A credibility-aware swarm-federated deep learning framework in internet of vehicles

Although Federated Deep Learning(FDL)enables distributed machine learning in the Internet of Vehicles(IoV),it requires multiple clients to upload model parameters,thus still existing unavoidable communication overhead and data privacy risks.The recently proposed Swarm Learning(SL)provides a decentralized machine learning approach for unit edge computing and blockchain-based coordination.A Swarm-Federated Deep Learning framework in the IoV system(IoV-SFDL)that integrates SL into the FDL framework is proposed in this paper.The IoV-SFDL organizes vehicles to generate local SL models with adjacent vehicles based on the blockchain empowered SL,then aggregates the global FDL model among different SL groups with a credibility weights prediction algorithm.Extensive experimental results show that compared with the baseline frameworks,the proposed IoV-SFDL framework reduces the overhead of client-to-server communication by 16.72%,while the model performance improves by about 5.02%for the same training iterations.

A Data Intrusion Tolerance Model Based on an Improved Evolutionary Game Theory for the Energy Internet

Malicious attacks against data are unavoidable in the interconnected,open and shared Energy Internet(EI),Intrusion tolerant techniques are critical to the data security of EI.Existing intrusion tolerant techniques suffered from problems such as low adaptability,policy lag,and difficulty in determining the degree of tolerance.To address these issues,we propose a novel adaptive intrusion tolerance model based on game theory that enjoys two-fold ideas:(1)it constructs an improved replica of the intrusion tolerance model of the dynamic equation evolution game to induce incentive weights;and (2)it combines a tournament competition model with incentive weights to obtain optimal strategies for each stage of the game process.Extensive experiments are conducted in the IEEE 39-bus system,whose results demonstrate the feasibility of the incentive weights,confirm the proposed strategy strengthens the system’s ability to tolerate aggression,and improves the dynamic adaptability and response efficiency of the aggression-tolerant system in the case of limited resources.

Low-Cost Federated Broad Learning for Privacy-Preserved Knowledge Sharing in the RIS-Aided Internet of Vehicles

High-efficiency and low-cost knowledge sharing can improve the decision-making ability of autonomous vehicles by mining knowledge from the Internet of Vehicles(IoVs).However,it is challenging to ensure high efficiency of local data learning models while preventing privacy leakage in a high mobility environment.In order to protect data privacy and improve data learning efficiency in knowledge sharing,we propose an asynchronous federated broad learning(FBL)framework that integrates broad learning(BL)into federated learning(FL).In FBL,we design a broad fully connected model(BFCM)as a local model for training client data.To enhance the wireless channel quality for knowledge sharing and reduce the communication and computation cost of participating clients,we construct a joint resource allocation and reconfigurable intelligent surface(RIS)configuration optimization framework for FBL.The problem is decoupled into two convex subproblems.Aiming to improve the resource scheduling efficiency in FBL,a double Davidon–Fletcher–Powell(DDFP)algorithm is presented to solve the time slot allocation and RIS configuration problem.Based on the results of resource scheduling,we design a reward-allocation algorithm based on federated incentive learning(FIL)in FBL to compensate clients for their costs.The simulation results show that the proposed FBL framework achieves better performance than the comparison models in terms of efficiency,accuracy,and cost for knowledge sharing in the IoV.

Call for Papers——Feature Topic Vol.22,No.2,2025 Efficient Cooperative Transmission over Satellite Internet for 6G

Satellite Internet,as a strategic public information infrastructure,can effectively bridge the limitations of traditional terrestrial network coverage,support global coverage and deep space exploration,and greatly enhance the range of network information services accessible to humans.With the transition of terrestrial mobile communication networks from the 5G era,which provides access to information anywhere,to the 6G era,which seeks to connect everything,the construction of satellite Internet,which promises a"network reaching everywhere and service is ubiquitous",has become the consensus of the industry's development and the focus of global scientific and technological innovation.

