and spacial orientation of the wave patterns allows manipulate by the energy exchange and release in the reactionary zones. A novel strategy for enhanced extreme thrust control in solid propulsion systems are based on manipulation by selforganization of the micro-and nano-scale oscillatory networks and self-organized patterns formation in the reactionary zones with use of the system of acoustic waves and electro-magnetic fields, generated by special kind of ring-shaped electric discharges along with resonance laser radiation. Application of special kind of the ring-shaped electric discharges demands the minimum expenses of energy and opens prospects for almost inertia-free control by combustion processes. Nano-sized additives will enhance self-organizing and self-synchronization of the micro-and nano-scale oscillatory networks on the nanometer scale. Suggested novel strategy opens the door for completely new ways for enhanced extreme thrust control of the solid propulsion systems.

A novel intrusion detection model for the CAN bus packet of in-vehicle network based on attention mechanism and autoencoder

The attacks on in-vehicle Controller Area Network(CAN)bus messages severely disrupt normal communication between vehicles.Therefore,researches on intrusion detection models for CAN have positive business value for vehicle security,and the intrusion detection technology for CAN bus messages can effectively protect the invehicle network from unlawful attacks.Previous machine learning-based models are unable to effectively identify intrusive abnormal messages due to their inherent shortcomings.Hence,to address the shortcomings of the previous machine learning-based intrusion detection technique,we propose a novel method using Attention Mechanism and AutoEncoder for Intrusion Detection(AMAEID).The AMAEID model first converts the raw hexadecimal message data into binary format to obtain better input.Then the AMAEID model encodes and decodes the binary message data using a multi-layer denoising autoencoder model to obtain a hidden feature representation that can represent the potential features behind the message data at a deeper level.Finally,the AMAEID model uses the attention mechanism and the fully connected layer network to infer whether the message is an abnormal message or not.The experimental results with three evaluation metrics on a real in-vehicle CAN bus message dataset outperform some traditional machine learning algorithms,demonstrating the effectiveness of the AMAEID model.

Energy-Efficieng MAC Protocols for Wireless Body Area Networks: A Survey

In this paper, we provide a comprehensive survey of key energy-efficient Medium Access Control (MAC) protocols for Wireless Body Area Networks (WBANs). At the outset, we outline the crucial attributes of a good MAC protocol for WBAN. Several sources that contribute to the energy inefficiency of WBAN are identified, and features of the various MAC protocols qualitatively compared. Then, we further investigate some representative TDMA-based energy-efficient MAC protocols for WBAN by emphasizing their strengths and weaknesses. Finally, we conclude with a number of open research issues with regard to WBAN MAC layer.

Simulation of Optical Packet-Switched Metropolitan Area Network

This paper introduces architectures of two types optical packet switched metropolitan area networks and their media access control protocols. We have designed related network simulation systems. With these simulation systems, the characteristics and performance of the two MANs can be achieved.

MAC Layer Resource Allocation for Wireless Body Area Networks

Wireless body area networks （WBANs） can provide low-cost, timely healthcare services and are expected to be widely used for e-healthcare in hospitals. In a hospital, space is often limited and multiple WBANs have to coexist in an area and share the same channel in order to provide healthcare services to different patients. This causes severe interference between WBANs that could significantly reduce the network throughput and increase the amount of power consumed by sensors placed on the body. There-fore, an efficient channel-resource allocation scheme in the medium access control （MAC） layer is crucial. In this paper, we devel-op a centralized MAC layer resource allocation scheme for a WBAN. We focus on mitigating the interference between WBANs and reducing the power consumed by sensors. Channel and buffer state are reported by smartphones deployed in each WBAN, and channel access allocation is performed by a central controller to maximize network throughput. Sensors have strict limitations in terms of energy consumption and computing capability and cannot provide all the necessary information for channel allocation in a timely manner. This deteriorates network performance. We exploit the temporal correlation of the body area channel in order to minimize the number of channel state reports necessary. We view the network design as a partly observable optimization prob-lem and develop a myopic policy, which we then simulate in Matlab.

