Digital Communications and Networks最新文献_第9页

Performance analysis of RIS-assisted dual-hop mixed FSO-RF UAV communication systems ris辅助双跳混合FSO-RF无人机通信系统性能分析

IF 7.5 2区计算机科学 Q1 TELECOMMUNICATIONS

Digital Communications and Networks

Pub Date : 2025-08-01 DOI: 10.1016/j.dcan.2025.02.001

Donghyun Kim , Hwi Sung Park , Bang Chul Jung

In this paper, we investigate a Reconfigurable Intelligent Surface (RIS)-assisted Free-Space Optics–Radio Frequency (FSO–RF) mixed dual-hop communication system for Unmanned Aerial Vehicles (UAVs). In the first hop, a source UAV transmits data to a relay UAV using the FSO technique. In the second hop, the relay UAV forwards data to a destination Mobile Station (MS) via an RF channel, with the RIS enhancing coverage and performance. The relay UAV operates in a Decode-and-Forward (DF) mode. As the main contribution, we provide a mathematical performance analysis of the RIS-assisted FSO–RF mixed dual-hop UAV system, evaluating outage probability, Bit-Error Rate (BER), and average capacity. The analysis accounts for factors such as atmospheric attenuation, turbulence, geometric losses, and link interruptions caused by UAV hovering behaviors. To the best of our knowledge, this is the first theoretical investigation of RIS-assisted FSO–RF mixed dual-hop UAV communication systems. Our analytical results show strong agreement with Monte Carlo simulation outcomes. Furthermore, simulation results demonstrate that RIS significantly enhances the performance of UAV-aided mixed RF/FSO systems, although performance saturation is observed due to uncertainties stemming from UAV hovering behavior.

本文研究了一种用于无人机的可重构智能表面（RIS）辅助自由空间光学-射频（FSO-RF）混合双跳通信系统。在第一跳中，源无人机使用FSO技术向中继无人机传输数据。在第二跳中，中继无人机通过射频信道将数据转发到目标移动站（MS）， RIS增强了覆盖范围和性能。中继无人机以解码和转发（DF）模式操作。作为主要贡献，我们提供了ris辅助FSO-RF混合双跳无人机系统的数学性能分析，评估了中断概率，误码率（BER）和平均容量。该分析考虑了由无人机悬停行为引起的大气衰减、湍流、几何损失和链路中断等因素。据我们所知，这是ris辅助FSO-RF混合双跳无人机通信系统的第一个理论研究。我们的分析结果与蒙特卡罗模拟结果非常吻合。此外，仿真结果表明，RIS显著提高了无人机辅助混合RF/FSO系统的性能，尽管由于无人机悬停行为的不确定性导致性能饱和。

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引用次数: 0

Environment-aware streaming media transmission method in high-speed mobile networks 高速移动网络中环境感知流媒体传输方法

IF 7.5 2区计算机科学 Q1 TELECOMMUNICATIONS

Digital Communications and Networks

Pub Date : 2025-08-01 DOI: 10.1016/j.dcan.2025.03.007

Jia Guo, Jinqi Zhu, Xiang Li, Bowen Sun, Qian Gao, Weijia Feng

With technological advancements, high-speed rail has emerged as a prevalent mode of transportation. During travel, passengers exhibit a growing demand for streaming media services. However, the high-speed mobile networks environment poses challenges, including frequent base station handoffs, which significantly degrade wireless network transmission performance. Improving transmission efficiency in high-speed mobile networks and optimizing spatiotemporal wireless resource allocation to enhance passengers' media experiences are key research priorities. To address these issues, we propose an Adaptive Cross-Layer Optimization Transmission Method with Environment Awareness (ACOTM-EA) tailored for high-speed rail streaming media. Within this framework, we develop a channel quality prediction model utilizing Kalman filtering and an algorithm to identify packet loss causes. Additionally, we introduce a proactive base station handoff strategy to minimize handoff-related disruptions and optimize resource distribution across adjacent base stations. Moreover, this study presents a wireless resource allocation approach based on an enhanced genetic algorithm, coupled with an adaptive bitrate selection mechanism, to maximize passenger Quality of Experience (QoE). To evaluate the proposed method, we designed a simulation experiment and compared ACOTM-EA with established algorithms. Results indicate that ACOTM-EA improves throughput by 11% and enhances passengers' media experience by 5%.

