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Proactive Mobility-Aware Fog Service Continuity Using Digital Twins and GRU-EWMA-Based Association Forecasting 认领 引用
1
作者 Navjeet Kaur Ayush Mittal Saad Alahmari 《Computers, Materials & Continua》 SCIE EI 2026年第7期1543-1576,共34页
Mobile fog computing must support latency-sensitive applications under dynamic user mobility and time-varying network conditions.Existing mobility-aware scheduling approaches are largely reactive and often ignore pred... Mobile fog computing must support latency-sensitive applications under dynamic user mobility and time-varying network conditions.Existing mobility-aware scheduling approaches are largely reactive and often ignore prediction uncertainty,resulting in service disruptions and inefficient task migration.This paper proposes an uncertainty-aware digital twin-based orchestration framework for proactive mobility-aware fog computing.The framework maintains real-time synchronized digital twins of users and fog nodes and integrates a hybrid Gated Recurrent Unit-Exponentially Weighted Moving Average(GRU-EWMA)mobility prediction model with fog-load forecasting to enable joint mobility-and load-aware decision-making.An entropy-based confidence mechanism is introduced to regulate proactive handover and task migration,thereby reducing unnecessary task migrations when predictions are uncertain.The proposed framework is implemented in the MobFogSim simulator and evaluated against state-of-the-art baselines.Experimental results demonstrate that the proposed approach reduces the average task delay by up to 28.1%,decreases energy consumption by up to 9.5%,and improves the task success rate to 99.1%,while incurring only a modest digital-twin computational overhead.These results confirm that integrating uncertainty-aware mobility prediction with digital twin-driven orchestration significantly enhances reliability and efficiency in mobile fog computing environments. 展开更多
关键词 Fog computing mobile edge computing(MEC) digital twin proactive handoff task migration service continuity gated recurrent unit(GRU) exponentially weighted moving average(EWMA) MobFogSim
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Comprehensive Analysis of the Relative Dispersion of Droplet-Size Distributions and Their Relationships to Key Physical Fog Processes Under Different Aerosol Conditions and Evolutionary Stages 认领 引用
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作者 Xingcan JIA Chunsong LU +7 位作者 Zhiheng LIAO Ping TIAN Yuan WANG Fei WANG Shuai YANG Youjun DOU Xiange LIU Yangang LIU 《Advances in Atmospheric Sciences》 SCIE CAS CSCD 2026年第4期861-873,I0042-I0046,共13页
The relative dispersion of cloud and fog droplets has significant impacts on aerosol indirect effects,radiative transfer,and microphysical processes.However,previous studies have been mostly concerned with clouds,with... The relative dispersion of cloud and fog droplets has significant impacts on aerosol indirect effects,radiative transfer,and microphysical processes.However,previous studies have been mostly concerned with clouds,with limited studies on fog,particularly those that examine the combined influences of all key physical processes and their roles during fog evolution.As such,this study aims to conduct a comprehensive investigation by examining the relationships between relative dispersion and other microphysical variables,as well as the underlying microphysical and dynamic processes,based on field fog campaigns in polluted and clean conditions.In polluted fog,droplet concentrations are higher,leading to smaller droplets and increased dispersion.The correlation between dispersion and droplet volume-mean radius is positive in the polluted fog,but shifts to negative in clean fog.We attribute the difference to various microphysical processes like aerosol activation,condensation,collision-coalescence,and entrainment-mixing.In polluted fog,high aerosol concentrations,low supersaturations,and strong turbulence(entrainment-mixing)provide suitable conditions for the simultaneous occurrence of droplet condensation and aerosol activation,resulting in a positive correlation between dispersion and volume-mean radius,especially during the fog formation stage.In contrast,during the mature stage in clean fog,condensation is dominant with weak aerosol activation leading to a negative correlation between relative dispersion and volume-mean radius.The collision-coalescence process is more active in the mature stage,increasing radii and leading to the negative correlation between dispersion and volume-mean radius.This result sheds new light on understanding the relative dispersion and mechanisms in fog under different aerosol backgrounds. 展开更多
关键词 fog relative dispersion evolutionary stage aerosol activation collision-coalescence
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Trust-Centric Security Architecture and Anomaly Analytics for Distributed Fog-IoT Systems 认领 引用
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作者 Maram Fahaad Almufareh Mamoona Humayun +2 位作者 Sadia Din Khalid Haseeb Amr Munshi 《Computer Modeling in Engineering & Sciences》 SCIE EI 2026年第4期1413-1424,共12页