Blockchain-Enabled Federated Learning with Differential Privacy for Internet of Vehicles

The rapid evolution of artificial intelligence(AI)technologies has significantly propelled the advancement of the Internet of Vehicles(IoV).With AI support,represented by machine learning technology,vehicles gain the capability to make intelligent decisions.As a distributed learning paradigm,federated learning(FL)has emerged as a preferred solution in IoV.Compared to traditional centralized machine learning,FL reduces communication overhead and improves privacy protection.Despite these benefits,FL still faces some security and privacy concerns,such as poisoning attacks and inference attacks,prompting exploration into blockchain integration to enhance its security posture.This paper introduces a novel blockchain-enabled federated learning(BCFL)scheme with differential privacy(DP)tailored for IoV.In order to meet the performance demanding IoV environment,the proposed methodology integrates a consortium blockchain with Practical Byzantine Fault Tolerance(PBFT)consensus,which offers superior efficiency over the conventional public blockchains.In addition,the proposed approach utilizes the Differentially Private Stochastic Gradient Descent(DP-SGD)algorithm in the local training process of FL for enhanced privacy protection.Experiment results indicate that the integration of blockchain elevates the security level of FL in that the proposed approach effectively safeguards FL against poisoning attacks.On the other hand,the additional overhead associated with blockchain integration is also limited to a moderate level to meet the efficiency criteria of IoV.Furthermore,by incorporating DP,the proposed approach is shown to have the(ε-δ)privacy guarantee while maintaining an acceptable level of model accuracy.This enhancement effectively mitigates the threat of inference attacks on private information.

Power-Domain Collision-Tolerant Random Access Method with Auxiliary Beam for Satellite Internet of Things:A New Solution

There are numerous terminals in the satellite Internet of Things(IoT).To save cost and reduce power consumption,the system needs terminals to catch the characteristics of low power consumption and light control.The regular random access(RA)protocols may generate large amounts of collisions,which degrade the system throughout severally.The near-far effect and power control technologies are not applicable in capture effect to obtain power difference,resulting in the collisions that cannot be separated.In fact,the optimal design at the receiving end can also realize the condition of packet power domain separation,but there are few relevant researches.In this paper,an auxiliary beamforming scheme is proposed for power domain signal separation.It adds an auxiliary reception beam based on the conventional beam,utilizing the correlation of packets in time-frequency domain between the main and auxiliary beam to complete signal separation.The roll-off belt of auxiliary beam is used to create the carrier-to-noise ratio(CNR)difference.This paper uses the genetic algorithm to optimize the auxiliary beam direction.Simulation results show that the proposed scheme outperforms slotted ALOHA(SA)in terms of system throughput per-formance and without bringing terminals additional control burden.

Federated Learning on Internet of Things:Extensive and Systematic Review

The proliferation of IoT devices requires innovative approaches to gaining insights while preserving privacy and resources amid unprecedented data generation.However,FL development for IoT is still in its infancy and needs to be explored in various areas to understand the key challenges for deployment in real-world scenarios.The paper systematically reviewed the available literature using the PRISMA guiding principle.The study aims to provide a detailed overview of the increasing use of FL in IoT networks,including the architecture and challenges.A systematic review approach is used to collect,categorize and analyze FL-IoT-based articles.Asearch was performed in the IEEE,Elsevier,Arxiv,ACM,and WOS databases and 92 articles were finally examined.Inclusion measures were published in English and with the keywords“FL”and“IoT”.The methodology begins with an overview of recent advances in FL and the IoT,followed by a discussion of how these two technologies can be integrated.To be more specific,we examine and evaluate the capabilities of FL by talking about communication protocols,frameworks and architecture.We then present a comprehensive analysis of the use of FL in a number of key IoT applications,including smart healthcare,smart transportation,smart cities,smart industry,smart finance,and smart agriculture.The key findings from this analysis of FL IoT services and applications are also presented.Finally,we performed a comparative analysis with FL IID(independent and identical data)and non-ID,traditional centralized deep learning(DL)approaches.We concluded that FL has better performance,especially in terms of privacy protection and resource utilization.FL is excellent for preserving privacy becausemodel training takes place on individual devices or edge nodes,eliminating the need for centralized data aggregation,which poses significant privacy risks.To facilitate development in this rapidly evolving field,the insights presented are intended to help practitioners and researchers navigate the complex terrain of FL and IoT.

