Edge computing for Industry 5.0: fundamental, applications and research challenges

Internet of Things: A Survey on Enabling Technologies, Protocols, and Applications

Al-Fuqaha, A., Guizani, M., Mohammadi, M., Aledhari, M., & Ayyash, M. (2015) · IEEE Communications Surveys & Tutorials · doi:10.1109/comst.2015.2444095 · Cited by 8,630 · cited 1×

Industry 4.0: state of the art and future trends

Xu, L. D., Xu, E. L., & Li, L. (2018) · International Journal of Production Research · doi:10.1080/00207543.2018.1444806 · Cited by 3,405

The expected contribution of Industry 4.0 technologies for industrial performance

Dalenogare, L. S., Benitez, G. B., Ayala, N. F., & Frank, A. G. (2018) · International Journal of Production Economics · doi:10.1016/j.ijpe.2018.08.019 · Cited by 2,201

6G Wireless Communication Systems: Applications, Requirements, Technologies, Challenges, and Research Directions

Chowdhury, M. Z., Shahjalal, M. A., Ahmed, S., & Jang, Y. M. (2020) · IEEE Open Journal of the Communications Society · doi:10.1109/ojcoms.2020.3010270 · Cited by 1,925

Industry 5.0: A survey on enabling technologies and potential applications

Maddikunta, P. K. R., Pham, Q.-V., B, P., Deepa, N., Dev, K., Gadekallu, T. R., Ruby, R., & Liyanage, M. (2022) · Journal of Industrial Information Integration · doi:10.1016/j.jii.2021.100257 · Cited by 1,890

Digital Twin-driven smart manufacturing: Connotation, reference model, applications and research issues

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A Survey on Metaverse: Fundamentals, Security, and Privacy

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6G Wireless Communications: Vision and Potential Techniques

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Survey on fog computing: architecture, key technologies, applications and open issues

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Industrial Artificial Intelligence in Industry 4.0 - Systematic Review, Challenges and Outlook

Peres, R. S., Jia, X., Lee, J., Sun, K., Colombo, A. W., & Barata, J. (2020) · IEEE Access · doi:10.1109/access.2020.3042874 · Cited by 820

A containerized Edge AI predictive maintenance infrastructure for rotating components using continuous wavelet transform images and Transformer UNet autoencoder for Industry 4.0

Keshavarz, M. A., & Sharifian, S. (2025) · The Journal of Supercomputing · doi:10.1007/s11227-025-07904-5 · Cited by 1

A container optimal matching deployment algorithm based on CN-Graph for mobile edge computing

Rao, H., Chen, S., Du, Y., Xu, X., Chen, H., & Jia, G. (2024) · The Journal of Supercomputing · doi:10.1007/s11227-024-06450-w

Impactos da inovação e da diversidade no valor das empresas: uma análise bibliométrica e revisão sistemática da literatura

de Oliveira, C. H. F., & Jucá, M. N. (2025) · International Journal of Innovation · doi:10.5585/2025.26422

Utilizing Digital Twins for Predictive Modelling in Manufacturing Cyber-Physical Systems

Maheswari, B. U., Sujatha, R., Deekshitha, V., & Ananth, V. (2025) · Communications in computer and information science · doi:10.1007/978-3-031-86302-8_20

Zero-Shot Binarization Lightweight Model for a Data-Free Edge Network

Zeng, K., Gu, H., Duan, Y., Shen, T., & Li, R. (2025) · IEEE Transactions on Cognitive Communications and Networking · doi:10.1109/tccn.2025.3569598

Anomaly Detection for Multi-tenant Networks Based on AutoEncoder

Kim, Y., Park, J., & Kim, J. (2025) · Lecture notes in computer science · doi:10.1007/978-981-96-7071-0_25

Optimal Contract Formulation for Mobile Edge Computing Task Offloading in Heterogeneous Networks Considering the Age of Information

Sun, Z., & Wang, P. (2025) · IEICE Transactions on Information and Systems · doi:10.1587/transinf.2024edp7289