The real-time systems perform key functionalities in various fields to automate the communication and response in critical events.The Internet of Things(IoT),integrated with numerous physical objects,gathers environme... The real-time systems perform key functionalities in various fields to automate the communication and response in critical events.The Internet of Things(IoT),integrated with numerous physical objects,gathers environmental data,processes it at the edge,and provides intelligent decisions while routing health records to processing units.However,the dynamic and resource-constrained nature of IoT-based healthcare environments introduces significant challenges related to latency,transmission costs,and the reliable interaction of devices amid uncertain activities.In this work,we propose a framework for a consistent and trustworthy system that uses a weighted trust aggregation model to consider multiple parameters and support timely routing decisions in a Fog-driven healthcare environment.Furthermore,authorized access to critical and sensitive health data is achieved through mutual authentication among devices,ensuring data integrity.The analysis of trust scores dynamically enhances resilience and the timely detection of malicious actions,thereby improving the healthcare system’s performance across unpredictable channels.The performance of the proposed framework is tested and validated against CLCSR and FSRF,and performance results revealed the significance for energy consumption,response time,network throughput,trust level,and accuracy across varying fog node capacity and interference scenarios. 展开更多
关键词 Fog computing data privacy healthcare system intelligent decision network attackers
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MILOF-TCN:A Hierarchical Edge-Fog Framework for Monitoring Abnormal and Missing Patterns in Electric Vehicle Charging Data 认领 引用
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作者 Hwa-Young Jeong 《Computers, Materials & Continua》 SCIE EI 2026年第9期2004-2024,共21页
The rapid growth of electric vehicle(EV)charging infrastructures has introduced new challenges in monitoring abnormal load behaviors under strict latency and resource constraints.Conventional anomaly detection approac... The rapid growth of electric vehicle(EV)charging infrastructures has introduced new challenges in monitoring abnormal load behaviors under strict latency and resource constraints.Conventional anomaly detection approaches either rely on centralized processing or incur excessive false alarms,limiting their practical applicability in large-scale deployments.This paper proposes a hierarchical edge-fog anomaly detection framework that integrates lightweight edge-level filtering with a fog-level Temporal Convolutional Network(TCN)detector.The edge component suppresses non-informative patterns,while the fog layer performs temporal modeling on selectively forwarded data.This design enables controllable reduction of fog-level processing load.Under corrected end-to-end evaluation on real-world EV charging load data,the hierarchical pipeline should be interpreted as a system operating point rather than a uniformly superior detector.Relative to fog-only TCN-AE inference,the selected routing policy reduces fog workload by 34.9%and shortens average detection delay from 93.6 to 75.6 h,but increases false alarms per day from 0.88 to 7.29 and lowers F1 from 0.547 to 0.455.Sensitivity experiments over routing thresholds reveal a consistent trade-off among fog workload,alert burden,detection delay,and retained anomaly evidence.Additional routing diagnostics show that the primary source of performance degradation is information loss induced by filtering,rather than weakness of the fog detector on the forwarded subset.These findings suggest that hierarchical edge intelligence is a practical but calibration-sensitive direction for scalable anomaly monitoring in EV charging infrastructures. 展开更多
关键词 Edge computing fog computing anomaly detection electric vehicle charging time-series monitoring temporal convolutional networks missing data patterns hierarchical architecture
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A secure mist-fog-assisted cooperative offloading framework for sustainable smart city development 认领 引用 被引量：1
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作者 Subhranshu Sekhar Tripathy Sujit Bebortta +3 位作者 Mazin Abed Mohammed Muhammet Deveci Haydar Abdulameer Marhoon Radek Martinek 《Digital Communications and Networks》 SCIE EI CSCD 2026年第1期165-179,共15页
Practical applications of smart cities and the Internet of Things(IoT)have multiplied,posing many difficulties in network performance,dependability,and security.Concerns of accessibility,reliability,sustainability,and... Practical applications of smart cities and the Internet of Things(IoT)have multiplied,posing many difficulties in network performance,dependability,and security.Concerns of accessibility,reliability,sustainability,and security too have arisen correspondingly because of the decentralized character of the smart city and IoT systems.Fog computing offers a foundation for various applications,including cognitive support,health and social services,intelligent transportation systems,and pervasive computing and communications.Fog computing can help enhance these apps'productivity and lower the end-to-end delay experienced by such time-sensitive applications.In this research,we propose a reliable and secure service delivery strategy at the network edge for smart cities.To improve the availability and dependability,along with the security of smart city applications,the approach employs a combined method uniting distributed fog servers in addition to mist servers with the help of an intrusion detection system.Simulation findings suggest a reduction of 40.3%in the delay incurred by each service request for highly dense areas and 60.6%for moderately dense environments.Furthermore,the system has low false-negative rates and high detection and accuracy rates,decreasing service requests 2%. 展开更多