Analysis of Mobile and Internet Network Coverage: Propagation of Electromagnetic Waves and Concept of Digital Divide in Burundi

Mobile and Internet network coverage plays an important role in digital transformation and the exploitation of new services. The evolution of mobile networks from the first generation (1G) to the 5th generation is still a long process. 2G networks have developed the messaging service, which complements the already operational voice service. 2G technology has rapidly progressed to the third generation (3G), incorporating multimedia data transmission techniques. It then progressed to fourth generation (4G) and LTE (Long Term Evolution), increasing the transmission speed to improve 3G. Currently, developed countries have already moved to 5G. In developing countries, including Burundi, a member of the East African Community (ECA) where more than 80% are connected to 2G technologies, 40% are connected to the 3G network and 25% to the 4G network and are not yet connected to the 5G network and then still a process. The objective of this article is to analyze the coverage of 2G, 3G and 4G networks in Burundi. This analysis will make it possible to identify possible deficits in order to reduce the digital divide between connected urban areas and remote rural areas. Furthermore, this analysis will draw the attention of decision-makers to the need to deploy networks and coverage to allow the population to access mobile and Internet services and thus enable the digitalization of the population. Finally, this article shows the level of coverage, the digital divide and an overview of the deployment of base stations (BTS) throughout the country to promote the transformation and digital inclusion of services.

Connecting Through Cyberspace Xiamen forum puts spotlight on deepening China-Africa media cooperation through Internet

In an era of connectivity and digital innovation,the China-Africa relationship stands out as a stimulus for international cooperation in the field of the Internet and media cooperation.

Parental Psychological Control and Internet Gaming Disorder Tendency:A Moderated Mediation Model of Core Self-Evaluation and Intentional Self-Regulation

Internet gaming disorder(IGD)among junior high school students is an increasingly prominent mental health concern.It is important to look for influences behind internet gaming disorder tendency(IGDT)in the junior high school student population.The present study aimed to reveal the explanatory mechanisms underlying the association between parental psychological control(PPC)and internet gaming disorder tendency among junior high school students by testing the mediating role of core self-evaluation(CSE)and the moderating role of intentional self-regulation(ISR).Participants in present study were 735 Chinese junior high school students who completed offline self-report questionnaires on parental psychological control,core self-evaluation,intentional self-regulation,and Internet gaming disorder tendency.Analyses were conducted via mediation and moderated mediation.The results showed that:(1)Parental psychological control was positively related to junior high school students’Internet gaming disorder tendency.Core self-evaluation,and intentional self-regulation were negatively related to junior high school students’Internet gaming disorder tendency,respectively.(2)Core self-evaluation partially mediated the relationship between parental psychological control and junior high school students’Internet gaming disorder tendency.(3)Intentional self-regulation moderated the association between parental psychological control and Internet gaming disorder tendency,as well as the relationships between parental psychological control and core self-evaluation and core self-evaluation and Internet gaming disorder tendency in the mediated model.Based on these findings,we believe that there is a need to weaken parental psychological control,strengthen junior high school students’core self-evaluation and intentional self-regulation,and to recognize the important role of parents as well as their children’s personal positive traits in the healthy development of junior high school students.

Research on Professional Teaching Reform of the E-Commerce Major in Vocational Colleges Under the Internet Era

With the rapid development of science and technology,the face of human society has undergone great changes;with the emergence of the Internet era,all kinds of educational technology,equipment,and software in vocational colleges have been widely used to carry out education and teaching,and has achieved remarkable results.Based on this,colleges and universities’electronic commerce(e-commerce)professional teachers should try to rely on the Internet to build information teaching classrooms,introduce advanced methods to build efficient classrooms by integrating teaching resources,and optimize the top-level design,so as to activate the classroom atmosphere,mobilize students’emotions,make them immersed in the teaching of electronic commerce courses.In view of this,this paper combines the existing theory and experience,first analyzes the dilemma faced by the current teaching of e-commerce in vocational colleges,then discusses the practical significance of teaching reform based on the Internet era,and lastly puts forward the specific practice path.

Application Analysis of Doctor-Nurse Cooperation Follow-up Model Based on the Internet Platform in Continuation Care of Patients after Urooncology Surgery