随着科技的进步，高速铁路已经成为一种普遍的交通方式。在旅行中，乘客对流媒体服务的需求日益增长。然而，高速移动网络环境带来了挑战，包括频繁的基站切换，这大大降低了无线网络的传输性能。提高高速移动网络的传输效率，优化无线资源的时空分配，以增强乘客的媒体体验是研究的重点。为了解决这些问题，我们提出了一种针对高铁流媒体的环境意识自适应跨层优化传输方法（ACOTM-EA）。在这个框架内，我们开发了一个信道质量预测模型，利用卡尔曼滤波和一种算法来识别数据包丢失的原因。此外，我们引入了一种主动的基站切换策略，以最大限度地减少与切换相关的中断，并优化相邻基站之间的资源分配。此外，本研究提出了一种基于增强型遗传算法的无线资源分配方法，结合自适应比特率选择机制，以最大限度地提高乘客体验质量（QoE）。为了评估所提出的方法，我们设计了一个仿真实验，并将ACOTM-EA与已有算法进行了比较。结果表明，ACOTM-EA提高了11%的吞吐量，提高了5%的乘客媒体体验。

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引用次数: 0

A knowledge graph-based reinforcement learning approach for cooperative caching in MEC-enabled heterogeneous networks 基于知识图的异构网络协同缓存强化学习方法

IF 7.5 2区计算机科学 Q1 TELECOMMUNICATIONS

Digital Communications and Networks

Pub Date : 2025-08-01 DOI: 10.1016/j.dcan.2024.12.006

Dan Wang, Yalu Bai, Bin Song

Existing wireless networks are flooded with video data transmissions, and the demand for high-speed and low-latency video services continues to surge. This has brought with it challenges to networks in the form of congestion as well as the need for more resources and more dedicated caching schemes. Recently, Multi-access Edge Computing (MEC)-enabled heterogeneous networks, which leverage edge caches for proximity delivery, have emerged as a promising solution to all of these problems. Designing an effective edge caching scheme is critical to its success, however, in the face of limited resources. We propose a novel Knowledge Graph (KG)-based Dueling Deep Q-Network (KG-DDQN) for cooperative caching in MEC-enabled heterogeneous networks. The KG-DDQN scheme leverages a KG to uncover video relations, providing valuable insights into user preferences for the caching scheme. Specifically, the KG guides the selection of related videos as caching candidates (i.e., actions in the DDQN), thus providing a rich reference for implementing a personalized caching scheme while also improving the decision efficiency of the DDQN. Extensive simulation results validate the convergence effectiveness of the KG-DDQN, and it also outperforms baselines regarding cache hit rate and service delay.

现有的无线网络充斥着视频数据传输，对高速和低延迟视频服务的需求持续激增。这给网络带来了拥堵的挑战，也需要更多的资源和更专用的缓存方案。最近，支持多访问边缘计算（MEC）的异构网络，利用边缘缓存进行近距离传输，已经成为解决所有这些问题的有希望的解决方案。然而，在资源有限的情况下，设计一个有效的边缘缓存方案是其成功的关键。我们提出了一种新的基于知识图（KG）的Dueling Deep Q-Network (KG- ddqn)，用于支持mec的异构网络中的协同缓存。KG- ddqn方案利用KG来发现视频关系，为用户对缓存方案的偏好提供有价值的见解。具体来说，KG指导选择相关视频作为缓存候选（即DDQN中的动作），从而为实现个性化缓存方案提供了丰富的参考，同时也提高了DDQN的决策效率。大量的仿真结果验证了KG-DDQN的收敛有效性，并且在缓存命中率和服务延迟方面也优于基线。

