Fog computing: A taxonomy, systematic review, current trends and research challenges

Fog computing and its role in the internet of things

Bonomi, F., Milito, R., Zhu, J., & Addepalli, S. (2012) · Proceedings of the first edition of the MCC workshop on Mobile cloud computing · doi:10.1145/2342509.2342513 · Cited by 6,244

Untitled work

(2004) · Cited by 5,198

CloudSim: a toolkit for modeling and simulation of cloud computing environments and evaluation of resource provisioning algorithms

Calheiros, R. N., Ranjan, R. K., Beloglazov, A., Rose, C. A. F. D., & Buyya, R. (2010) · Software Practice and Experience · doi:10.1002/spe.995 · Cited by 4,961

Guidance on Conducting a Systematic Literature Review

Xiao, Y., & Watson, M. (2019) · Journal of Planning Education and Research · doi:10.1177/0739456x17723971 · Cited by 3,467

Lessons from Applying the Systematic Literature Review Process within the Software Engineering Domain

Brereton, P., Kitchenham, B. A., Budgen, D., Turner, M., & Khalil, M. (2007) · Journal of Systems and Software · doi:10.1016/j.jss.2006.07.009 · Cited by 2,394

Fog and IoT: An Overview of Research Opportunities

Chiang, M., & Zhang, T. (2016) · IEEE Internet of Things Journal · doi:10.1109/jiot.2016.2584538 · Cited by 2,362

iFogSim: A toolkit for modeling and simulation of resource management techniques in the internet of things, edge and fog computing environments

Gupta, H., Vahid Dastjerdi, A., Ghosh, S. K., & Buyya, R. (2017) · Software: Practice and Experience · doi:10.1002/spe.2509 · Cited by 1,649

All one needs to know about fog computing and related edge computing paradigms: A complete survey

Yousefpour, A., Fung, C., Nguyen, T., Kadiyala, K., Jalali, F., Niakanlahiji, A., Kong, J., & Jue, J. P. (2019) · Journal of Systems Architecture · doi:10.1016/j.sysarc.2019.02.009 · Cited by 1,368

A Comprehensive Survey on Fog Computing: State-of-the-Art and Research Challenges

Mouradian, C., Naboulsi, D., Yangui, S., Glitho, R. H., Morrow, M. J., & Polakos, P. A. (2018) · IEEE Communications Surveys & Tutorials · doi:10.1109/comst.2017.2771153 · Cited by 1,022

Vehicular Fog Computing: A Viewpoint of Vehicles as the Infrastructures

Hou, X., Li, Y., Chen, M., Wu, D., Jin, D., & Chen, S. (2016) · IEEE Transactions on Vehicular Technology · doi:10.1109/tvt.2016.2532863 · Cited by 943

AI for next generation computing: Emerging trends and future directions

Gill, S. S., Xu, M., Ottaviani, C., Patros, P., Rami Bahsoon, A., Shaghaghi, A., Golec, M., Stankovski, V., Wu, H., Abraham, A., et al. (2022) · Internet of Things · doi:10.1016/j.iot.2022.100514 · Cited by 775

Edge AI: A survey

Singh, R., & Gill, S. S. (2023) · Internet of Things and Cyber-Physical Systems · doi:10.1016/j.iotcps.2023.02.004 · Cited by 572

Structural health monitoring of civil engineering structures by using the internet of things: A review

Mishra, M., Lourenço, P. B., & Ramana, G. V. (2022) · Journal of Building Engineering · doi:10.1016/j.jobe.2021.103954 · Cited by 484

AI-based fog and edge computing: A systematic review, taxonomy and future directions

Iftikhar, S., Gill, S. S., Song, C., Xu, M., Aslanpour, M. S., Toosi, A. N., Du, J., Wu, H., Ghosh, S., Chowdhury, D., et al. (2022) · Internet of Things · doi:10.1016/j.iot.2022.100674 · Cited by 297

A review on fog computing: Issues, characteristics, challenges, and potential applications