Geleceğin Üretim Devrimi Olarak Endüstri 5.0: Kavramsal Bir Değerlendirme

Koska, A. (2025) · İktisadi İdari ve Siyasal Araştırmalar Dergisi · doi:10.25204/iktisad.1657113

Guest Editorial: Edge Intelligence for Next Generation Industrial IoT Applications

Menon, V. G., Adhikari, M., Gupta, B. B., Hazra, A., & Mastorakis, S. (2025) · IET Networks · doi:10.1049/ntw2.70008

HADML: Hierarchical Asynchronous Deep Mutual Learning in Edge Intelligence Systems

Yin, R., Wang, T., Liu, S., Wu, C., Chen, X., & Liu, Y. (2025) · IEEE Transactions on Vehicular Technology · doi:10.1109/tvt.2025.3587453

Application of TCN Edge Operation Model in Photovoltaic Power Generation Forecasting

Zhang, S., Liu, B., Zhang, Q., Wu, G., Liu, Y., & Zhang, W. (2025) · IEEE International Conference on Electronic Technology, Communication and Information (ICETCI) · doi:10.1109/icetci64844.2025.11084131

Real Time Sensor Data Validation Using FPGA Accelerated Artificial Neural Networks

Ali, M. T., Mohammed, M. S., Al-Jumaili, A. M., & Saleh, A. H. (2025) · Journal Européen des Systèmes Automatisés · doi:10.18280/jesa.580610

Advances in Mathematical Cryptography and Information Security Toward Industry 5.0

Lee, C., Do, D., & Imoize, A. L. (2025) · Mathematics · doi:10.3390/math13162660

Implementing IoT Technology on Mobile Platform: Edge-Cloud Integration and Data Handling

Krejčí, J., Babiuch, M., Wierbica, R., & Krys, V. (2025) · Mechanisms and machine science · doi:10.1007/978-3-032-02106-9_2

Master-Device-Coordinated Optimization for Distributed CNN Inference at the Edge

Guo, H. Y., & Wang, X. (2025) · International Symposium on Robotics, Artificial Intelligence and Information Engineering (RAIIE) · doi:10.1109/raiie65740.2025.11140395

Ai-driven energy-aware task offloading with network traffic considerations in fog-cloud environments

Zolghadri, M., Asghari, P., Dashti, S., & Hedayati, A. (2025) · Cluster Computing · doi:10.1007/s10586-025-05446-2

Next-Gen Shopping: The Smart Shoppe Trolley for Autonomous Retail Navigation

Agrawal, V., Suryansh, Dwivedi, Y. K., Jitender, Sharma, A., & Maurya, A. K. (2025) · International Conference on Energy, Power and Environment (ICEPE) · doi:10.1109/icepe65965.2025.11139722

An Evaluation of YOLOv7 and YOLOv7-Tiny Models for Spool Counting Tasks on the Edge for Industrial Automation

Sitatham, M., & Rongchai, K. (2025) · IEEE Symposium on Computers & Informatics (ISCI) · doi:10.1109/isci65687.2025.11167262

Foundations of cybersecurity and edge computing

Khan, K., & Goodridge, W. S. (2025) · Elsevier eBooks · doi:10.1016/b978-0-443-34109-0.00008-5

Safe Edge Intelligent Control With Cross-Loop Constraints and Stability Guarantees

Xue, C., & Ma, Y. (2025) · IEEE Transactions on Automation Science and Engineering · doi:10.1109/tase.2025.3620556

Sustainable Synergy: Transforming the Textile Sector by Leveraging Industry 5.0 Enablers

Awasthi, K., Padwekar, K., Shamim, K., & Misra, S. C. (2025) · Sustainable Development · doi:10.1002/sd.70336

Edge-AD: An Edge-Oriented Anomaly Detection Approach with Gated Fusion and Dynamic Thresholding

Wang, C., Wang, T., Chu, Y., Yang, X., & Su, Z. (2025) · International Conference on Internet of Things, Artificial Intelligence and Mechanical Automation (IoTAIMA) · doi:10.1109/iotaima66468.2025.11212741

Testbed-Validated Optimized Federated Remote Inspection for App Vending in Distributed Edge Caching Systems