关键词 Security Reliability Trustworthy computing Resource provisioning Threat detection Fog computing Internet of things
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Erratum:Bio-inspired Fog Harvesting Fabric Materials:Principle,Fabrication,Engineering Applications and Challenges 认领 引用
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作者 Xueke Yang Sha Li +2 位作者 Xiaobo Wang Xiaoming Qian Songnan Zhang 《Journal of Bionic Engineering》 SCIE EI CSCD 2026年第1期549-549,共1页
The original online version of this article was revised:"The article Bio-inspired Fog Harvesting Fabric Materials:Principle,Fabrication,Engineering Applications and Challenges,written by Xueke Yang,Sha Li,Xiaobo ... The original online version of this article was revised:"The article Bio-inspired Fog Harvesting Fabric Materials:Principle,Fabrication,Engineering Applications and Challenges,written by Xueke Yang,Sha Li,Xiaobo Wang,Xiaoming Qian,and Songnan Zhang,was originally published under exclusive license to Jilin University.Following the authors'decision to opt for retrospective open access,the copyright of the article was changed on 27 April 2025 to©The Authors 2025.The article is now distributed under the terms of the Creative Commons Attribution License(http://gffzzeb6f7f563f66445dh00qq50pvbxpf6ffv.ffgz.tsg.suse.edu.cn/licenses/by/4.0),which permits unrestricted use,distribution,and reproduction in any medium,provided the original author(s)and source are credited." 展开更多
关键词 principle fog harvesting fabric materials fabrication challenges engineering applications bio inspired
Multi-Objective Enhanced Cheetah Optimizer for Joint Optimization of Computation Offloading and Task Scheduling in Fog Computing 认领 引用
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作者 Ahmad Zia Nazia Azim +5 位作者 Bekarystankyzy Akbayan Khalid J.Alzahrani Ateeq Ur Rehman Faheem Ullah Khan Nouf Al-Kahtani Hend Khalid Alkahtani 《Computers, Materials & Continua》 SCIE EI 2026年第3期1559-1588,共30页
The cloud-fog computing paradigm has emerged as a novel hybrid computing model that integrates computational resources at both fog nodes and cloud servers to address the challenges posed by dynamic and heterogeneous c... The cloud-fog computing paradigm has emerged as a novel hybrid computing model that integrates computational resources at both fog nodes and cloud servers to address the challenges posed by dynamic and heterogeneous computing networks.Finding an optimal computational resource for task offloading and then executing efficiently is a critical issue to achieve a trade-off between energy consumption and transmission delay.In this network,the task processed at fog nodes reduces transmission delay.Still,it increases energy consumption,while routing tasks to the cloud server saves energy at the cost of higher communication delay.Moreover,the order in which offloaded tasks are executed affects the system’s efficiency.For instance,executing lower-priority tasks before higher-priority jobs can disturb the reliability and stability of the system.Therefore,an efficient strategy of optimal computation offloading and task scheduling is required for operational efficacy.In this paper,we introduced a multi-objective and enhanced version of Cheeta Optimizer(CO),namely(MoECO),to jointly optimize the computation offloading and task scheduling in cloud-fog networks to minimize two competing objectives,i.e.,energy consumption and communication delay.MoECO first assigns tasks to the optimal computational nodes and then the allocated tasks are scheduled for processing based on the task priority.The mathematical modelling of CO needs improvement in computation time and convergence speed.Therefore,MoECO is proposed to increase the search capability of agents by controlling the search strategy based on a leader’s location.The adaptive step length operator is adjusted to diversify the solution and thus improves the exploration phase,i.e.,global search strategy.Consequently,this prevents the algorithm from getting trapped in the local optimal solution.Moreover,the interaction factor during the exploitation phase is also adjusted based on the location of the prey instead of the adjacent Cheetah.This increases the exploitation capability of agents,i.e.,local search capability.Furthermore,MoECO employs a multi-objective Pareto-optimal front to simultaneously minimize designated objectives.Comprehensive simulations in MATLAB demonstrate that the proposed algorithm obtains multiple solutions via a Pareto-optimal front and achieves an efficient trade-off between optimization objectives compared to baseline methods. 展开更多
关键词 Computation offloading task scheduling cheetah optimizer fog computing optimization resource allocation internet of things
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A Hybrid Harmony Search-Nondominated Sorting Approach for Cost-Efficient and Deadline-Aware Fog-Enabled IoT Placement 认领 引用
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作者 Zahra Farhadpour Tan Fong Ang Chee Sun Liew 《Computers, Materials & Continua》 SCIE EI 2026年第6期1961-1986,共26页