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引用次数: 0

FlyCache: Recommendation-driven edge caching architecture for full life cycle of video streaming FlyCache：推荐驱动的边缘缓存架构，用于视频流的全生命周期

IF 7.5 2区计算机科学 Q1 TELECOMMUNICATIONS

Digital Communications and Networks

Pub Date : 2025-08-01 DOI: 10.1016/j.dcan.2025.01.001

Shaohua Cao , Quancheng Zheng , Zijun Zhan , Yansheng Yang , Huaqi Lv , Danyang Zheng , Weishan Zhang

With the rapid development of 5G technology, the proportion of video traffic on the Internet is increasing, bringing pressure on the network infrastructure. Edge computing technology provides a feasible solution for optimizing video content distribution. However, the limited edge node cache capacity and dynamic user requests make edge caching more complex. Therefore, we propose a recommendation-driven edge Caching network architecture for the Full life cycle of video streaming (FlyCache) designed to improve users' Quality of Experience (QoE) and reduce backhaul traffic consumption. FlyCache implements intelligent caching management across three key stages: before-playback, during-playback, and after-playback. Specifically, we introduce a cache placement policy for the before-playback stage, a dynamic prefetching and cache admission policy for the during-playback stage, and a progressive cache eviction policy for the after-playback stage. To validate the effectiveness of FlyCache, we developed a user behavior-driven edge caching simulation framework incorporating recommendation mechanisms. Experiments conducted on the MovieLens and synthetic datasets demonstrate that FlyCache outperforms other caching strategies in terms of byte hit rate, backhaul traffic, and delayed startup rate.

随着5G技术的快速发展，互联网上视频流量的比例越来越大，给网络基础设施带来了压力。边缘计算技术为优化视频内容分发提供了可行的解决方案。然而，有限的边缘节点缓存容量和动态用户请求使得边缘缓存更加复杂。因此，我们提出了一种推荐驱动的边缘缓存网络架构，用于视频流的全生命周期（FlyCache），旨在提高用户的体验质量（QoE）并减少回程流量消耗。FlyCache在三个关键阶段实现智能缓存管理：播放前、播放期间和播放后。具体来说，我们为播放前阶段引入了一个缓存放置策略，为播放期间阶段引入了一个动态预取和缓存准入策略，并为播放后阶段引入了一个渐进的缓存清除策略。为了验证FlyCache的有效性，我们开发了一个包含推荐机制的用户行为驱动的边缘缓存模拟框架。在MovieLens和合成数据集上进行的实验表明，FlyCache在字节命中率、回程流量和延迟启动率方面优于其他缓存策略。

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引用次数: 0

Sum rate maximization in UAV-assisted data harvesting network supported by CF-mMIMO system exploiting statistical CSI 利用统计CSI的CF-mMIMO系统支持的无人机辅助数据采集网络的和速率最大化