Ali, M. N., & Liu, X. (2025) · IEEE Transactions on Mobile Computing · doi:10.1109/tmc.2025.3626937

VM-ORAM: A Novel High-Performance ORAM Architecture for Efficient Data Integrity Verification in Industrial Cloud

Li, C., Chen, W., Liu, G., Tan, C. K., Liu, L., Ye, W., & Chronopoulos, A. T. (2025) · IEEE Transactions on Industrial Informatics · doi:10.1109/tii.2025.3624225

Advancing Industry 5.0 with IoT Transformations: Future Prospectives

Tunwal, B., Kaur, A., & Kumar, S. (2025) · International Conference on Next Generation of Green Information and Emerging Technologies (GIET) · doi:10.1109/giet65294.2025.11234847

Efficiency optimization of AI automatic control systems via heuristic scheduling in edge computing environments

Han, L., Wang, J., Ren, D., Li, X.-L., & Cui, W. (2025) · International Journal of Parallel Emergent and Distributed Systems · doi:10.1080/17445760.2025.2591041

A DRL-based workflow scheduling for cost and delay minimization in vehicular networks

Yin, L., Wu, W., Huang, J. Y., Luo, H., Liang, W., & Li, K. (2025) · The Journal of Supercomputing · doi:10.1007/s11227-025-08021-z

OLASS: Online Lyapunov Optimization with Selective Scheduling in High-Load Edge Computing

Zhang, Y., Rong, X., & Tao, Y. (2025) · IEEE International Symposium on Parallel and Distributed Processing with Applications (ISPA) · doi:10.1109/ispa67752.2025.00030

Fault-Tolerant Resource Allocation and Task Offloading Scheme for UAV NOMA-MEC Networks

Zhang, Q., Zhang, H., Zhang, S., Liao, K., & Habib, A. (2025) · IEEE International Symposium on Parallel and Distributed Processing with Applications (ISPA) · doi:10.1109/ispa67752.2025.00038

Layer-Reused Collaborative Scheduling for Container-Dependent Tasks in Industrial Real-Time Systems

Zhang, H., Lin, W., Huang, Y., Wu, H., Wu, C., & Li, K. (2025) · ACM Transactions on Embedded Computing Systems · doi:10.1145/3779131

A Proposed IoT System for Monitoring and Controlling Movable Zamzam Tanks in the Holy Mosque

Mohamed, T. M. (2025) · International Journal of Advanced Computer Science and Applications · doi:10.14569/ijacsa.2025.0161113

Theoretical Insights into Organizational Sustainability Management in the Context of Industry 5.0

Vagiuc, P.-D., Pîslaru, M., & Herghiligiu, I. V. (2025) · International Conference on Electromechanical and Energy Systems (SIELMEN) · doi:10.1109/sielmen67352.2025.11260805

A Profit-aware Mobile Server Deployment Approach in Edge Computing

Chen, Y., Dong, H., Jin, X., & Wang, Z. (2025) · International Conference on Networking and Network Applications (NaNA) · doi:10.1109/nana66698.2025.00050

Dual-Algorithm Framework for Privacy-Preserving Task Scheduling Under Historical Inference Attacks

Chen, E., Ye, A., & Deng, H. (2025) · Computers · doi:10.3390/computers14120558

Edge-Native IoT Data Architectures for Practitioners: A Glass Manufacturing Use Case

Antonini, M., Rubini, A., Dallapiccola, D., Vecchio, M., Peghini, N., & Antonelli, F. (2025) · IEEE Internet of Things Magazine · doi:10.1109/miot.2025.3635403

Federated Multi-Label Feature Selection via Dual-Layer Hybrid Breeding Cooperative Particle Swarm Optimization with Manifold and Sparsity Regularization

Zhang, S., Jin, H., Ye, Z., Yang, J., Zhang, J., Wu, D., Zheng, X., & Song, D. (2025) · Computers, materials & continua/Computers, materials & continua (Print) · doi:10.32604/cmc.2025.068044

Challenges and opportunities of electric mobility towards industry 5.0: The case of Costa Rica

Atencio, G. S. (2025) · LACCEI International Multi-Conference for Engineering, Education and Technology (LACCEI) · doi:10.18687/laccei2025.1.1.266