Daş, R., & Inuwa, M. M. (2023) · Telematics and Informatics Reports · doi:10.1016/j.teler.2023.100049 · Cited by 214

Deep learning models for cloud, edge, fog, and IoT computing paradigms: Survey, recent advances, and future directions

Ahmad, S., Shakeel, I., Mehfuz, S., & Ahmad, J. (2023) · Computer Science Review · doi:10.1016/j.cosrev.2023.100568 · Cited by 197

Modern computing: Vision and challenges

Gill, S. S., Wu, H., Patros, P., Ottaviani, C., Arora, P., Pujol, V. C., Haunschild, D., Parlikad, A. K., Cetinkaya, O., Lutfiyya, H., et al. (2024) · Telematics and Informatics Reports · doi:10.1016/j.teler.2024.100116 · Cited by 197

Recent Advances in Evolving Computing Paradigms: Cloud, Edge, and Fog Technologies

Nancy, A. A., Ravindran, D., Vincent, P. M. D. R., Srinivasan, K., & Hu, Y. (2021) · Sensors · doi:10.3390/s22010196 · Cited by 177

Village 4.0: Digitalization of village with smart internet of things technologies

Malik, P. K., Singh, R., Gehlot, A., Akram, S. V., & Das, P. K. (2022) · Computers & Industrial Engineering · doi:10.1016/j.cie.2022.107938 · Cited by 182

Hunterplus: ai based energy-efficient task scheduling for cloud–fog computing environments

Iftikhar, S., Ahmad, M. M. M., Tuli, S., Chowdhury, D., Xu, M., Gill, S. S., & Uhlig, S. (2023) · Internet of Things · doi:10.1016/j.iot.2022.100667 · Cited by 153

A Survey on Intrusion Detection Systems for Fog and Cloud Computing

Chang, V. I. C., Golightly, L., Modesti, P., Xu, Q. A., Doan, L. M. T., Hall, K., Boddu, S., & Kobusińska, A. (2022) · Future Internet · doi:10.3390/fi14030089 · Cited by 128

AI augmented Edge and Fog computing: Trends and challenges

Tuli, S., Mirhakimi, F., Pallewatta, S., Zawad, S., Casale, G., Javadi, B., Yan, F., Buyya, R., & Jennings, N. R. (2023) · Journal of Network and Computer Applications · doi:10.1016/j.jnca.2023.103648 · Cited by 147

Scheduling IoT Applications in Edge and Fog Computing Environments: A Taxonomy and Future Directions

Goudarzi, M., Palaniswami, M. S., & Buyya, R. (2022) · ACM Computing Surveys · doi:10.1145/3544836 · Cited by 122

Task offloading in fog computing: A survey of algorithms and optimization techniques

Kumari, N., Yadav, A., & Jana, P. K. (2022) · Computer Networks · doi:10.1016/j.comnet.2022.109137 · Cited by 110

Artificial Intelligence Techniques for Securing Fog Computing Environments: Trends, Challenges, and Future Directions

Alsadie, D. (2024) · IEEE Access · doi:10.1109/access.2024.3463791 · Cited by 107

Offloading Mechanisms Based on Reinforcement Learning and Deep Learning Algorithms in the Fog Computing Environment

Abdulazeez, D. H., & Askar, S. K. (2023) · IEEE Access · doi:10.1109/access.2023.3241881 · Cited by 112

A systematic survey of attack detection and prevention in Connected and Autonomous Vehicles

Limbasiya, T., Teng, K. Z., Chattopadhyay, S., & Zhou, J. (2022) · Vehicular Communications · doi:10.1016/j.vehcom.2022.100515 · Cited by 76

Optimizing task offloading with metaheuristic algorithms across cloud, fog, and edge computing networks: A comprehensive survey and state-of-the-art schemes

Rahmani, A. M., Haider, A., Khoshvaght, P., Gharehchopogh, F. S., Moghaddasi, K., Rajabi, S., & Hosseinzadeh, M. (2025) · Sustainable Computing Informatics and Systems · doi:10.1016/j.suscom.2024.101080 · Cited by 50