IF 7.5 2区计算机科学 Q1 TELECOMMUNICATIONS

Digital Communications and Networks

Pub Date : 2025-08-01 DOI: 10.1016/j.dcan.2024.06.009

Linlin Xu , Qi Zhu , Wenchao Xia , Jun Zhang , Gan Zheng , Hongbo Zhu

Unmanned Aerial Vehicles (UAVs) have been considered to have great potential in supporting reliable and timely data harvesting for Sensor Nodes (SNs) from an Internet of Things (IoT) perspective. However, due to physical limitations, UAVs are unable to further process the harvested data and have to rely on terrestrial servers, thus extra spectrum resource is needed to convey the harvested data. To avoid the cost of extra servers and spectrum resources, in this paper, we consider a UAV-based data harvesting network supported by a Cell-Free massive Multiple-Input-Multiple-Output (CF-mMIMO) system, where a UAV is used to collect and transmit data from SNs to the central processing unit of CF-mMIMO system for processing. In order to avoid using additional spectrum resources, the entire bandwidth is shared among radio access networks and wireless fronthaul links. Moreover, considering the limited capacity of the fronthaul links, the compress-and-forward scheme is adopted. In this work, in order to maximize the ergodically achievable sum rate of SNs, the power allocation of ground access points, the compression of fronthaul links, and also the bandwidth fraction between radio access networks and wireless fronthaul links are jointly optimized. To avoid the high overhead introduced by computing ergodically achievable rates, we introduce an approximate problem, using the large-dimensional random matrix theory, which relies only on statistical channel state information. We solve the nontrivial problem in three steps and propose an algorithm based on weighted minimum mean square error and Dinkelbach's methods to find solutions. Finally, simulation results show that the proposed algorithm converges quickly and outperforms the baseline algorithms.

从物联网（IoT）的角度来看，无人驾驶飞行器（uav）在支持传感器节点（SNs）可靠和及时的数据收集方面具有巨大的潜力。然而，由于物理限制，无人机无法对采集的数据进行进一步处理，必须依赖地面服务器，因此需要额外的频谱资源来传输采集的数据。为了避免额外的服务器和频谱资源成本，本文考虑了一种基于无人机的数据采集网络，该网络由无单元大规模多输入多输出（CF-mMIMO）系统支持，其中无人机用于从SNs收集数据并将其传输到CF-mMIMO系统的中央处理单元进行处理。为了避免使用额外的频谱资源，整个带宽在无线接入网和无线前传链路之间共享。此外，考虑到前传链路的容量有限，采用了压缩转发方案。为了最大限度地提高网络传输速率，对地面接入点的功率分配、前传链路的压缩以及无线接入网和无线前传链路之间的带宽比例进行了联合优化。为了避免计算遍历可达速率带来的高开销，我们引入了一个近似问题，使用大维随机矩阵理论，它只依赖于统计信道状态信息。我们分三步求解非平凡问题，并提出了一种基于加权最小均方误差和Dinkelbach方法的求解算法。最后，仿真结果表明，该算法收敛速度快，优于基准算法。

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引用次数: 0

Profit-driven distributed trading mechanism for IoT data 利益驱动的物联网数据分布式交易机制

IF 7.5 2区计算机科学 Q1 TELECOMMUNICATIONS

Digital Communications and Networks

Pub Date : 2025-08-01 DOI: 10.1016/j.dcan.2024.10.014

Chang Liu , Zhili Wang , Qun Zhang , Shaoyong Guo , Xuesong Qiu

Data trading is a crucial means of unlocking the value of Internet of Things (IoT) data. However, IoT data differs from traditional material goods due to its intangible and replicable nature. This difference leads to ambiguous data rights, confusing pricing, and challenges in matching. Additionally, centralized IoT data trading platforms pose risks such as privacy leakage. To address these issues, we propose a profit-driven distributed trading mechanism for IoT data. First, a blockchain-based trading architecture for IoT data, leveraging the transparent and tamper-proof features of blockchain technology, is proposed to establish trust between data owners and data requesters. Second, an IoT data registration method that encompasses both rights confirmation and pricing is designed. The data right confirmation method uses non-fungible token to record ownership and authenticate IoT data. For pricing, we develop an IoT data value assessment index system and introduce a pricing model based on a combination of the sparrow search algorithm and the back propagation neural network. Finally, an IoT data matching method is designed based on the Stackelberg game. This establishes a Stackelberg game model involving multiple data owners and requesters, employing a hierarchical optimization method to determine the optimal purchase strategy. The security of the mechanism is analyzed and the performance of both the pricing method and matching method is evaluated. Experiments demonstrate that both methods outperform traditional approaches in terms of error rates and profit maximization.