The heterogeneity and dynamic behavior of fog computing environments introduce major challenges to achieving optimal application placement.Limited fog resources and varying workloads often necessitate offloading appli... The heterogeneity and dynamic behavior of fog computing environments introduce major challenges to achieving optimal application placement.Limited fog resources and varying workloads often necessitate offloading applications beyond their local clusters,making it difficult to maintain the required level of service quality under varying conditions.In this context,placement methods must ensure a balanced trade-off between multiple objectives,such as time and cost,while maintaining reliable adherence to constraints like application deadlines and limited fog-node memory.Existing solutions,including heuristic,metaheuristic,learning-based,and hybrid optimization approaches,have been proposed to address these challenges.However,many of these methods rely on weighted objective formulations with limited visibility into trade-offs among conflicting objectives,emphasize local refinement over sustained exploration,or handle resource and deadline constraints implicitly,reducing their effectiveness in resource-constrained and dynamic fog environments.To overcome these limitations,this paper proposes a hybrid Harmony Search-Nondominated Sorting Genetic Algorithm(HS-NSGA),which integrates the improvisation operators of HS with the Pareto-based elitist selection of NSGA-Ⅱ.The proposed algorithm advances the state of the art by enabling unbiased trade-off exploration and preserving high-quality solutions while explicitly enforcing memory constraints and deadline requirements.HS serves as the primary search mechanism,generating diverse candidate placements through memory consideration,randomization,and pitch adjustment,while nondominated sorting and crowding distance guide the selection of high-quality trade-off solutions across iterations.To further improve robustness against constraint violations in dynamic conditions,a fraction of the population is diversified using NSGA-Ⅱ mutation and crossover operators.Experimental evaluations across heterogeneous fog-cloud scenarios demonstrate that HS-NSGA consistently achieves superior cost-time reduction compared with representative hybrid genetic and swarm-based methods while satisfying application deadline requirements and fog-node memory constraints.For makespan,HS-NSGA achieved reductions of 14.5%over LD-NPGA(Local Draft Niche-Pareto Genetic Algorithm),16.8%over FSPGA(Fog Service Placement Genetic Algorithm),19.5%over FSPPSO(Fog Service Placement Particle Swarm Optimization),and 16.1%over GA-FSA(Genetic Algorithm Flamingo Search Algorithm),with consistent improvements across varying task volumes.For cost,reductions reached 32.7%,35.5%,42.9%,and 30.7%over LD-NPGA,FSPGA,FSPPSO,and GA-FSA,respectively. 展开更多
关键词 Fog computing hybrid metaheuristics harmony search application placement multi-objective scheduling
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AI-Powered Anomaly Detection and Cybersecurity in Healthcare IoT with Fog-Edge 认领 引用 被引量：2
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作者 Fatima Al-Quayed 《Computer Modeling in Engineering & Sciences》 SCIE EI 2026年第1期1339-1372,共34页
The rapid proliferation of Internet of Things(IoT)devices in critical healthcare infrastructure has introduced significant security and privacy challenges that demand innovative,distributed architectural solutions.Thi... The rapid proliferation of Internet of Things(IoT)devices in critical healthcare infrastructure has introduced significant security and privacy challenges that demand innovative,distributed architectural solutions.This paper proposes FE-ACS(Fog-Edge Adaptive Cybersecurity System),a novel hierarchical security framework that intelligently distributes AI-powered anomaly detection algorithms across edge,fog,and cloud layers to optimize security efficacy,latency,and privacy.Our comprehensive evaluation demonstrates that FE-ACS achieves superior detection performance with an AUC-ROC of 0.985 and an F1-score of 0.923,while maintaining significantly lower end-to-end latency(18.7 ms)compared to cloud-centric(152.3 ms)and fog-only(34.5 ms)architectures.The system exhibits exceptional scalability,supporting up to 38,000 devices with logarithmic performance degradation—a 67×improvement over conventional cloud-based approaches.By incorporating differential privacy mechanisms with balanced privacy-utility tradeoffs(ε=1.0–1.5),FE-ACS maintains 90%–93%detection accuracy while ensuring strong privacy guarantees for sensitive healthcare data.Computational efficiency analysis reveals that our architecture achieves a detection rate of 12,400 events per second with only 12.3 mJ energy consumption per inference.In healthcare risk assessment,FE-ACS demonstrates robust operational viability with low patient safety risk(14.7%)and high system reliability(94.0%).The proposed framework represents a significant advancement in distributed security architectures,offering a scalable,privacy-preserving,and real-time solution for protecting healthcare IoT ecosystems against evolving cyber threats. 展开更多
关键词 AI-powered anomaly detection healthcare IoT fog computing cybersecurity intrusion detection
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Latency minimization for multiuser computation offloading in fog-radio access networks 认领 引用
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作者 Wei Zhang Shafei Wang +3 位作者 Ye Pan Qiang Li Jingran Lin Xiaoxiao Wu 《Digital Communications and Networks》 SCIE EI CSCD 2025年第1期160-171,共12页