Theoretical Design for a Self-Powered Disaster Resilient Seismic Response System Using Piezoelectric HarvestingPreprint

Dubey, A. (2025) · SSRN Electronic Journal · doi:10.2139/ssrn.5727382

Human BlackBox: An Edge AI-based Real-Time Emergency Detection System

Koduppanapolackal, J. J., Rozario, N. J., & Mahalakshmi, P. (2025) · International Conference on IoT Based Control Networks and Intelligent Systems (ICICNIS) · doi:10.1109/icicnis66685.2025.11315541

QSC: An Edge Server Placement Strategy Based on Spectral Clustering and Q-Learning

Zhou, Z., Ou, X., Yu, T., & Liu, J. (2026) · Communications in computer and information science · doi:10.1007/978-981-95-3483-8_36

Edge Computing Announcements and Stock Value: A Signaling Theory View

Lin, S., Chan, H. K., Shao, J., & Li, B. (2026) · Responsible innovation in industry · doi:10.1007/978-981-95-5819-3_10

Reinforcement Learning-Driven MOEA Framework for Secure and Efficient Task Scheduling in Cloud-Edge Systems

Smithamol, M. B., Haripriya, A., & Sridhar, R. (2026) · Lecture notes in networks and systems · doi:10.1007/978-981-96-9191-3_23

Publicly verifiable information sharing solution in edge computing scenarios

Liu, W., & Xue, Q. (2025) · International Conference on Intelligent Informatics and Biomedical Sciences (ICIIBMS) · doi:10.1109/iciibms66230.2025.11316697

FCAC: Content-Aware Adaptive Configuration with Scene-Target Fusion in Edge Video Analytics

Li, Y., Yao, R., Cao, Z., & Shen, J. (2025) · IEEE International Conference on Parallel and Distributed Systems (ICPADS) · doi:10.1109/icpads67057.2025.11322932

Periodic Review on Decentralized Framework in Edge Computing

Shirke, H. S., & Gavankar, N. L. (2025) · International Conference on Future Technologies (ICFT) · doi:10.1109/icft66708.2025.11336553

PBEVFormer: A Lightweight Pedestrian Detection Method Based on Attention Optimization and Model Pruning

Dong, T., Sun, B., Peng, B., Fu, Y., & Zeng, J. (2025) · International Conference on Communication and Information Processing (ICCIP) · doi:10.1145/3784833.3784895

PAHInA: Precision-Aware Hierarchical In-Network Aggregation for Edge Distributed Training

Nian, Y., Yi, B., He, Q., Wang, X., Min, G., Li, K., & Das, S. K. (2026) · IEEE Transactions on Networking · doi:10.1109/ton.2026.3660333

Customizing Human Machine Interfaces leveraging Digital Twins and Large Language Models

Franco, F., Lamazzi, L., Picone, M., Savarese, M., Grazia, C. A., & Bedogni, L. (2026) · IEEE Consumer Communications and Networking Conference · doi:10.1109/ccnc65079.2026.11366401

Industry 5.0 as the Manufacturing Revolution of the Future: A Conceptual Assessment

Koska, A. (2025) · DergiPark (Istanbul University)

Secure FPGA Fabric Architecture for Edge AI Applications in Smart Industrial Monitoring

Balassem, Z. A., & Hussein, R. R. (2026) · Lecture notes in electrical engineering · doi:10.1007/978-981-95-5831-5_42

Edge AI for Industry 5.0: Challenges and Opportunities

Medojević, M., Tošić, M., Bajić, B., & Rikalović, A. (2026) · Lecture notes in networks and systems · doi:10.1007/978-3-032-04890-5_6

Deep Learning at the Edge: Pushing AI Beyond the Cloud

Sharma, M., Saini, H. C., Saxena, A., Agarwal, S., Chaudhary, S., & Sikarwal, P. K. (2025) · IEEE International Conference on Blockchain and Distributed Systems Security (ICBDS) · doi:10.1109/icbds67396.2025.11377984