数据交易是释放物联网（IoT）数据价值的重要手段。然而，物联网数据不同于传统的物质产品，因为它的无形和可复制性。这种差异导致了模糊的数据权利、令人困惑的定价和匹配方面的挑战。此外，集中式物联网数据交易平台存在隐私泄露等风险。为了解决这些问题，我们提出了一种利润驱动的物联网数据分布式交易机制。首先，提出了一种基于区块链的物联网数据交易架构，利用区块链技术的透明和防篡改特性，在数据所有者和数据请求者之间建立信任。其次，设计了一种包含权利确认和定价的物联网数据登记方法。数据权利确认方法使用不可替代的令牌来记录所有权并对物联网数据进行认证。在定价方面，我们开发了物联网数据价值评估指标体系，并引入了基于麻雀搜索算法和反向传播神经网络相结合的定价模型。最后，设计了一种基于Stackelberg博弈的物联网数据匹配方法。建立了涉及多个数据所有者和请求者的Stackelberg博弈模型，采用层次优化方法确定最优购买策略。分析了该机制的安全性，并对定价方法和匹配方法的性能进行了评价。实验表明，这两种方法在错误率和利润最大化方面都优于传统方法。

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引用次数: 0

CC-OLIA: A dynamic congestion control algorithm for multipath QUIC in mobile networks 移动网络中多路径QUIC的动态拥塞控制算法

IF 7.5 2区计算机科学 Q1 TELECOMMUNICATIONS

Digital Communications and Networks

Pub Date : 2025-08-01 DOI: 10.1016/j.dcan.2024.11.017

Haoyu Wang , Yang Liu , Zijun Li , Yu Zhang , Wenjing Gong , Tao Jiang , Ting Bi , Jiaxi Zhou

High-quality services in today's mobile networks require stable delivery of bandwidth-intensive network content. Multipath QUIC (MPQUIC), as a multipath protocol that extends QUIC, can utilize multiple paths to support stable and efficient transmission. The standard coupled congestion control algorithm in MPQUIC synchronizes these paths to manage congestion, meeting fairness requirements and improving transmission efficiency. However, current algorithms' Congestion Window (CWND) reduction approach significantly decreases CWND upon packet loss, which lowers effective throughput, regardless of the congestion origin. Furthermore, the uncoupled Slow-Start (SS) in MPQUIC leads to independent exponential CWND growth on each path, potentially causing buffer overflow. To address these issues, we propose the CC-OLIA, which incorporates Packet Loss Classifcation (PLC) and Coupled Slow-Start (CSS). The PLC distinguishes between congestion-induced and random packet losses, adjusting CWND reduction accordingly to maintain throughput. Concurrently, the CSS module coordinates CWND growth during the SS, preventing abrupt increases. Implementation on MININET shows that CC-OLIA not only maintains fair performance but also enhances transmission efficiency across diverse network conditions.

在当今的移动网络中，高质量的服务需要稳定地提供带宽密集型的网络内容。多路径QUIC （Multipath QUIC， MPQUIC）是对QUIC进行扩展的多路径协议，可以利用多条路径支持稳定高效的传输。MPQUIC中标准的耦合拥塞控制算法通过同步这些路径来管理拥塞，满足公平性要求，提高传输效率。然而，当前算法的拥塞窗口（CWND）减少方法显着降低了丢包时的拥塞窗口，这降低了有效吞吐量，无论拥塞来源如何。此外，MPQUIC中不耦合的慢启动（SS）导致每个路径上独立的指数级CWND增长，可能导致缓冲区溢出。为了解决这些问题，我们提出了CC-OLIA，它结合了丢包分类（PLC）和耦合慢启动（CSS）。PLC区分拥塞引起的和随机丢包，相应地调整CWND减少以保持吞吐量。同时，CSS模块在SS期间协调CWND的增长，防止CWND的突然增长。在MININET上的实现表明，CC-OLIA不仅保持了公平的性能，而且提高了不同网络条件下的传输效率。

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引用次数: 0

A lightweight dual authentication scheme for V2V communication in 6G-based vanets 一个轻量级的双重认证方案，用于基于6g的V2V通信