Objective:To explore the application effect of a doctor-nurse cooperation follow-up model based on an Internet platform in the continuation of care for patients after uro-oncology surgery.Methods:A convenient sampling method was used to select patients with urinary system tumors who underwent surgery in the Department of Urology in Grade III A general hospital in Shanghai from May to August 2022.Patients who underwent surgery from May to June 2022 were assigned to the control group,and those who underwent surgery from July to August 2022 were assigned to the experimental group.The control group received routine post-discharge nursing health education and telephone follow-up.On the basis of routine discharge guidance,the experimental group implemented the intervention method based on the Internet platform in continuation care.The levels of self-management efficacy,satisfaction,and incidence of unplanned readmission were compared one month after discharge between the two groups.Results:One month after discharge,the self-management efficacy of the experimental group(90.15±7.92)was significantly higher than that of the control group(79.10±7.84),and the patient satisfaction score(97.83±2.32)was significantly higher than that of the control group(90.23±2.58),with statistical significance(P<0.05).Additionally,the incidence of unplanned readmissions within one month after discharge in the experimental group(1.59%)was slightly lower than that in the control group(4.84%).Conclusion:The doctor-nurse cooperation follow-up model based on the Internet platform in continuation care can significantly improve the self-management efficiency of patients after discharge and enhance patient satisfaction,providing a new approach for discharge follow-up of urological tumor patients after surgery.

Research on a Comprehensive Monitoring System for Tunnel Operation based on the Internet of Things and Artificial Intelligence Identification Technology

This article proposes a comprehensive monitoring system for tunnel operation to address the risks associated with tunnel operations.These risks include safety control risks,increased traffic flow,extreme weather events,and movement of tectonic plates.The proposed system is based on the Internet of Things and artificial intelligence identification technology.The monitoring system will cover various aspects of tunnel operations,such as the slope of the entrance,the structural safety of the cave body,toxic and harmful gases that may appear during operation,excessively high and low-temperature humidity,poor illumination,water leakage or road water accumulation caused by extreme weather,combustion and smoke caused by fires,and more.The system will enable comprehensive monitoring and early warning of fire protection systems,accident vehicles,and overheating vehicles.This will effectively improve safety during tunnel operation.

Exploration of Industrial Internet Security Technology and Application from the Perspective of Generative Artificial Intelligence

In recent years,artificial intelligence technology has developed rapidly around the world is widely used in various fields,and plays an important role.The integration of industrial Internet security with new technologies such as big models and generative artificial intelligence has become a hot research issue.In this regard,this paper briefly analyzes the industrial Internet security technology and application from the perspective of generative artificial intelligence,hoping to provide some valuable reference and reference for readers.

ERAS理念下中医特色护理干预在腰椎间盘突出症术后恐动症患者中的应用

目的:探讨加快康复外科(ERAS)理念下中医特色护理干预在腰椎间盘突出症(LDH)术后恐动症患者中的应用效果。方法:选取2023年6月1日~11月1日收治的108例LDH术后恐动症患者为研究对象,按照随机数字表法分为研究组和对照组各54例,对照组实施术后常规护理,研究组在常规护理基础上实施ERAS理念下中医特色护理干预;比较两组不同时间疼痛状况[采用疼痛数字评分法(NRS)]、恐动症状况(采用恐动症TSK评分量表)、自我效能[采用一般自我效能感量表(GSES)]。结果:研究组术后1周、出院时、术后1个月恐动症TSK、NRS评分均低于对照组(P<0.01),研究组不同时间GSES评分高于对照组(P<0.01)。结论:基于ERAS理念构建的中医特色护理干预方案可降低LDH术后恐动症患者的恐动程度,减轻患者疼痛,有利于其快速康复。

ERAS理念在老年脊柱手术患者围术期中的应用研究

目的:本研究立足于加速康复理念,通过制定综合性、连续性、全面性的脊柱外科手术围术期患者管理方案,探讨其应用效果。方法:通过组建MDT团队,制订加速康复方案,选取2019年6月—2022年5月赤峰市医院脊柱外科收治的244例老年脊柱手术患者为研究对象,按手术方式分为4组:腰椎后路短节段内固定减压术组对照组、腰椎后路短节段内固定减压术组ERAS组、经皮椎体成形术(PVP)/椎体后凸成形术(PKP)组对照组、PVP/PKP组ERAS组。探讨不同手术方式的老年脊柱患者围术期的管理效果。结果:腰椎后路短节段内固定减压术组ERAS组住院时间、首次下地时间均短于腰椎后路短节段内固定减压术组对照组,住院费用少于腰椎后路短节段内固定组对照组,组间差异有统计学意义(P<0.05);PVP/PKP组ERAS组住院时间、首次下地时间均短于PVP/PKP组对照组,组间差异有统计学意义(P<0.05)。腰椎后路短节段内固定减压术组ERAS组腹胀、便秘、感染、心脑血管疾病、深静脉血栓(VTE)发生率低于腰椎后路短节段内固定减压术组对照组,差异有统计学意义(P<0.05);PVP/PKP组ERAS组腹胀、便秘、VTE发生率均低于PVP/PKP组对照组,组间差异有统计学意义(P<0.05)。结论:在老年脊柱手术患者围术期中应用ERAS理念,可以加快患者康复速度,缩短平均住院时间,减少住院费用,降低患者围术期的各种并发症,提高患者围术期舒适度。

