Packet Loss Research Articles

Моделювання систем реального часу з використанням RUDP протоколу передачі даних

The efficiency of real-time systems makes them applicable in various fields by utilizing protocols for data transmission. Well-known transport layer protocols include Transmission Control Protocol (TCP) and User Datagram Protocol (UDP), which facilitate such transmission. However, there are challenges in using these protocols [1] in real-time systems where data rapidly changes during application execution. Exclusively using one of these protocols adversely affects the stable operation of the application and increases the risk of data obsolescence. The objective of this work is to develop and model a data transmission subsystem for real-time systems that utilizes the Reliable UDP (RUDP) protocol [2] for data synchronization. Implementing the RUDP network protocol in the subsystem addresses network issues such as delay, packet loss, and duplication in the most optimal way during real-time data synchronization between sensors and the server, reducing the load on bandwidth. The tasks of the developed subsystem, consisting of a server and a client, include: reading user-specified system data, reliable message transmission between the server and the client using sockets for RUDP protocol operation, ensuring the most optimal message delivery in case of packet loss, subsystem operation modeling compared to well-known UDP and TCP protocols. The simulation results reveal that the maximum time spent by the subsystem is 2.03 seconds for the RUDP protocol and 6.22 seconds for the TCP protocol. Therefore, RUDP is recommended for data transmission in the future. In the event of message loss, retransmission occurs exponentially, calculated using the proposed formula. If the initial transmission occurs immediately, subsequent times exponentially increase but remain collectively less than the transmission time for the TCP protocol.

A Framework for Mitigating Gray Hole Attack On Mobile Ad Hoc Networks

posing a significant challenge to network performance and reliability. In a gray hole attack, a malicious node selectively drops packets while forwarding others, leading to increased packet loss and latency. This paper presents a novel Gray Hole Prevention algorithm designed to detect and mitigate the effects of such attacks, thereby enhancing the security and efficiency of MANETs. The proposed algorithm integrates existing techniques, specifically the Secure Detection Prevention and Elimination Gray Hole (SDPEGH) approach, with proactive measures to improve detection accuracy and minimize the risk of blacklisting legitimate nodes. Extensive simulations were conducted using the NS-2 simulation tool, comparing the performance of the proposed algorithm against traditional methods. The results demonstrate a significant improvement in network performance, with the GRAY-HP algorithm achieving a PDR of 92%, compared to 78% for the SDPEGH algorithm, representing an increase of 18%. Additionally, the throughput improved by 25%, reaching 85 kbps, while the energy consumption was reduced by 15%, indicating a more efficient use of resources. The routing overhead was also minimized by 20%, showcasing the algorithm's effectiveness in maintaining network stability. This research contributes to the field of network security by providing a robust solution to gray hole attacks, thereby enhancing the reliability and performance of MANETs. The findings underscore the importance of proactive security measures in dynamic and decentralized environments, paving the way for future advancements in secure communication protocols for mobile networks.

SDERP: Stable‐aware differential evolution‐based routing protocol for mobile wireless networks

SummaryA mobile ad hoc network (MANET) is a network with non‐wired communications and non‐centralized administration where all its nodes are mobile. Firstly, one of the leading drawbacks of wireless networks is their energy consumption because the constituent nodes of the network have a restricted battery capacity yet greater consumption caused by the mobility of the nodes, their processing power, the frequent sending of data, and so on. Secondly, data packets may be lost due to traffic, noise, or the mobility of nodes, whose data transmission in real‐time applications would be compromised by this loss. In order to resolve the problem of energy consumption and that of the loss of data packets for MANETs, we propose a new stable‐aware differential evolution‐based routing protocol (SDERP). We include a fitness function to select the best new path from all new paths issued at the end of this algorithm. This fitness function is based on energy constraints and link stability. The performance of our proposal is compared with OPAOMDV‐EE, FT‐AORP, EE‐LB‐AOMDV and AOMDV. The results show that our SDERP has better network performance than the other routing protocols. Specifically, it obtains a packet delivery ratio that is higher by up to 17%, an overhead ratio reduced by up to 33%, an energy efficiency better by up to 39%, and end‐to‐end delay reduced by up to 16%.