A Framework for Multi-constrained Optimization in Fog-Cloud Task Scheduling

Pinky, Verma, K., & Kumar, A. (2026) · Lecture notes in networks and systems · doi:10.1007/978-3-032-09825-2_16

Long-Term Multivariate Forecasting of Quality Variables in Industrial Production Processes Based on a Hybrid Deep Learning Framework and Novel Flexible Sensor

Li, K., Wang, Q., Liu, H., Wang, M., Cui, Y., & Qin, J. (2026) · IEEE Transactions on Instrumentation and Measurement · doi:10.1109/tim.2026.3666071

A Study on Machine Learning Models Performance Analysis in Smart Home Appliances

Karrolla, B., Kar, U. N., & Das, R. K. (2025) · OITS International Conference on Information Technology (OCIT) · doi:10.1109/ocit66168.2025.11399953

A dynamic security evaluation model for vehicular edge computing information system

Guo, Z., Zuo, J., Xie, W., Lu, Y., Wang, Z., Tian, H., Cao, R., & Ma, S. (2026) · Peer-to-Peer Networking and Applications · doi:10.1007/s12083-026-02216-8

Intelligent Computing Framework for Real-Time Decision-Making in Industry 5.0 Applications

Suri, S., Mokashi, S. P., Guntupalli, B. K. R., Kiran, K. R., Linkalapalli, K., & Chaudhary, V. (2025) · International Conference on Advances in Computation, Communication and Information Technology (ICAICCIT) · doi:10.1109/icaiccit68829.2025.11434024

Addressing Global Challenges and Overcoming Barriers to the Widespread Adoption of Precision Agriculture Technologies

Yasmeen, F., Hussain, S., Iqbal, M. H., Ehsan, M., & Raja, N. I. (2026) · Advances in computational intelligence and robotics book series · doi:10.4018/979-8-3373-7257-0.ch013

AI-powered predictive analytics models for early disease detection in digital twin-enabled healthcare

Giri, V. V., Chavan, S. V., Mulla, R. M., & Patil, N. S. (2026) · Advances in computers · doi:10.1016/bs.adcom.2026.02.005

Monitoring Approaches for Smart Robotic Dental Workstations Using IoT Architectures

Krajňák, F., Duplák, J., Yeromina, M., & Adamčík, M. (2026) · SAR Journal - Science and Research · doi:10.18421/sar91-09

Distributed Semantic Communication Network with Adaptive Channel Conditions and Transmission Rates Joint Source-Channel Coding

Zhao, X., Ji, H., Yuan, P., & Cheng, X. (2026) · Lecture notes in computer science · doi:10.1007/978-981-95-8417-8_26

Edge Computing and Federated Learning as Enabling Technologies for Industry 5.0: A Literature Review with an Industrial Focus

Moreno-Castellanos, J., Velasco, J. M. N., & la Prieta, F. D. (2026) · Lecture notes in networks and systems · doi:10.1007/978-3-032-05748-8_8

Blockchain-Empowered Federated Learning Applications in Smart Manufacturing: A Literature Review

Khan, M. I., Farahani, M. A., & Wuest, T. (2026) · Journal of Computing and Information Science in Engineering · doi:10.1115/1.4071613

Research on Safety Detection and Management Optimization Based on Machine Vision Inspection

刘, 沅. (2026) · Mechanical Engineering and Technology · doi:10.12677/met.2026.152019

Edge Computing: Processing at the Edge

Sardar, T. H. (2026) · Springer eBooks · doi:10.1007/978-3-032-19632-3_13

High-frequency monitoring of watershed soil erosion regimes via edge-deployed lightweight deep learning: An ordinal morphological proxy for transient sediment transportPreprint

He, W., Fu, Y., Li, R., Sun, Z., Lin, Y., Zhang, X., Li, K., Xu, Y., & Sun, L. (2026) · SSRN Electronic Journal · doi:10.2139/ssrn.6585179

Ahafed: accelerated hierarchical aggregation for heterogeneous federated learning in multi-UAV networks

Liu, X., Wu, G., Li, S., Liu, Y., Li, Y., Yu, S., & Li, X. (2026) · International Journal of Machine Learning and Cybernetics · doi:10.1007/s13042-026-03015-6