一体化保温方案联合ERAS护理对手术患者睡眠质量的影响

目的:观察手术患者应用一体化保温方案联合加速康复外科(ERAS)护理对睡眠质量的影响。方法:选取2022年5月至2023年12月厦门大学附属第一医院接受手术治疗的患者86例作为研究对象,按照Excel表排序分为对照组和观察组,每组43例。对照组开展常规护理,观察组开展一体化保温方案联合ERAS护理。对2组患者术中体温变化情况、围术期睡眠质量[匹兹堡睡眠质量指数量表(PSQI)]、术后恢复指标等进行比较。结果:术前2组体温指数比较,差异无统计学意义(P>0.05),术后手术10 min、20 min、30 min观察组体温比对照组高(P<0.05);护理前,2组PSQI评分比较,差异无统计学意义(P>0.05),护理后,观察组PSQI评分比对照组低,差异有统计学意义(P<0.05);患者术后住院时间、下床活动时间、排气时间以及拔管时间观察组比对照组短,差异有统计学意义(P<0.05)。结论:在对手术患者进行护理时开展一体化保温方案联合ERAS护理,可以稳定患者手术期间体温情况,改善睡眠质量,更利于术后恢复。

ERAS理念下术前优化前移护理模式用于子宫肌瘤腹腔镜手术患者对应激反应及术后恢复的影响

目的:探讨ERAS理念下术前优化前移护理模式在子宫肌瘤腹腔镜手术患者中的应用效果。方法:选择2022年1月—2023年12月本院96例子宫肌瘤腹腔镜手术患者,根据随机数字表法进行分组,参考组48例行常规护理,干预组48例采用ERAS理念下术前优化前移护理模式。观察两组应激反应、术后恢复情况、术后疼痛程度及并发症发生情况。结果:两组术后12h的收缩压、舒张压及心率与术前1d相比均更高,但干预组低于参考组(P<0.05);干预组术后首次下床活动、首次排气、首次排便、首次自主进食时间及住院时间均较参考组更短(P<0.05);干预组术后各时间点的数字评价量表(NRS)评分均低于参考组(P<0.05);干预组术后并发症总发生率低于参考组(P<0.05)。结论:ERAS理念下术前优化前移护理模式能够减轻子宫肌瘤腹腔镜手术患者的应激反应,促进其术后恢复与术后疼痛缓解,有助于减少术后并发症。

“互联网+”远程指导康复对肩袖损伤ERAS理念下关节镜手术后患者的康复效果研究

目的探讨基于“互联网+”远程指导康复对肩袖损伤ERAS理念下关节镜手术后患者的康复效果。方法选择2021年1月至2022年6月本院收治的肩袖损伤ERAS理念下关节镜手术后患者227例,数字随机法随机分为对照组109例,观察组118例。对照组采取常规康复和随访,观察组采取基于“互联网+”的远程指导康复,持续3个月。比较两组患者手术前后的肩关节Constant Murley评分及生活质量。结果观察组Constant Murley评分及生活质量均高于对照组,差异均有统计学意义(P<0.05)。结论基于“互联网+”远程指导康复能够提升肩袖损伤ERAS理念下关节镜手术后患者的康复效果。

采用ERA5数据构建基于人工神经网络的天津ZWD模型

提出一种高精度的ZWD模型(tianjin_zwd,TZ)。TZ基于2016-2018年逐小时气压分层的ERA5,欧洲中尺度气象预报中心第五代再分析产品数据,采用BP神经网络建立。然后,根据2019年的ERA5产品导出的ZWD对TZ模型进行了验证。结果表明:相比GPT3模型,TZ模型可提供更贴近真值的ZWD估值;并且,其RMSE由5.0 cm (GPT3)降至4.5 cm,表明10%的精度提升。上述结果表明TZ模型实现了更优的预测性能,该模型的构建策略可为全国其他地区的ZWD建模提供借鉴。