An Edge Computing-Based Preventive Framework With Machine Learning- Integration for Anomaly Detection and Risk Management in Maritime Wireless Communications

Algarni, A., Acarer, T., & Ahmad, Z. (2024) · IEEE Access · doi:10.1109/access.2024.3387529 · Cited by 49

Enabling Technologies for Next-Generation Smart Cities: A Comprehensive Review and Research Directions

Ali, S. A., Elsaid, S. A., Ateya, A. A., ELAffendi, M. A., & El‐Latif, A. A. A. (2023) · Future Internet · doi:10.3390/fi15120398 · Cited by 58

Challenges and Opportunities in Fog Computing Scheduling: A Literature Review

Chuan, W. C., Laghari, S. U. A., Manickam, S., Ashraf, E., & Karuppayah, S. (2025) · IEEE Access · doi:10.1109/access.2024.3525261 · Cited by 41

Remote Monitoring and Maintenance for Equipment and Production Lines on Industrial Internet: A Literature Review

Li, Q., Yang, Y., & Jiang, P. (2022) · Machines · doi:10.3390/machines11010012 · Cited by 48

Energy-Efficient and Secure Load Balancing Technique for SDN-Enabled Fog Computing

Singh, J., Singh, P., Amhoud, E. M., & Hedabou, M. (2022) · Sustainability · doi:10.3390/su141912951 · Cited by 40

Machine learning-based computation offloading in edge and fog: a systematic review

Taheri-abed, S., Moghadam, A. M. E., & Rezvani, M. H. (2023) · Cluster Computing · doi:10.1007/s10586-023-04100-z · Cited by 36

Fog Intelligence for Secure Smart Villages: Architecture and Future Challenges

Aljuhani, A., Kumar, P., Kumar, R., Jolfaei, A., & Islam, A. K. M. N. (2022) · IEEE Consumer Electronics Magazine · doi:10.1109/mce.2022.3193268 · Cited by 36

Reinforcement learning based task offloading of IoT applications in fog computing: algorithms and optimization techniques

Allaoui, T., Gasmi, K., & Ezzedine, T. (2024) · Cluster Computing · doi:10.1007/s10586-024-04518-z · Cited by 34

Optimal placement of applications in the fog environment: A systematic literature review

Islam, M. M., Ramezani, F., Lu, H., & Naderpour, M. (2022) · Journal of Parallel and Distributed Computing · doi:10.1016/j.jpdc.2022.12.001 · Cited by 31

Integrating Wireless Remote Sensing and Sensors for Monitoring Pesticide Pollution in Surface and Groundwater

Mutunga, T., Sinanović, S., & Harrison, C. S. (2024) · Sensors · doi:10.3390/s24103191 · Cited by 29

Geometric-thermal error control system for gear profile grinding machine

Liu, J., Ma, C., Gui, H., & Li, M. (2022) · Advanced Engineering Informatics · doi:10.1016/j.aei.2022.101618 · Cited by 28

Seagull optimization algorithm based multi-objective vm placement in edge-cloud data centers

Nabavi, S., Wen, L., Gill, S. S., & Xu, M. (2023) · Internet of Things and Cyber-Physical Systems · doi:10.1016/j.iotcps.2023.01.002 · Cited by 26

Ultra-Reliable Low-Latency Communications: Unmanned Aerial Vehicles Assisted Systems

Osama, M., Ateya, A. A., Elsaid, S. A., & Muthanna, A. (2022) · Information · doi:10.3390/info13090430 · Cited by 25

Def-DReL: Towards a sustainable serverless functions deployment strategy for fog-cloud environments using deep reinforcement learning

Dehury, C. K., Poojara, S. R., & Srirama, S. N. (2023) · Applied Soft Computing · doi:10.1016/j.asoc.2023.111179 · Cited by 24

Resource allocation in Fog–Cloud Environments: State of the art

Zolghadri, M., Asghari, P., Dashti, S. E., & Hedayati, A. (2024) · Journal of Network and Computer Applications · doi:10.1016/j.jnca.2024.103891 · Cited by 24