Recently,the Fog-Radio Access Network(F-RAN)has gained considerable attention,because of its flexible architecture that allows rapid response to user requirements.In this paper,computational offloading in F-RAN is con... Recently,the Fog-Radio Access Network(F-RAN)has gained considerable attention,because of its flexible architecture that allows rapid response to user requirements.In this paper,computational offloading in F-RAN is considered,where multiple User Equipments(UEs)offload their computational tasks to the F-RAN through fog nodes.Each UE can select one of the fog nodes to offload its task,and each fog node may serve multiple UEs.The tasks are computed by the fog nodes or further offloaded to the cloud via a capacity-limited fronhaul link.In order to compute all UEs'tasks quickly,joint optimization of UE-Fog association,radio and computation resources of F-RAN is proposed to minimize the maximum latency of all UEs.This min-max problem is formulated as a Mixed Integer Nonlinear Program(MINP).To tackle it,first,MINP is reformulated as a continuous optimization problem,and then the Majorization Minimization(MM)method is used to find a solution.The MM approach that we develop is unconventional in that each MM subproblem is solved inexactly with the same provable convergence guarantee as the exact MM,thereby reducing the complexity of MM iteration.In addition,a cooperative offloading model is considered,where the fog nodes compress-and-forward their received signals to the cloud.Under this model,a similar min-max latency optimization problem is formulated and tackled by the inexact MM.Simulation results show that the proposed algorithms outperform some offloading strategies,and that the cooperative offloading can exploit transmission diversity better than noncooperative offloading to achieve better latency performance. 展开更多
关键词 Fog-radio access network Fog computing Majorization minimization WMMSE
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6G smart fog radio access network: Architecture, key technologies, and research challenges 认领 引用 被引量：3
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作者 Lincong Zhang Mingyang Zhang +1 位作者 Xiangyu Liu Lei Guo 《Digital Communications and Networks》 SCIE EI CSCD 2025年第3期898-911,共14页
The 6G smart Fog Radio Access Network(F-RAN)is an integration of 6G network intelligence technologies and the F-RAN architecture.Its aim is to provide low-latency and high-performance services for massive access devic... The 6G smart Fog Radio Access Network(F-RAN)is an integration of 6G network intelligence technologies and the F-RAN architecture.Its aim is to provide low-latency and high-performance services for massive access devices.However,the performance of current 6G network intelligence technologies and its level of integration with the architecture,along with the system-level requirements for the number of access devices and limitations on energy consumption,have impeded further improvements in the 6G smart F-RAN.To better analyze the root causes of the network problems and promote the practical development of the network,this study used structured methods such as segmentation to conduct a review of the topic.The research results reveal that there are still many problems in the current 6G smart F-RAN.Future research directions and difficulties are also discussed. 展开更多
关键词 6G Smart technology Smart fog radio access network Artificial intelligence Non-orthogonal multiple access Reconfigurable intelligent surface
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Fog Research in China:An Overview 认领 引用 被引量：101
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作者 牛生杰 陆春松 +2 位作者 于华英 赵丽娟 吕晶晶 《Advances in Atmospheric Sciences》 SCIE CAS 2010年第3期639-662,共24页
Fog can adversely affect human activity directly and indirectly, resulting in large losses both in terms of the local economy and lives. Much effort has been devoted to studies of fog across many areas of China, and i... Fog can adversely affect human activity directly and indirectly, resulting in large losses both in terms of the local economy and lives. Much effort has been devoted to studies of fog across many areas of China, and in that context this paper aims to summarize climatic characteristics and review fog field experiments and their major results relating to fog mechanisms, physical properties and chemical characteristics. Progress in the application of remote sensing techniques and numerical simulation in fog research are also discussed. In particular, the effects of urbanization and industrialization on fog are highlighted. To end, perspectives on future fog research are outlined. The goal of this review paper is to introduce fog research in China to the global academic community and thus promote international collaboration on fog research. This is important because most papers on fog in China are published in Chinese, which are unreadable for the vast majority of non-Chinese researchers. 展开更多
关键词 fog climatic characteristics fog observations fog mechanisms physicochemical characteristics,remote sensing fog modeling
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Ensemble-Based Adaptive Observations for Improving Sea Fog Prediction in Coastal Regions around the Bohai Sea:Case Study with Cold-Front Synoptic Pattern 认领 引用 被引量：1
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作者 Huiqin HU Chengqing RUAN Xiaolin YU 《Advances in Atmospheric Sciences》 SCIE CAS CSCD 2025年第4期794-815,共22页