Implementation of Load Balancing Using the PCC (Per Connection Classifier) Method on Computer Networks to Improve Responsiveness

Dependence on a single ISP can lead to the risk of internet disconnection, necessitating a solution to enhance network performance and responsiveness. This research explores the implementation of load balancing using the Per Connection Classifier (PCC) method to improve the responsiveness of computer networks utilizing three ISPs (Internet Service Providers). The test results indicate that the PCC method across the three ISPs can increase throughput by 9.32 Mbps, reduce delay by 43.54 ms, and decrease jitter by 74.17 ms while packet loss remains stable at 0.0%. Additionally, the recursive gateway failover technique in PCC load balancing demonstrates a significant increase in throughput up to 83.3 Mbps, a reduction in delay by 0.27 ms, and a reduction in jitter by 1.15 ms. Packet loss remains stable at 0.0% under varying ISP conditions. Moreover, a comparison between the PCC and PBR methods with the least connection algorithm shows that both methods effectively enhance network responsiveness, with the PCC method exhibiting superior performance in throughput.

Evaluating the Impact of Mid-Link Bandwidth Constraints on Video Streaming Performance Using NS2

A detailed simulation study of video streaming over a simple best-effort network topology is conducted using Network Simulator 2 (NS2). The simulation involves transmitting a video stream across a simple network topology where the central link's data rate varies to simulate different cases. The network topology consists of : node 0 (sender), node 3 (receiver), and nodes 1 and 2 as intermediate nodes. The study aims to examine the impact of mid-link bandwidth variations on packet loss during video transmission. Specifically, the mid-link connecting nodes experience bandwidth reductions to 10, 8, and 5 Mbps. By adjusting the mid-link bandwidth, we simulate scenarios that typically cause packet drops and measure the resulting packet loss for each bandwidth configuration. The simulation results provide insights into how bandwidth constraints affect video streaming performance, emphasizing the correlation between reduced mid-link capacity and increased packet drop rates. The results indicate that maintaining the video encoding constant while reducing the mid-link bandwidth to half of its required capacity results in an approximately 30% rise in dropped packets and a fivefold increase in end-to-end delay. This significant packet loss severely degrades the video quality, highlighting the importance of adequate mid-link bandwidth for maintaining high-quality transmission.

Dynamic priority-based bandwidth allocation scheme for machine type communications

The burgeoning realm of Machine Type Communications (MTC) has ushered in a paradigm shift in wireless communication, necessitating innovative strategies to efficiently manage diverse application requirements. This paper presents a pioneering Dynamic Priority-based Bandwidth Allocation (DPBA) scheme tailored specifically for MTC scenarios, encompassing both MTC and Human Type Communications (HTC) coexistence. DPBA employs an adaptive framework addressing dynamic MTC traffic, optimizing resource use while meeting latency constraints and sporadic data patterns. By dynamically prioritizing MTC applications based on requirements, the scheme allocates bandwidth for reliable data delivery. DPBA extends to MTC and HTC coexistence, managing diverse quality demands. This underlines its versatility and capacity to serve distinct needs in a shared spectrum. To substantiate its performance, the DPBA scheme is rigorously evaluated against a spectrum of related allocation methods like Proportional Fairness (PF), Static Priority Scheduling (SPS), and the Machine Learning-based Scheme (MLS), DPBA excels in simulations, minimizing packet loss, latency, enhancing throughput and ensuring fairness, surpassing benchmarks. This research underscores the critical importance of tailored bandwidth allocation strategies in advancing MTC and HTC coexistent environments. With its adaptability, efficiency, and remarkable performance, the DPBA scheme emerges as a cornerstone in the trajectory of wireless communication networks, catering to the distinct requirements of both MTC and HTC applications.

User-dedicated optical path switching with optical-wireless cooperative control for low-latency and seamless handover

We propose a user-dedicated optical path switching technique for low-latency and seamless handover in the radio access network (RAN) with the all-photonic network (APN). The APN is a network that connects end points directly with optical paths of dedicated wavelengths assigned to each user and provides large-capacity and low-latency connections. As mobile systems beyond 5th generation (5G) and 6th generation (6G) will require extremely low latency, applying the APN to the RAN is promising to achieve this. However, the RAN with the APN has a challenge in optical path switching during the handover procedure of mobile systems because optical switches that compose the APN do not have an Internet protocol (IP) layer function that enables routing control for handover in the conventional router network. Our proposed optical path switching technique to solve this challenge utilizes optical-wireless cooperative control and switches an optical path dedicated to user equipment (UE) executing handover in conjunction with its handover procedure. The key point of the proposed technique is that a next generation node B (gNB) transmits an optimal-timing optical path switching trigger to the optical switch. We experimentally demonstrated the generation of a dedicated optical path for UE in the RAN with the APN as a premise to enable the proposed optical path switching technique. To evaluate the feasibility and effectiveness of the proposed optical path switching technique, we experimentally compared the optical switch and router in terms of latency performance, packet loss, and packet misdirection in the path switching during handover. The results indicated successful optical path switching during handover without packet loss and packet misdirection while reducing the latency per single network equipment by 99%, from 4 µs for the router to 45 ns for the optical switch.