High-availability clusters: A taxonomy, survey, and future directions

Somasekaram, P., Călinescu, R., & Buyya, R. (2021) · Journal of Systems and Software · doi:10.1016/j.jss.2021.111208 · Cited by 22

Fog node discovery and selection: A Systematic literature review

Bukhari, A. A., Hussain, F. K., & Hussain, F. K. (2022) · Future Generation Computer Systems · doi:10.1016/j.future.2022.04.034 · Cited by 22

A systematic review of the soft computing methods shaping the future of the metaverse

Madjid Tavana, D., & Sorooshian, S. (2023) · Applied Soft Computing · doi:10.1016/j.asoc.2023.111098 · Cited by 24

Digital forensics challenges and readiness for 6G Internet of Things (IoT) networks

Akinbi, A. (2023) · Wiley Interdisciplinary Reviews Forensic Science · doi:10.1002/wfs2.1496 · Cited by 23

Simulation Tools for Fog Computing: A Comparative Analysis

Fahimullah, M., Philippe, G., Ahvar, S., & Trocan, M. (2023) · Sensors · doi:10.3390/s23073492 · Cited by 20

A cost-aware IoT application deployment approach in fog computing

Faraji‐Mehmandar, M., Ghobaei‐Arani, M., & Shakarami, A. (2025) · Cluster Computing · doi:10.1007/s10586-024-04873-x · Cited by 19

Reinforcement Learning-Based Optimization Framework for Application Component Migration in NFV Cloud-Fog Environments

Afrasiabi, S. N., Ebrahimzadeh, A., Mouradian, C., Malektaji, S., & Glitho, R. (2022) · IEEE Transactions on Network and Service Management · doi:10.1109/tnsm.2022.3217723 · Cited by 19

Security and Privacy of Wearable Wireless Sensors in Healthcare: A Systematic Review

Kaur, R., Shahrestani, S. A., & Ruan, C. (2024) · Computer Networks and Communications · doi:10.37256/cnc.2120243852 · Cited by 16

Multi-objective fog node placement strategy based on heuristic algorithms for smart factories

Xu, F., Yin, Z., Han, G., Li, Y., Zhang, F., & Bi, Y. (2023) · Wireless Networks · doi:10.1007/s11276-023-03262-3 · Cited by 14

Fog Computing Resource-Scheduling Strategy in IoT Based on Artificial Bee Colony Algorithm

Liu, W., Li, C., Zheng, A., Zheng, Z., Zhang, Z., & Xiao, Y. (2023) · Electronics · doi:10.3390/electronics12071511 · Cited by 14

The importance of nature‐inspired metaheuristic algorithms in the data routing and path finding problem in the internet of things

Dong‐liang, L., Lu, B., & Hai‐hua, W. (2023) · International Journal of Communication Systems · doi:10.1002/dac.5450 · Cited by 13

Enabling DevOps for Fog Applications in the Smart Manufacturing domain: A Model-Driven based Platform Engineering approach

Cuadra, J., Hurtado, E., Sarachaga, I., Estévez, E., Casquero, O., & Armentia, A. (2024) · Future Generation Computer Systems · doi:10.1016/j.future.2024.03.053 · Cited by 12

A Survey on Load Balancing Techniques in Fog Computing

Singh, J., Warraich, J., & Singh, P. (2021) · International Conference on Computing Sciences (ICCS) · doi:10.1109/iccs54944.2021.00018 · Cited by 12

Prototype of an Emergency Response System Using IoT in a Fog Computing Environment

Ortiz-Garcés, I., Andrade, R., Sánchez-Viteri, S., & Villegas-Ch, W. E. (2023) · Computers · doi:10.3390/computers12040081 · Cited by 12

DEEDSP: Deadline‐aware and energy‐efficient dynamic service placement in integrated Internet of Things and fog computing environments

Sri Raghavendra, M., Chawla, P., & Singh Gill, S. (2021) · Transactions on Emerging Telecommunications Technologies · doi:10.1002/ett.4368 · Cited by 18