A Realistic ICT Network Design and Implementation in the Neighbourhood Area of the Smart Grid

The Smart Grid has three main characteristics, which are to some degree antagonistic. These characteristics are: provision of good power quality, energy cost reduction and improvement in the reliability of the grid. The need to ensure that they can be accomplished together demands a much richer ICT monitoring and control network than the current system. In this paper we particularly investigate the design and deployment of the ICT system in the urban environment, specifically in a university campus that is embedded in a city, thus it represents the Neighbourhood Area Network (NAN) level of the Smart Grid. In order to design an ICT infrastructure, we have introduced two related architectures: namely communications network architecture and a software architecture. Having access to the characteristics of a real NAN guides us to choose appropriate communication technologies and identify the actual requirements of the system. To implement these architectures at this level we need to gather and process information from environmental sensors (monitoring e.g. temperature, movement of people and vehicles) that can provide useful information about changes in the loading of the NAN, with information from instrumentation of the Power Grid itself. Energy constraints are one of the major limitations of the communication network in the Smart Grid, especially where wireless networking is proposed. Thus we analyse the most energy efficient method of collecting and sending data. The main contribution of this research is that we propose and implement an energy efficient ICT network and describe our software architecture at the NAN level, currently very underdeveloped. We also discuss our experimental results. To our knowledge, no such architectures have yet been implemented for collecting data which can provide the basis of Decision Support Tools (DSTs).

Resource Exhaustion Attack Detection Scheme for WLAN Using Artificial Neural Network

IEEE 802.11 Wi-Fi networks are prone to many denial of service(DoS)attacks due to vulnerabilities at the media access control(MAC)layer of the 802.11 protocol.Due to the data transmission nature of the wireless local area network(WLAN)through radio waves,its communication is exposed to the possibility of being attacked by illegitimate users.Moreover,the security design of the wireless structure is vulnerable to versatile attacks.For example,the attacker can imitate genuine features,rendering classificationbased methods inaccurate in differentiating between real and false messages.Althoughmany security standards have been proposed over the last decades to overcome many wireless network attacks,effectively detecting such attacks is crucial in today’s real-world applications.This paper presents a novel resource exhaustion attack detection scheme(READS)to detect resource exhaustion attacks effectively.The proposed scheme can differentiate between the genuine and fake management frames in the early stages of the attack such that access points can effectively mitigate the consequences of the attack.The scheme is built through learning from clustered samples using artificial neural networks to identify the genuine and rogue resource exhaustion management frames effectively and efficiently in theWLAN.The proposed scheme consists of four modules whichmake it capable to alleviates the attack impact more effectively than the related work.The experimental results show the effectiveness of the proposed technique by gaining an 89.11%improvement compared to the existing works in terms of detection.

治涝导向的平原河网地区海绵城市实施路径探索——以宿迁市国家海绵城市示范系统化实施方案为例

针对平原河网地区的排涝特征与问题,在梳理构建治涝片区排水格局的基础上分类提出了针对性的治涝策略。对于具有一定坡度。在多数时期可以实现自排的治涝片区,采用“上蓄+中分+下排”模式,分段缓解排涝压力,提高城区排涝标准对于整体地势低洼,在多数时期很难自排的治涝片区,采用“建闸营圩,蓄排并举”模式,将雨水排口分散建设小型雨水泵站的模式调整为片区排涝主干河道末端建设大型排涝泵站的模式,充分利用片区内部河网的输送和调蓄能力,增强城区应对暴雨的韧性。

基于MobileViT轻量化网络的车载CAN入侵检测方法

车载控制区域网络(controller area network,CAN)总线因缺少安全措施而易被攻击,因此入侵检测系统(intrusion detection system,IDS)在保护车载CAN总线免受网络攻击中发挥着重要作用.现有基于深度学习的车载CAN总线入侵检测方法存在资源开销大和延迟较高的问题.为减少检测延迟,提高检测率,提出一种利用改进的轻量化MobileViT模型对车载CAN总线进行入侵检测的方法.首先,将攻击流量可视化为彩色图,再使用GELU替换MobileViT的MV2模块中常规ReLU6,从而作为该模块的激活函数,可有效解决神经元死亡问题,提升模型收敛速度.使用指数衰减自动更新学习率,并通过迁移学习加速训练过程实现对彩色图分类,从而达到对入侵行为的检测.基于CAR-HACKING DATASET数据集的实验表明,改进后的MobileViT在消耗较少算力的情况下对入侵行为的检测准确率为100%,模型参数仅为2.12 MB,平均响应时间仅为1.6 ms,节省了训练资源,并保证了检测的准确率.