Dynamic event‐triggered model‐free adaptive control for networked control systems with random packet loss

AbstractA novel dual‐channel dynamic event‐triggered model‐free adaptive control method with compensation is proposed for nonlinear networked control systems (NCSs) subjected to random packet loss. In order to tackle the issue of redundant data transmission, a dual‐channel triggering control framework is designed, where data transmission only occurs upon meeting the triggering conditions. Compared with the traditional static event‐triggered schemes with fixed triggering thresholds, the proposed method allows for dynamically adjustable triggering thresholds. This means that the number of data transmissions in the forward and feedback channels can be further reduced. In addition, considering the detrimental impact of random packet loss and output event‐triggered on the system, compensation is applied to the system's output data using the linear data model of the nonlinear system, which is directly derived from I/O data without incorporating any other mechanistic model information, thereby ensuring optimal control performance. In contrast to existing results, the proposed control strategy can enhance system performance while conserving network communication resources. The effectiveness and superiority of the proposed scheme have been validated through two simulations.

Longitudinal motion calibration for connected and automated vehicles in the presence of packet loss

Connected and automated vehicles (CAVs) equipped with vehicle-to-vehicle wireless communication can enhance traffic stability by effectively shortening the following distances. However, packet loss can lead to decline in performance and efficiency, potentially affecting driving safety. To address the destabilising impact on longitudinal motion calibration during packet loss, this paper proposes a dual chain calibration framework (DCCF). This framework consists of a transmission chain for real-time calibration through compensation calculations and a storage chain for periodic auxiliary calibration by reproducing packet loss data. The effectiveness is validated through a series of simulation experiments. The results demonstrate that the proposed DCCF, irrespective of the packet loss rate (PLR) and in both ideal and packet loss communication environments, can effectively maintain a stable following.

Mustang: Improving QoE for Real-Time Video in Cellular Networks by Masking Jitter

The advent of 5G and interactive live broadcasting has led to a growing trend of people preferring real-time interactive video services on mobile devices, particularly mobile phones. In this work, we measure the performance of Google congestion control (GCC) in cellular networks, which is the default congestion control algorithm for Web Real-Time Communication (WebRTC). Our measurements show that GCC sometimes makes bitrate decisions which are harmful to quality of experience (QoE) in cellular networks with high jitter. We further find that the frame delivery time (FDT) in the player can mitigate network jitter and maintain QoE. Moreover, the receiving rate is better to reflect the network congestion than RTT in cellular networks. Based on these measurements and findings, we propose Mustang, an algorithm designed to overcome the jitter in cellular networks. Mustang makes use of the FDT and receiving rate as feedback information to the sender. Then the sender adjusts its sending rate based on the information to guarantee QoE. We have implemented Mustang in WebRTC and evaluated it in both emulated and real cellular networks. The experimental results show that Mustang can improve WebRTC’s QoS and QoE performance. For QoS, Mustang increases the sending rate by 72.1% and has similar RTT and packet loss when compared with GCC, while it is about 30% better for QoE.

Impact of Wireless Network Packet Loss on Real-Time Video Streaming Application: A Comparative Study of H.265 and H.266 Codecs

The transmission of real-time videos over wireless networks is prone to the negative consequences of packet loss and delay, which can have a potential effect on the video quality during streaming. These impairments can lead to interruptions, buffering, and degradation of visual and auditory elements, resulting in an unsatisfactory user experience. In this paper, we aim to address the challenges associated with packet loss and delay parameters in wireless networks, and propose an approach to alleviate their impact on real-time video transmission. The proposed approach involves utilizing the H.265/H.266 video coding standards. For Versatile Video Coding (VVC), a patch support for VVdeC and VVenC to FFmpeg (Fast Forward Moving Picture Expert Group) is added. As a result, FFmpeg is used to encode, stream and decode all videos. Raw videos of 2K qualities are encoded based on the adaptive quantization (QP) for the above-mentioned codecs. By selecting optimal transmission data based on various network conditions, this approach enhances the Quality of Experience (QoE) for end-users while minimizing resource usage in the wireless network. Furthermore, the proposed approach selects the codec standards according to their bitrates and frame rates. Simulation results indicate that the proposed approach has a significant improvement for real-time video streaming over wireless networks to satisfy the end user experience. The approach also outperforms other related work by gaining a PSNR of +12 dB for H.265 and +13 dB for H.266 when the network packet loss is 1%.