Intelligent Fog-IoT Networks with 6G Endorsement: Foundations, Applications, Trends and Challenges

Ansar, S. A., Samriya, J. K., Kumar, M., Gill, S. S., & Khan, R. A. (2023) · Springer eBooks · doi:10.1007/978-3-031-30101-8_12 · Cited by 11

A Scalable Fog Computing Solution for Industrial Predictive Maintenance and Customization

D’Agostino, P., Violante, M., & Macario, G. (2024) · Electronics · doi:10.3390/electronics14010024 · Cited by 11

A Comprehensive Analysis of Computing Paradigms Leading to Fog Computing: Simulation Tools, Applications, and Use Cases

Patel, S. H., & Patel, R. P. (2023) · Journal of Computer Information Systems · doi:10.1080/08874417.2022.2121782 · Cited by 10

A Survey of Edge Computing Resource Allocation and Task Scheduling Optimization

Xu, X., Ding, H., Wang, J., & Hua, L. (2024) · Communications in computer and information science · doi:10.1007/978-981-97-4390-2_11 · Cited by 10

Fog Computing in Healthcare: Systematic Review

Navakauskas, D., & Kazlauskas, M. (2023) · Informatica · doi:10.15388/23-infor525 · Cited by 9

Fuzzy-Centric Fog–Cloud Inspired Deep Interval Bi-LSTM Healthcare Framework for Predicting Yellow Fever Outbreak

Verma, P., Shaikh, T. A., Sood, S. K., Kaur, H., Kumar, M., Wu, H., & Gill, S. S. (2024) · IEEE Transactions on Fuzzy Systems · doi:10.1109/tfuzz.2024.3412197 · Cited by 9

Soft computing approaches for dynamic multi-objective evaluation of computational offloading: a literature review

Khan, S., Zheng, J., & Ali, H. (2024) · Cluster Computing · doi:10.1007/s10586-024-04543-y · Cited by 9

Vehicular Fog Computing: A Survey of Architectures, Resource Management, Challenges and Emerging Trends

Husain, M. H., Ahmadi, M., & Mardukhi, F. (2024) · Wireless Personal Communications · doi:10.1007/s11277-024-11373-z · Cited by 9

Smart Lighting Systems: State-of-the-Art in the Adoption of the EdgeML Computing Paradigm

Paolone, G., Paesani, R., Pilotti, F., Camplone, J., Piazza, A., & Felice, P. D. (2025) · Future Internet · doi:10.3390/fi17020090 · Cited by 11

Energy Coherent Fog Networks Using Multi-Sink Wireless Sensor Networks

Ramadan, R. Α., Sharif, M. H., Alreshidi, E. J., Sharif, M. H. U., İnce, İ. F., Kamberaj, H., & Khedr, A. Y. (2021) · IEEE Access · doi:10.1109/access.2021.3135311 · Cited by 9

Adaptively secure multi-authority attribute-based broadcast encryption in fog computing

Chen, J., Niu, J., Hao, L., Li, L., & Ling, Y. (2023) · Computer Networks · doi:10.1016/j.comnet.2023.109844 · Cited by 9

Toward a unified computing paradigm: a survey and roadmap for data management in integrated IoT, fog, and cloud services

Hemmati, A., Khaledian, N., & Rahmani, A. M. (2026) · Peer-to-Peer Networking and Applications · doi:10.1007/s12083-025-02183-6 · Cited by 9

Introduction to different computing paradigms: cloud computing, fog computing, and edge computing

Shinde, S. V., Hemanth, D. J., & Elhoseny, M. (2023) · Elsevier eBooks · doi:10.1016/b978-0-323-99412-5.00005-8 · Cited by 9

ESMA: Towards elevating system happiness in a decentralized serverless edge computing framework

Datta, S., Addya, S. K., & Ghosh, S. K. (2023) · Journal of Parallel and Distributed Computing · doi:10.1016/j.jpdc.2023.104762 · Cited by 8

An Advanced IoT-Based Architecture for Healthcare Systems: A Focus on Blockchain-based Edge Computing for Diabetes Management