This study explored the observation strategy and effectiveness of synoptic-scale adaptive observations for improving sea fog prediction in coastal regions around the Bohai Sea based on a poorly predicted fog event wit... This study explored the observation strategy and effectiveness of synoptic-scale adaptive observations for improving sea fog prediction in coastal regions around the Bohai Sea based on a poorly predicted fog event with cold-front synoptic pattern(CFSP).An ensemble Kalman filter data assimilation system for the Weather Research and Forecasting model was adopted with ensemble sensitivity analysis(ESA).By comparing observation impacts(estimated from a 40-member ensemble with ESA)among different meteorological observation variables and pressure levels,the temperature at 850 hPa and surface layer(850 hPa-and-surface temperature)was selected as the target observation type.Additionally,the area with large observation impacts for this observation type was predicted in the transition region of the surface low–high system.This area developed southward with the low and moved eastward with the low–high system,which could be explained by the main features of CFSP.Moreover,both experiments assimilating synthetic and real observations showed that assimilating 850 hPa-and-surface temperature observations generally yielded better fog coverage forecasts in areas with greater observation impacts than areas with smaller impacts.However,the effectiveness of adaptive observations was reduced when real observations rather than synthetic observations were assimilated,which is possibly due to factors such as observation and model errors.The main conclusions above were verified by another typical fog event with CFSP characteristics.Results of this study highlight the importance of improved initial conditions in the transition region of the low–high system for improving fog prediction and provide scientific guidance for implementing an observation network for fog forecasting over the Bohai Sea. 展开更多
关键词 sea fog forecasting synoptic-scale adaptive observations ESA method observations of temperature profile below 850 hPa cold-front synoptic pattern
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Physical-layer secure hybrid task scheduling and resource management for fog computing IoT networks 认领 引用 被引量：1
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作者 ZHANG Shibo GAO Hongyuan +1 位作者 SU Yumeng SUN Rongchen 《Journal of Systems Engineering and Electronics》 SCIE CSCD 2025年第5期1146-1160,共15页
Fog computing has emerged as an important technology which can improve the performance of computation-intensive and latency-critical communication networks.Nevertheless,the fog computing Internet-of-Things(IoT)systems... Fog computing has emerged as an important technology which can improve the performance of computation-intensive and latency-critical communication networks.Nevertheless,the fog computing Internet-of-Things(IoT)systems are susceptible to malicious eavesdropping attacks during the information transmission,and this issue has not been adequately addressed.In this paper,we propose a physical-layer secure fog computing IoT system model,which is able to improve the physical layer security of fog computing IoT networks against the malicious eavesdropping of multiple eavesdroppers.The secrecy rate of the proposed model is analyzed,and the quantum galaxy–based search algorithm(QGSA)is proposed to solve the hybrid task scheduling and resource management problem of the network.The computational complexity and convergence of the proposed algorithm are analyzed.Simulation results validate the efficiency of the proposed model and reveal the influence of various environmental parameters on fog computing IoT networks.Moreover,the simulation results demonstrate that the proposed hybrid task scheduling and resource management scheme can effectively enhance secrecy performance across different communication scenarios. 展开更多
关键词 fog computing Internet-of-Things(IoT) physical layer security hybrid task scheduling and resource management quantum galaxy-based search algorithm(QGSA)
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Impact of the Changbai Mountains'topography on spring fog over the Bohai Sea 认领 引用
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作者 Meng Tian Ying Wen +3 位作者 Lihong Meng Ye Zhang Shu Liu Yang Guo 《Atmospheric and Oceanic Science Letters》 CSCD 2025年第4期54-60,共7页
Fog is a highly complex weather phenomenon influenced by numerous factors.This study investigated the impact of the Changbai Mountains’topography on the formation and development of spring fog in the Bohai Sea.From 1... Fog is a highly complex weather phenomenon influenced by numerous factors.This study investigated the impact of the Changbai Mountains’topography on the formation and development of spring fog in the Bohai Sea.From 12 to 14 May 2021,the Bohai region experienced a sea fog event.Utilizing Himawari-8 satellite data,ERA5 reanalysis dataset,land and sea station observations,the WRF model,a topography sensitivity experiment,and backward trajectory tracking,the influence of the Changbai Mountains’topography on the evolution of this sea fog event was assessed.Results indicated that the Changbai Mountains’topography significantly impacted the propagation and concentration of the sea fog through dual effects—namely,the Venturi Effect and Foehn Clearance Effect.Comparative simulations incorporating and excluding the Changbai Mountains revealed that its topography favored weak convergence(Venturi Effect)of low-level airflow over the Bohai Sea induced by a high-pressure system,promoting westward fog expansion.Additionally,the backward trajectory analysis further indicated that the Foehn Clearance Effect of the Changbai Mountains extended its influence far beyond the immediate lee side,contributing to significant changes in atmospheric conditions such as reductions in relative humidity and increases in potential temperature.The dry,warm foehn contributed to a reduction in the liquid water content,ultimately leading to the weakening or even dissipation of the sea fog in the region close to the Changbai Mountains.This study emphasizes the crucial role of the Changbai Mountains’topography in the development and evolution of fog,providing valuable insights for forecasting fog in regions with complex terrain. 展开更多