Development of Synchronization Selection Method in IoT with Secure Channel Bidirectional Communication

Background: The rapid development of wireless communications and mobile computation has given rise to the novel Internet of Things (IoT) systems, which is causing considerable research attention and industrial development. However, the lack of synchronization between the timers of IoT devices compromises the network's security. Aim: The purpose of this patent application is to present a technique for synchronizing the timepieces of IoT gadgets and establishing a secure channel for the transmission of data from source to destination. Objective: This study proposes a Synchronization Selection Method (SSM) for IoT systems to enhance network security and reduce packet loss. Methods: The method utilizes time-lay synchronization and RSA algorithm-based secure channel establishment. Time lay is a technique that was developed for IoT devices to achieve efficient clock synchronization of sensor nodes. Before synchronizing the sensor nodes' timings, the cluster leaders initiate the process. Utilizing a finite number of nodes, the proposed method was executed in MATLAB. Results: Time-lay synchronization involves all network nodes synchronizing their clocks with a third-party clock. In the context of time-lay synchronization, the term “third-party clock” refers to a single specific point that contains the time signal that all nodes in the network use as a reference. This third-party clock is outside of the network nodes and acts as the standard for the precise and synchronized time within the network. Therefore, it can be deduced that each of the techniques possesses its advantages and disadvantages. Each of the synchronization techniques has the potential to significantly benefit the IoT by offering smart clock synchronization that is more secure. Experimental results demonstrate that the proposed method improves throughput and reduces packet loss compared to existing techniques. Conclusion: The potential of this patent is highly significant for solving the synchronization problem of IoT devices and enhancing network security with decreased network packet loss. Other: The SSM would be assessed using the parameters of packet loss and throughput.

Real-time optical-wireless cooperative switching on wireless quality degradation for end-to-end video delay guarantee

This paper proposes an optical-wireless cooperative control method to guarantee end-to-end delays in the case of radio quality degradation in wireless networks by switching optical paths. The method leverages the control information from mobile systems to dynamically switch the optical path between the distributed unit (DU) and the far aggregated central unit (CU) to another path forward to the nearest virtualized central unit (vCU) at the edge sight, on the basis of the radio quality. This enables demanding applications that require a combination of high bandwidth and low latency, such as remote operation using drones. Preliminary simulations were conducted to investigate the effect of quality degradation in the wireless domain and the potential effectiveness of the proposed delay compensation method. In the experiments conducted to verify the feasibility of the proposed method, the results demonstrated that the optical path switching was successfully performed without packet loss and within 4 ms from the transmission of the control frame. The proposed method was also able to correctly switch back when the processing rate of mobile edge computing (MEC) was exceeded after the radio quality recovered. This study demonstrates the effectiveness of further coordination between wired and wireless control for a wider range of real-time applications using video.

Network impact analysis on the performance of Secure Group Communication schemes with focus on IoT

Secure and scalable group communication environments are essential for many IoT applications as they are the cornerstone for different IoT devices to work together securely to realize smart applications such as smart cities or smart health. Such applications are often implemented in Wireless Sensor Networks, posing additional challenges. Sensors usually have low capacity and limited network connectivity bandwidth. Over time, a variety of Secure Group Communication (SGC) schemes have emerged, all with their advantages and disadvantages. This variety makes it difficult for users to determine the best protocol for their specific application purpose. When selecting a Secure Group Communication scheme, it is crucial to know the model’s performance under varying network conditions. Research focused so far only on performance in terms of server and client runtimes. To the best of our knowledge, we are the first to perform a network-based performance analysis of SGC schemes. Specifically, we analyze the network impact on the two centralized SGC schemes SKDC and LKH and one decentralized/contributory SGC scheme G-DH. To this end, we used the ComBench tool to simulate different network situations and then measured the times required for the following group operations: group creation, adding and removing members. The evaluation of our simulation results indicates that packet loss and delay influence the respective SGC schemes differently and that the execution time of the group operations depends more on the network situations than on the group sizes.