Tlemçani, K., Andaloussi, S. J., Azbeg, K., Ouchetto, O., & Fetjah, L. (2023) · International Conference on Networking, Information Systems & Security (NISS) · doi:10.1145/3607720.3607756 · Cited by 7

Dynamic task offloading for IoT-Fog-Cloud systems: a network traffic-aware decision tree approach

Zolghadri, M., Asghari, P., Dashti, S. E., & Hedayati, A. (2025) · Computing · doi:10.1007/s00607-025-01449-4 · Cited by 7

Simulating fog computing in OMNeT++

Al-Rubaie, N. R. O., Kamel, R. N. N., & Alshemari, R. M. (2022) · Bulletin of Electrical Engineering and Informatics · doi:10.11591/eei.v12i2.4201 · Cited by 7

Unboxing fog security: a review of fog security and authentication mechanisms

Kaliya, N., & Pawar, D. (2023) · Computing · doi:10.1007/s00607-023-01208-3 · Cited by 7

Pareto-Optimised Fog Storage Services with Novel Service-Level Agreement Specification

Kochovski, P., Paščinski, U., Stankovski, V., & Ciglarič, M. (2022) · Applied Sciences · doi:10.3390/app12073308 · Cited by 7

A Survey on Fog Computing in IoT

Rasheed, M. A., Saleem, J., Murtaza, H., Tanweer, H. A., Rasheed, M. A., & Ahmed, M. (2021) · VFAST Transactions on Software Engineering · doi:10.21015/vtse.v9i4.727 · Cited by 7

Resource Provisioning in Fog Computing - A Survey

Vetriveeran, D., & Leena Sri, R. (2025) · ACM Computing Surveys · doi:10.1145/3744662 · Cited by 6

FORK: A Kubernetes-Compatible Federated Orchestrator of Fog-Native Applications Over Multi-Domain Edge-to-Cloud Ecosystems

Ejaz, S., & Al-Naday, M. (2024) · Conference on Innovation in Clouds, Internet and Networks and Workshops (ICIN) · doi:10.1109/icin60470.2024.10494435 · Cited by 6

Efficient Geospatial Data Analysis Framework in Fog Environment

Saber, W. E., Eisa, R., & Attia, R. M. (2022) · IEEE Access · doi:10.1109/access.2022.3231787 · Cited by 6

FogLBS: Utilizing fog computing for providing mobile Location-Based Services to mobile customers

Orabi, M., Aghbari, Z. A., & Kamel, I. (2023) · Pervasive and Mobile Computing · doi:10.1016/j.pmcj.2023.101832 · Cited by 6

A Dynamic IIoT Framework Based on the Publish–Subscribe Paradigm

Ungurean, I., & Găitan, N. C. (2023) · Sensors · doi:10.3390/s23249829 · Cited by 6

Modeling of a Generic Edge Computing Application Design

Roig, P. J., Alcaraz, S., Gilly, K., Bernad, C., & Juiz, C. (2021) · Sensors · doi:10.3390/s21217276 · Cited by 6

Allocation and migration of microservices in SDN-based vehicular fog networks

Alvarenga, L. D. C., Sousa, P., & Costa, A. (2022) · Iberian Conference on Information Systems and Technologies (CISTI) · doi:10.23919/cisti54924.2022.9820608 · Cited by 6

Scheduling Latency-Sensitive Tasks in the Cloud Continuum with Hierarchical Reinforcement Learning

Monaco, D., Sacco, A., Casetti, C., & Marchetto, G. (2025) · IEEE/IFIP Network Operations and Management Symposium (NOMS) · doi:10.1109/noms57970.2025.11073729 · Cited by 6

A Comprehensive Survey on Fog Computing: Architectures, Techniques, Challenges, and Future Directions

Chaturvedi, P., Ahmad, S., & Mewada, A. (2026) · Archives of Computational Methods in Engineering · doi:10.1007/s11831-026-10579-7 · Cited by 6