山区铁路隧道钻爆法施工安全风险演化路径及防控研究

山区铁路隧道钻爆法施工安全风险突出,探索安全风险演化路径并提出安全风险防控措施,对减少安全事故发生意义重大。针对山区铁路隧道钻爆法施工特点,运用文本挖掘分析历史安全事故资料、铁路标准规范资料、现场安全风险评估报告、相关研究文献资料等,结合“4M1E”理论和专家经验识别山区铁路隧道钻爆法施工主要安全风险因素和安全风险事件。采用质性分析法,结合现场调研和专家访谈,提取安全风险因素间、安全风险事件间、安全风险因素及事件间相互关系,构建山区铁路隧道钻爆法施工安全风险演化网络模型。基于风险演化理论、复杂网络理论等,利用度中心性、介数中心性、聚类系数、特征向量中心性、中间中心度等多项指标分析山区铁路隧道钻爆法施工安全风险演化网络节点重要度、边的关键性,从而确定关键链演化路径,并提出安全风险防控措施。研究结果表明:山区铁路隧道钻爆法施工安全风险包括人员、设备、技术、管理、环境5类共41个主要安全风险因素和塌方、突泥涌水等6个主要安全风险事件,确定了安全风险演化网络中8个关键节点、20条关键边和3条关键链,针对关键链风险演化路径提出了安全风险防控措施,为提高山区铁路隧道钻爆法施工安全风险管理水平提供参考。

大尺度圩田水网地区特色生态空间单元解析及传承策略研究——以高淳为例

我国幅员辽阔,各个地区的乡村空间各具特色。在诸如江浙一带的圩田水网地区便形成了独特的生态-聚落空间布局模式。文章以大尺度高淳水网地区的聚落空间为研究对象,在分析现状水系网络、农田体系、圩堤陆路等生态要素共同作用下的乡村特色空间基础上,从维持水田格局的特色性、分类引导聚落选址和堤路网体系优化布局三个方面,分别探究传承乡村特色空间的策略与导控方法,旨在为我国其他相似圩田水网地区的乡村特色空间传承提供实践指导方法和参考借鉴意义。

苏州市南星湖片区水网乡村景观生态风险时空动态变化与分区管控研究

苏南地区是中国城镇发展的先行区,具有复杂的水网空间特征,呈现出一定的地域特殊性。伴随快速化城镇发展,水网乡村景观格局破碎化、生态风险增加等问题突显,基于景观生态风险评价提出分区管控策略是维护地区生态系统稳定性的有效方法。以苏州市南星湖片区为例,运用景观格局指数构建景观生态风险评价模型,分析研究区2010–2020年景观生态风险的时空分布特征,并运用CA-Markov模型对2030年景观生态风险空间分布进行模拟预测,提出时空动态变化下的空间分区管控策略。研究表明2010–2020年南星湖片区景观生态风险呈上升趋势,高、较高风险面积占比分别增加7.77%、4.58%,中、较低风险面积有所下降,多向更高一级风险转移,其中荷花荡、甫港村等建设用地扩张区域风险等级上升较显著。2030年情景模拟下景观生态风险等级不断上升,高、较高、中风险范围逐步扩张,面积占比分别增加3.3%、0.23%、2.16%,较低、低风险面积则逐步缩减,相较于现状,2030年情景模拟下风险等级上升区主要集中于南星湖、汾湖周边等建设用地与水域镶嵌分布区域。将2020年与2030年土地利用模拟下的景观生态风险空间分布进行叠置分析,基于现状与潜在风险区识别结果并提出时空动态演变下的空间分区管控策略,为实现苏南水网乡村生态保护和合理开发提供科学指导。

基于BEGAN的汽车CAN网络入侵检测数据增强方法研究

针对目前汽车CAN网络入侵检测算法因攻击样本缺少而导致数据不平衡问题,提出一种基于BEGAN的CAN入侵检测数据增强方法,引入one-hot编码将CAN报文特征图像化,结合构建的生成对抗网络,生成与真实攻击格式一致且内容差异的有效样本。通过采集实车数据作为真实样本进行训练,从特征图、t-SNE可视化、统计学分析和分类器验证角度验证了所生成的增强数据集的实用性,可提高入侵检测分类器准确率;与传统过采样算法含随机过采样(ROS)、合成少数过采样(SMOTE)、SMOTE-ENN、自适应合成过采样(ADASYN)相比,具有更高的准确率。

基于鸿蒙系统的无人方程式赛车远程监控与数据管理系统开发

为了提高无人方程式赛车运行的安全性,设计了一种基于鸿蒙系统的无人方程式赛车远程监控与数据管理系统。该系统主要包括数据采集软件、远程监控平台、云数据库。数据采集软件使用鸿蒙系统开发,通过使用控制器局域网(controller area network,CAN)总线传输、蓝牙传输、WebSocket协议、HTTP协议,实现对CAN数据的解析、显示、转发。监控系统使用Spring Boot框架开发,实现对无人方程式赛车的远程监控。云数据库使用MySQL数据库开发,实现无人方程式赛车数据的快速存储。测试结果表明,该套系统可以实现对无人方程式赛车的远程监控,实现十万级以上数据量低延迟储存,数据丢失率平均为0.0424%。目前,该套系统已经应用到无人方程式赛车的调试中。