IF 7.5 2区计算机科学 Q1 TELECOMMUNICATIONS

Digital Communications and Networks

Pub Date : 2025-08-01 DOI: 10.1016/j.dcan.2024.12.005

Xia Feng , Yaru Wang , Kaiping Cui , Liangmin Wang

The advancement of 6G wireless communication technology has facilitated the integration of Vehicular Ad-hoc Networks (VANETs). However, the messages transmitted over the public channel in the open and dynamic VANETs are vulnerable to malicious attacks. Although numerous researchers have proposed authentication schemes to enhance the security of Vehicle-to-Vehicle (V2V) communication, most existing methodologies face two significant challenges: (1) the majority of the schemes are not lightweight enough to support real-time message interaction among vehicles; (2) the sensitive information like identity and position is at risk of being compromised. To tackle these issues, we propose a lightweight dual authentication protocol for V2V communication based on Physical Unclonable Function (PUF). The proposed scheme accomplishes dual authentication between vehicles by the combination of Zero-Knowledge Proof (ZKP) and MASK function. The security analysis proves that our scheme provides both anonymous authentication and information unlinkability. Additionally, the performance analysis demonstrates that the computation overhead of our scheme is approximately reduced 23.4% compared to the state-of-the-art schemes. The practical simulation conducted in a 6G network environment demonstrates the feasibility of 6G-based VANETs and their potential for future advancements.

6G无线通信技术的进步促进了车载自组织网络（vanet）的集成。然而，在开放和动态vanet中，通过公共通道传输的消息容易受到恶意攻击。尽管许多研究人员提出了验证方案来提高车对车（V2V）通信的安全性，但大多数现有方法面临两个重大挑战：(1)大多数方案不够轻量化，无法支持车辆之间的实时消息交互；(2)身份、职位等敏感信息有被泄露的风险。为了解决这些问题，我们提出了一种基于物理不可克隆功能（PUF）的轻量级V2V通信双重认证协议。该方案通过零知识证明（Zero-Knowledge Proof， ZKP）和MASK功能的结合，实现了车辆间的双重认证。安全性分析证明，该方案既提供匿名认证，又提供信息不可链接性。此外，性能分析表明，与最先进的方案相比，我们方案的计算开销大约减少了23.4%。在6G网络环境中进行的实际仿真证明了基于6G的vanet的可行性及其未来发展的潜力。

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引用次数: 0

Low-complexity multi-target localization via multi-BS sensing 基于多bs传感的低复杂度多目标定位

IF 7.5 2区计算机科学 Q1 TELECOMMUNICATIONS

Digital Communications and Networks

Pub Date : 2025-08-01 DOI: 10.1016/j.dcan.2024.11.002

Yinxiao Zhuo , Zhaocheng Wang

Integrated Sensing and Communication (ISAC) is envisioned as a promising technology for Sixth-Generation (6G) wireless communications, which enables simultaneous high-rate communication and high-precision target localization. Compared to independent sensing and communication modules, dual-function ISAC could leverage the strengths of both communication and sensing in order to achieve cooperative gains. When considering the communication core network, ISAC system facilitates multiple communication devices to collaborate for networked sensing. This paper investigates such kind of cooperative ISAC systems with distributed transmitters and receivers to support non-connected and multi-target localization. Specifically, we introduce a Time of Arrival (TOA) based multi-target localization scheme, which leverages the bi-static range measurements between the transmitter, target, and receiver channels in order to achieve elliptical localization. To obtain the low-complexity localization, a two-stage search-refine localization methodology is proposed. In the first stage, we propose a Successive Greedy Grid-Search (SGGS) algorithm and a Successive-Cancellation-List Grid-Search (SCLGS) algorithm to address the Measurement-to-Target Association (MTA) problem with relatively low computational complexity. In the second stage, a linear approximation refinement algorithm is derived to facilitate high-precision localization. Simulation results are presented to validate the effectiveness and superiority of our proposed multi-target localization method.