ANALIZA STATYSTYK SIECI KOMPUTEROWYCH W CELU IDENTYFIKACJI PRZEPŁYWÓW INFORMACJI ZAKŁÓCAJĄCYCH STABILNOŚĆ W WOJSKOWYCH SIECIACH LOKALNYCH

The increasing complexity and scope of military computer networks necessitate robust methods to ensure network stability and security. This study presents a comprehensive analysis of computer network statistics in military local networks to develop a method for detecting information flows that disrupt stability. By leveraging advanced statistical techniques and machine learning algorithms, this research aims to enhance the cybersecurity posture of military local networks globally. Military networks are vital for communication, data exchange, and operational coordination. However, the dynamic nature of network traffic and the persistent threat of cyberattacks pose significant challenges to maintaining network stability. Traditional monitoring techniques often fail to meet the unique requirements of military networks, which demand high levels of security and rapid response capabilities. This study employs a multi-faceted approach to detect anomalies in network traffic, utilizing statistical methods such as Z-score analysis, Principal Component Analysis (PCA), and Autoregressive Integrated Moving Average (ARIMA) models. Machine learning techniques, including Support Vector Machines (SVM), Random Forests, Neural Networks, K-means clustering, and Reinforcement Learning, are also applied to identify patterns indicative of stability-disrupting information flows. The integration of statistical and machine learning methods forms a hybrid model that enhances anomaly detection, providing a robust framework for network security. The research problem is formulated as follows: does data collection include comprehensive network traffic data from various segments of military local area networks, including packet flows, transmission rates, and error rates over a specified period? Statistical analysis identifies patterns in the network traffic, which are then used to train machine learning models to classify normal and abnormal traffic. The research hypothesis states that machine learning models achieve high accuracy in detecting stability-disrupting information flows, with a precision rate exceeding 90%. The models identified several instances of stability-disrupting events, correlating these with known security incidents to validate the effectiveness of the detection method. This study underscores the importance of continuous monitoring and analysis of network statistics to ensure stability and security. The proposed method can be integrated with existing network monitoring and intrusion detection systems, providing a comprehensive approach to network security. Future research can build on these findings to develop more sophisticated models and explore additional factors influencing network stability, including the incorporation of advanced machine learning techniques, such as deep learning, and the exploration of other network metrics, like latency and packet loss. This comprehensive approach aims to enhance the security and operational reliability of military local networks.

Environmental noise monitoring using distributed hierarchical wireless acoustic sensor network

Acoustic noise pollution is one of many problems people face as cities grow. Long-term noise exposure can result in a series of physical and mental health diseases that are highly harmful to foetuses and newborns. Hence, many IoT-based wireless sensor network systems have been proposed for automated monitoring for long-term operation. However, these systems suffer from weaknesses in functionality, power consumption, costs, and scalability, which hinder large-scale deployment. In this study, we propose a distributed hierarchical wireless acoustic sensor network for environmental noise monitoring to do sound classification and A-weighted sound-pressure-level measurement to address the shortcomings of existing systems. A series of tests and comparisons are performed in diagnosing the performance with respect to recording continuity, packet loss, recording quality, accuracy on A-weighted sound pressure level calculations, and costs. Results show that this proposed network structure is feasible as a part of hardware implementation in a large-scale, low-cost, and high-scalable environmental noise monitoring system to classify sound.

Quality of Service-Aware Multi-Objective Enhanced Differential Evolution Optimization for Time Slotted Channel Hopping Scheduling in Heterogeneous Internet of Things Sensor Networks.