Behavioral Conflict Modeling for AI-Enabled Intelligent Manufacturing: A Risk-Attitude Extension of Graph Model for Conflict Resolution

Лю, П., Pan, Q., Zhu, B., & Wang, P. (2026) · IEEE Transactions on Engineering Management · doi:10.1109/tem.2026.3687286

Integrated Collaborative Architecture of Heterogeneous Unmanned Equipment Platform in Naval Warfare Based On Edge Computing

Guo, W., Xu, C., Shu, J., & Cui, G. (2025) · China Automation Congress (CAC) · doi:10.1109/cac67268.2025.11487212

Distribution network risk prediction based on data mining and improved PSO fused with SVM

Li, J., Xie, X., Jiang, J., Zhang, C., & Xu, X. (2026) · Scientific Reports · doi:10.1038/s41598-026-49979-x

Meta-Reinforcement Learning for Computation Offloading and Resource Allocation in MEC-Enabled Immersive Metaverse

Wang, Q., Jin, H., Dong, H., Zhang, P., Qin, A. K., & Gu, T. (2026) · IEEE Transactions on Mobile Computing · doi:10.1109/tmc.2026.3688757

From Edge to Cloud: A Modular Middleware for Hybrid Digital Twins

Flores-Martin, D., Lemus-Prieto, F., & Rico‐Gallego, J. (2026) · IEEE Internet Computing · doi:10.1109/mic.2026.3688189

Digital twin-driven edge–cloud collaborative remote fault diagnosis and intelligent predictive maintenance for critical hydropower equipment

Yang, D., Jiang, Z., Zheng, K., & Wang, Y. (2026) · Discover Artificial Intelligence · doi:10.1007/s44163-026-01998-3

Edge-Sage: GraphSAGE Framework for Decentralized Intrusion Detection in Edge IoT Networks

A.Hassan, F. A., & Al-Ameer, A. A. A. (2025) · Journal of Robotics and Control (JRC) · doi:10.18196/jrc.v6i6.28114

Low-latency, High-reliability Service Deployment and Dynamic Migration Strategies in Cloud-edge-device Collaborative Scenarios

Li, C. (2026) · International Conference on Advanced Electronic Materials, Computers and Software Engineering (AEMCSE) · doi:10.1109/aetcse69203.2026.11504383

Advanced Robotics Application in Industry 5.0 Manufacturing Processes

Shadija, V., Sharma, V., & Shukla, R. K. (2026) · Springer eBooks · doi:10.1007/978-3-031-91500-0_38

Federated multi-label feature selection via hybrid breeding optimization algorithm with manifold regularization and sparse constraints

Zhang, S., Ye, Z., Cai, T., Shen, J., Zhou, W., He, Q., Zhang, J., & Lei, M. (2026) · Neurocomputing · doi:10.1016/j.neucom.2026.134018

ASTFNet: An Adaptive Spatio-Temporal Fault Prediction Framework for Dynamic Edge Networks

Li, T., Chen, L., Wen, J., Liu, Y., Chen, H., & Yang, K. (2026) · IEEE Transactions on Network and Service Management · doi:10.1109/tnsm.2026.3698582

Integration and Application of 5G Ultra-Reliable and Low-Latency Communications in Networked Control Systems for Intelligent Factories

Zieliński, J. G., & Dąbrowski, D. P. (2026) · Journal of Applied Automation Technologies · doi:10.64972/jaat.2026v4.112

Real-Time Edge Computing Framework for IIoT-Driven Industrial Automation

Gnat, G., & Fąfara, U. (2025) · Journal of Applied Automation Technologies · doi:10.64972/jaat.2025v3.217p29e:392-404

Adaptive Model Pruning and Knowledge Codistillation for Heterogeneous Federated LearningPreprint

Zeng, Z., Zhang, X., Fan, L., Liu, Y., Zoha, A., & Imran, M. A. (2026) · SSRN Electronic Journal · doi:10.2139/ssrn.6900310

Temporal Irregularity-Aware Attention Mechanism for Industry 5.0 Intrusion Detection

Javeed, D., Adil, M., Kumar, P., & Liu, H. (2026) · IEEE Internet of Things Journal · doi:10.1109/jiot.2026.3701385