集成传感和通信（ISAC）被设想为第六代（6G）无线通信的一项有前途的技术，它能够同时实现高速通信和高精度目标定位。与独立的传感和通信模块相比，双功能ISAC可以利用通信和传感的优势来实现合作收益。在考虑通信核心网的情况下，ISAC系统便于多个通信设备协同进行网络化感知。本文研究了一种支持非连接和多目标定位的分布式发送和接收的协作ISAC系统。具体来说，我们介绍了一种基于到达时间（TOA）的多目标定位方案，该方案利用发射、目标和接收信道之间的双静态距离测量来实现椭圆定位。为了获得低复杂度的定位，提出了一种两阶段搜索-细化定位方法。在第一阶段，我们提出了一种连续贪婪网格搜索（SGGS）算法和一种连续取消列表网格搜索（SCLGS）算法来解决计算复杂度相对较低的测量-目标关联（MTA）问题。第二阶段，推导了一种线性逼近细化算法，实现了高精度定位。仿真结果验证了所提出的多目标定位方法的有效性和优越性。

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引用次数: 0

Blockchain-based lightweight trusted data interaction scheme for cross-domain IIoT 基于区块链的跨域工业物联网轻量级可信数据交互方案

IF 7.5 2区计算机科学 Q1 TELECOMMUNICATIONS

Digital Communications and Networks

Pub Date : 2025-08-01 DOI: 10.1016/j.dcan.2024.11.018

Fengqi Li , Yingjie Zhao , Kaiyang Zhang , Hui Xu , Yanjuan Wang , Deguang Wang

To facilitate cross-domain data interaction in the Industrial Internet of Things (IIoT), establishing trust between multiple administrative domains is essential. Although blockchain technology has been proposed as a solution, current techniques still suffer from issues related to efficiency, security, and privacy. Our research aims to address these challenges by proposing a lightweight, trusted data interaction scheme based on blockchain, which reduces redundant interactions among entities. We enhance the traditional Practical Byzantine Fault Tolerance (PBFT) algorithm to support lightweight distributed consensus in large-scale IIoT scenarios. Introducing a composite digital signature algorithm and incorporating veto power minimizes resource consumption and eliminates ineffective consensus operations. The experimental results show that, compared with PBFT, our scheme reduces latency by 27.2%, thereby improving communication efficiency and resource utilization. Furthermore, we develop a lightweight authentication technique specifically for cross-domain IIoT, leveraging blockchain technology to achieve distributed collaborative authentication. The performance comparisons indicate that our method significantly outperforms traditional schemes, with an average authentication latency of approximately 151 milliseconds. Additionally, we introduce a trusted federated learning (FL) algorithm that ensures comprehensive trust assessments for devices across different domains while protecting data privacy. Extensive simulations and experiments validate the reliability of our approach.

为了促进工业物联网（IIoT）中的跨域数据交互，在多个管理域之间建立信任至关重要。尽管区块链技术已被提出作为一种解决方案，但目前的技术仍然存在与效率、安全性和隐私相关的问题。我们的研究旨在通过提出基于区块链的轻量级可信数据交互方案来解决这些挑战，该方案减少了实体之间的冗余交互。我们改进了传统的实用拜占庭容错（PBFT）算法，以支持大规模工业物联网场景下的轻量级分布式共识。引入复合数字签名算法并结合否决权，最大限度地减少了资源消耗，消除了无效的共识操作。实验结果表明，与PBFT相比，该方案降低了27.2%的时延，从而提高了通信效率和资源利用率。此外，我们开发了一种专门针对跨域IIoT的轻量级身份验证技术，利用区块链技术实现分布式协作身份验证。性能比较表明，我们的方法明显优于传统方案，平均身份验证延迟约为151毫秒。此外，我们引入了一种可信的联邦学习（FL）算法，确保对不同领域的设备进行全面的信任评估，同时保护数据隐私。大量的仿真和实验验证了我们方法的可靠性。

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引用次数: 0