关键词 Bohai Sea Spring fog Numeral simulation Topography Foehn Clearance Effect
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Edge-Fog Enhanced Post-Quantum Network Security: Applications, Challenges and Solutions 认领 引用
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作者 Seo Yeon Moon Byung Hyun Jo +2 位作者 Abir El Azzaoui Sushil Kumar Singh Jong Hyuk Park 《Computers, Materials & Continua》 SCIE EI 2025年第7期25-55,共31页
With the rapid advancement of ICT and IoT technologies,the integration of Edge and Fog Computing has become essential to meet the increasing demands for real-time data processing and network efficiency.However,these t... With the rapid advancement of ICT and IoT technologies,the integration of Edge and Fog Computing has become essential to meet the increasing demands for real-time data processing and network efficiency.However,these technologies face critical security challenges,exacerbated by the emergence of quantum computing,which threatens traditional encryption methods.The rise in cyber-attacks targeting IoT and Edge/Fog networks underscores the need for robust,quantum-resistant security solutions.To address these challenges,researchers are focusing on Quantum Key Distribution and Post-Quantum Cryptography,which utilize quantum-resistant algorithms and the principles of quantum mechanics to ensure data confidentiality and integrity.This paper reviews the current security practices in IoT and Edge/Fog environments,explores the latest advancements in QKD and PQC technologies,and discusses their integration into distributed computing systems.Additionally,this paper proposes an enhanced QKD protocol combining the Cascade protocol and Kyber algorithm to address existing limitations.Finally,we highlight future research directions aimed at improving the scalability,efficiency,and practicality of QKD and PQC for securing IoT and Edge/Fog networks against evolving quantum threats. 展开更多
关键词 Edge computing fog computing quantum key distribution security post-quantum cryptography cascade protocol
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A Bioinspired Method for Optimal Task Scheduling in Fog-Cloud Environment 认领 引用
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作者 Ferzat Anka Ghanshyam G.Tejani +1 位作者 Sunil Kumar Sharma Mohammed Baljon 《Computer Modeling in Engineering & Sciences》 SCIE EI 2025年第3期2691-2724,共34页
Due to the intense data flow in expanding Internet of Things(IoT)applications,a heavy processing cost and workload on the fog-cloud side become inevitable.One of the most critical challenges is optimal task scheduling... Due to the intense data flow in expanding Internet of Things(IoT)applications,a heavy processing cost and workload on the fog-cloud side become inevitable.One of the most critical challenges is optimal task scheduling.Since this is an NP-hard problem type,a metaheuristic approach can be a good option.This study introduces a novel enhancement to the Artificial Rabbits Optimization(ARO)algorithm by integrating Chaotic maps and Levy flight strategies(CLARO).This dual approach addresses the limitations of standard ARO in terms of population diversity and convergence speed.It is designed for task scheduling in fog-cloud environments,optimizing energy consumption,makespan,and execution time simultaneously three critical parameters often treated individually in prior works.Unlike conventional single-objective methods,the proposed approach incorporates a multi-objective fitness function that dynamically adjusts the weight of each parameter,resulting in better resource allocation and load balancing.In analysis,a real-world dataset,the Open-source Google Cloud Jobs Dataset(GoCJ_Dataset),is used for performance measurement,and analyses are performed on three considered parameters.Comparisons are applied with well-known algorithms:GWO,SCSO,PSO,WOA,and ARO to indicate the reliability of the proposed method.In this regard,performance evaluation is performed by assigning these tasks to Virtual Machines(VMs)in the resource pool.Simulations are performed on 90 base cases and 30 scenarios for each evaluation parameter.The results indicated that the proposed algorithm achieved the best makespan performance in 80% of cases,ranked first in execution time in 61%of cases,and performed best in the final parameter in 69% of cases.In addition,according to the obtained results based on the defined fitness function,the proposed method(CLARO)is 2.52%better than ARO,3.95%better than SCSO,5.06%better than GWO,8.15%better than PSO,and 9.41%better than WOA. 展开更多
关键词 Improved ARO fog computing task scheduling GoCJ_Dataset chaotic map levy flight
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Summer Arctic sea fog 认领 引用 被引量：2
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作者 Xie Simei, Xue Zhenhe, Jiang Dezhong, Zou Bin, Qu Shaohou 《Acta Oceanologica Sinica》 SCIE CAS 2001年第2期183-196,共14页