Federated learning at a glance

Mukherjee, A., Das, S. K., & Buyya, R. (2026) · Elsevier eBooks · doi:10.1016/b978-0-44-344433-3.00006-x

Physical Layer Authentication for Wireless Powered Fog Computing Networks

Ma, X., Tan, H., & Xie, N. (2026) · IEEE Wireless Communications and Networking Conference Workshops (WCNCW) · doi:10.1109/wcncw67598.2026.11555315

Teaching the Machine, Narrating the Self: Teachers’ Lived Experiences in Implementing IoT-Based Transformative Learning

Siregar, A. A., Panggabean, T. E., Simanungkalit, E., & Siregar, M. H. R. (2026) · International Journal of Educational Narratives · doi:10.70177/ijen.v4i2.3648

Smart Computing Integration Networks: Architecture, Intelligence, Security, and Applications

Zhang, W., Zhang, C., Yang, D. H., Gao, D., & Zhang, H. (2026) · IEEE Transactions on Network Science and Engineering · doi:10.1109/tnse.2026.3706091

Graph Neural Networks Framework for Cybersecurity Threat Analysis in Edge Networks

Kulkarni, R., Krishnamurthy, R., Nayagi, D. S., Sundar, J., Ahire, K. P., & Balakrishnan, A. (2026) · International Conference on Inventive Research in Computing Applications (ICIRCA) · doi:10.1109/icirca69024.2026.11570611

Reliability modeling and analysis for Edge Intelligence-enabled Manufacturing Internet of Things

Fu, X., & Wang, Y. L. (2026) · Computers & Industrial Engineering · doi:10.1016/j.cie.2026.112222

CVASC: Cooperative value-aware service caching for collaborative edge networks

Ma, Y., ZHAO, Y., Hu, Y., & Zhang, X. (2026) · Physical Communication · doi:10.1016/j.phycom.2026.103242

Overselling-Aware Task Scheduling in MEC With Deep Reinforcement Learning

Long, S., Qian, J., Wang, J., Choi, Y., & Li, Z. (2026) · IEEE Transactions on Mobile Computing · doi:10.1109/tmc.2026.3709049

JCCO: Joint Communication and Computation Co-Design in MU-MIMO Edge Computing

Li, J., Shi, Y., Wang, X., Shen, W., & Zio, E. (2026) · IEEE Transactions on Mobile Computing · doi:10.1109/tmc.2026.3709165

An Intelligent Cloud Platform for Automotive Spare Parts Price Transparency

Pednekar, M., Gawade, P., Bulbule, R., Patil, M. S., Kurekar, S., & Kendre, S. A. (2026) · International Conference on Computing, Communication and Green Engineering (CCGE) · doi:10.1109/ccge67142.2026.11581663

Using AioT on the Edge as a Prototype for an Autonomous Sensing Node in an Orchard Field

Naeem, M., Elattar, H. M., & Aboul-Dahab, M. A. (2026) · ICEENG International Conference for Innovations in Intelligent Computing and Cybersecurity (IICC) · doi:10.1109/iicc69623.2026.11581972

Lightweight Dynamic Global Filter Network for Efficient Image Analysis on Edge Devices

He, S., Zhang, Z., Li, S., & Liu, J. (2026) · IEEE International Conference on Sensing, Communication, and Networking (SECON) · doi:10.1109/secon68281.2026.11579156

Decoding the future of edge computing in smart manufacturing: an industry 5.0 perspective

Nain, G., Pattanaik, K. K., Gauttam, H., & Mendes, P. (2026) · The International Journal of Advanced Manufacturing Technology · doi:10.1007/s00170-026-18577-6

UtiliNet: A Utility-Centric Framework for Modeling Network Resilience

Li, J., Tang, Z., & Shi, Y. (2026) · International Conference on Computer Supported Cooperative Work in Design (CSCWD) · doi:10.1109/cscwd68734.2026.11581743

A Pilot-Real-Calibrated Indoor Robotic IoT Benchmark Dataset for Edge-Assisted Mobile Robot Navigation and Anomaly Detection

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