The emergence of the Internet of Things (IoT) has attracted significant attention in industrial environments. These applications necessitate meeting stringent latency and reliability standards. To address this, the IEEE 802.15.4e standard introduces a novel Medium Access Control (MAC) protocol called Time Slotted Channel Hopping (TSCH). Designing a centralized scheduling system that simultaneously achieves the required Quality of Service (QoS) is challenging due to the multi-objective optimization nature of the problem. This paper introduces a novel optimization algorithm, QoS-aware Multi-objective enhanced Differential Evolution optimization (QMDE), designed to handle the QoS metrics, such as delay and packet loss, across multiple services in heterogeneous networks while also achieving the anticipated service throughput. Through co-simulation between TSCH-SIM and Matlab, R2023a we conducted multiple simulations across diverse sensor network topologies and industrial QoS scenarios. The evaluation results illustrate that an optimal schedule generated by QMDE can effectively fulfill the QoS requirements of closed-loop supervisory control and condition monitoring industrial services in sensor networks from 16 to 100 nodes. Through extensive simulations and comparative evaluations against the Traffic-Aware Scheduling Algorithm (TASA), this study reveals the superior performance of QMDE, achieving significant enhancements in both Packet Delivery Ratio (PDR) and delay metrics.

Modelling of Cyber Attack Detection and Response System for 5G Network Using Machine Learning Technique

The rapid increase in the adoption of 5G networks has revolutionized communication technologies, enabling high-speed data transmission and connectivity across various domains. However, the advent of 5G technology comes with an increased risk of cyber-attacks and security breaches, necessitating the development of robust defence mechanisms to safeguard network infrastructure and mitigate potential threats. The work presents a novel approach for modelling a cyber-attack response system tailored specifically for 5G networks, leveraging machine learning techniques to enhance threat detection and response capabilities. The study introduced innovative methodologies, including the integration of standard backpropagation and dropout regularization technique. Furthermore, an intelligent cyber threat classification model that proactively detects and mitigates malware threats in 5G networks was developed. Additionally, a comprehensive cyber-attack response model designed to isolate threats from the network infrastructure and mitigate potential security risks was formulated. The result of testing the response algorithm with simulation, and considering quality of service such as throughput, latency and packet loss, showed 80.05%, 24.9ms and 4.09% respectively. During system integration of the model on 5G network with stimulated malware, the throughput reported 71.81%. Also, packet loss reported loss rate of 23.18%, while latency reported 178.98ms. Our findings contribute to the advancement of cybersecurity in 5G environments and lay the foundation for the development of robust cyber defence systems to safeguard critical network infrastructure against emerging threats.

Privacy-Preserving Authentication Based on PUF for VANETs

The secret key is stored in an ideal tamper-proof device so that a vehicle can implement a secure authentication with the road-side units (RSUs) and other drivers. However, some adversaries can capture the secret key by physical attacks. To resist physical attacks, we propose a physical-preserving authentication based on a physical unclonable function for vehicular ad hoc networks. In the proposed scheme, a physical unclonable function is deployed on the vehicle and the RSU to provide a challenge–response mechanism. A secret key is only generated by the challenge–response mechanism when it is needed, which eliminates the need to store a long-term secret key. As a result, this prevents secret keys from being captured by adversaries, improving system security. In addition, route planning is introduced into the proposed scheme so that a vehicle can obtain the authentication key of RSUs on its route before vehicle-to-infrastructure authentication, which greatly speeds up the authentication when the vehicle enters the RSUs’ coverage. Furthermore, a detailed analysis demonstrates that the proposed scheme achieves security objectives in vehicular ad hoc networks. Ultimately, when contrasted with similar schemes, the performance assessment demonstrates that our proposed scheme surpasses others in terms of computational overhead, communication overhead and packet loss rate.

Compensation control of commercial vehicle platoon considering communication delay and response lag

The real-time accurate control of vehicle is of great significance for the stability of platoon driving. To address the impact of random time-varying communication delays, communication packet loss, data disorder, and significant response lag of commercial vehicle on platoon control performance in non-ideal communication environment, a novel compensation control method for commercial vehicle platoon is proposed to overcome the abovementioned issues. The proposed method significantly improves the impact of communication issues and vehicle response lag on platoon control, ensuring platoon safety while reducing inter-vehicle spacing and spacing error, and maintaining platoon stability. In addition, this method combines the comprehensive compensation mechanism with the Distributed Model Predictive Controller (DMPC), avoiding the establishment of additional compensation control modules and effectively reducing the computational burden. The results under emergency braking condition show that, compared with the method without compensation, the proposed method significantly reduces inter-vehicle spacing and spacing error, reducing the average maximum spacing error from 29.25 m to 1.44 m, shortening the error convergence time of the platoon by 28 %, and ensuring platoon stability. Additionally, compared to the compensation method based on Kalman Filtering (KF) and Smith predictor, the proposed method can reduce the average maximum spacing error by 60 % while maintaining similar convergence time and platoon stability.