Synchronous or quasi-synchronous sea-land-air observations were conducted using advanced sea ice, atmospheric and marine instruments during China's First Arctic Expedition. Expedition.Based on the Precious data fr... Synchronous or quasi-synchronous sea-land-air observations were conducted using advanced sea ice, atmospheric and marine instruments during China's First Arctic Expedition. Expedition.Based on the Precious data from the expedition, it was found that in the Arctic Ocean, most part of which is covered with ice or is mixed with ice, various kinds of sea fog formed such as advection fog, radiation fog and vapor fog. Each kind he its own characteristic and mechanics of creation. In the southern part of the Arctic Ocean, due to the sufficient warm and wet flow there, it is favorable for advection fog to form, which is dense and lasts a long time. On ice cap or vast floating ice, due to the strong radiation cooling effect, stable radiating fog is likely to form. In floating ice area there forms vapor fog with the appearance of masses of vapor from a boiling pot, which is different from short-lasting land fog. The study indicates that the reason why there are many kinds of sea fog form in the Arctic Ocean is because of the complicated cushion and the consequent sea-air interaction caused by the sea ice distribution and its unique physical characteristics. Sea fog is the atmospheric phenomenon of sea-air heat exchange. Especially, due to the high albedo of ice and snow surface, it is diffcult to absorb great amount of solar radiation during the polar days. Besides, ice is a poor conductor of heat; it blocks the sea-air heat exchange. The sea-air exchange is active in floating ice area where the ice is broken. The sea sends heat to the atmosphere in form of latent heat; vapor fog is a way of sea-air heat exchange influencing the climate and an indicator of the extent of the exchange. The study also indicates that the sea also transports heat to the atmosophere in form of sensible heat when vapor fog occurs. 展开更多
关键词 Arctic sea fog vapor fog radiation fog advection fog mechanism of the creation of sea fog
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A Fog-Based Approach for Theft Detection and Zero-Day Attack Prevention in Smart Grid Systems 认领 引用
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作者 Remah Younisse Mouhammd AlKasassbeh Amjad Aldweesh 《Computers, Materials & Continua》 SCIE EI 2025年第12期4921-4941,共21页
Smart grid systems are advancing electrical services,making them more compatible with Internet of Things(IoT)technologies.The deployment of smart grids is facing many difficulties,requiring immediate solutions to enha... Smart grid systems are advancing electrical services,making them more compatible with Internet of Things(IoT)technologies.The deployment of smart grids is facing many difficulties,requiring immediate solutions to enhance their practicality.Data privacy and security are widely discussed,and many solutions are proposed in this area.Energy theft attacks by greedy customers are another difficulty demanding immediate solutions to decrease the economic losses caused by these attacks.The tremendous amount of data generated in smart grid systems is also considered a struggle in these systems,which is commonly solved via fog computing.This work proposes an energytheft detection method for smart grid systems employed in a fog-based network infrastructure.This work also proposes and analyzes Zero-day energy theft attack detection through a multi-layered approach.The detection process occurs at fog nodes via five machine-learning classification models.The performance of the classifiers is measured,validated,and reported for all models at fog nodes,as well as the required training and testing time.Finally,the measured results are compared to when the detection process occurs at a central processing unit(cloud server)to investigate and compare the performance metrics’goodness.The results show comparable accuracy,precision,recall,and F1-measure performance.Meanwhile,the measured execution time has decreased significantly in the case of the fog-based network infrastructure.The fog-based model achieved an accuracy and recall of 98%,F1 score of 99%,and reduced detection time up to around 85%compared to the cloud-based approach. 展开更多
关键词 Smart grid security fog computing energy theft detection zero-day attack prevention machine learning in IoT
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Recent Observations and Modeling Study About Sea Fog over the Yellow Sea and East China Sea 认领 引用 被引量：1
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作者 ZHANG Suping 《Journal of Ocean University of China》 SCIE CAS 2012年第4期465-472,共8页
This review presents some of the latest achievements in sea fog research,including fog climatology,fog structure in the marine atmospheric boundary layer,and numerical simulations and forecasting of fog.With the devel... This review presents some of the latest achievements in sea fog research,including fog climatology,fog structure in the marine atmospheric boundary layer,and numerical simulations and forecasting of fog.With the development of atmospheric observational techniques and equipments,new facts about sea fog are revealed.The mechanisms involved in the formation,development and dissipation of sea fog are further explored with the help of advanced atmospheric models. 展开更多
关键词 sea fog climatology sea fog structure atmospheric boundary layer sea fog observation sea fog simulation
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