Simulating Fog of Medical Things: Research Challenges and Opportunities

Pati, A., Panigrahi, A., Parhi, M., Pattanayak, B. K., Sahu, B., & Kant, S. (2024) · IEEE Access · doi:10.1109/access.2024.3468015 · Cited by 5

Arithmetic Framework to Optimize Packet Forwarding among End Devices in Generic Edge Computing Environments

Roig, P. J., Alcaraz, S., Gilly, K., Bernad, C., & Juiz, C. (2022) · Sensors · doi:10.3390/s22020421 · Cited by 5

A Data-driven method for adaptive resource requirement allocation via probabilistic solar load and market forecasting utilizing digital twin

Yao, C., Wang, J., Sun, H., Chu, H., Jin, T., & Xiang, Q. (2023) · Solar Energy · doi:10.1016/j.solener.2023.01.005 · Cited by 4

Integration of blockchain, IoT, fog computing, and semantic technologies

Sathio, A. A., Rind, M. M., Awan, S. A., Junejo, A. R., & Ali, S. (2025) · Elsevier eBooks · doi:10.1016/b978-0-443-30076-9.00005-4 · Cited by 4

An Edge-Fog Architecture for Distributed 3D Reconstruction and Remote Monitoring of a Power Plant Site in the Context of 5G

Vidal, V. F., Honório, L. D. M., Pinto, M. F., Dantas, M. A. R., Aguiar, M., & Capretz, M. A. M. (2022) · Sensors · doi:10.3390/s22124494 · Cited by 4

Intent-based Decentralized Orchestration for Green Energy-aware Provisioning of Fog-native Workflows

Al-Naday, M., Goethals, T., & Volckaert, B. (2022) · International Conference on Network and Service Management (CNSM) · doi:10.23919/cnsm55787.2022.9964993 · Cited by 4

CMFog V : Proactive content migration for multi-level fog computing

Araújo, M. C., & Bittencourt, L. F. (2024) · Pervasive and Mobile Computing · doi:10.1016/j.pmcj.2024.101933 · Cited by 4

Resource Allocation and Scheduling of Linear Workflow Applications with Ageing Priorities and Transient Failures

Stavrinides, G. L., & Karatza, H. D. (2022) · IEEE/ACS International Conference on Computer Systems and Applications (AICCSA) · doi:10.1109/aiccsa56895.2022.10017928 · Cited by 4

Enhancing Cloud Security and Efficiency Through AI-Driven Intrusion Detection and Machine Learning-Based Resource Management

Ch, R., Nimmala, S., Batra, I., Malik, A., & Malik, P. K. (2025) · Advances in information security, privacy, and ethics book series · doi:10.4018/979-8-3373-0563-9.ch015 · Cited by 3

An Optimal Approach for Testing Control in The Distributed Cloud

Moutai, F. Z., Tajioue, M. A., Azzouzi, S., & Charaf, M. E. H. (2022) · International Conference on Control, Decision and Information Technologies (CoDIT) · doi:10.1109/codit55151.2022.9804043 · Cited by 3

A Review on Fog Computing: Research Challenges and Future Directions

Khaleel, T. A., Alani, O. A. N., & Al-Abdulqader, O. (2023) · Maǧallaẗ al-handasaẗ al-rāfidayn · doi:10.33899/rengj.2022.136642.1211 · Cited by 3

Privacy and security issues in fog-to-fog communication: A survey

Murkomen, T. (2023) · World Journal of Advanced Research and Reviews · doi:10.30574/wjarr.2023.20.3.2487 · Cited by 3

Fog Computing in Healthcare

Datta, S., & Datta, P. (2024) · doi:10.1002/9781394175345.ch8 · Cited by 3

Robust Security Framework for IoT-Enabled Smart Cities: Leveraging Ensemble Machine Learning Techniques in Fog Computing EnvironmentsPreprint

Kumari, R., & Kaur, K. (2024) · Research Square · doi:10.21203/rs.3.rs-5197026/v1 · Cited by 3

Video streaming on fog and edge computing layers: A systematic mapping study

de Moraes, A. L. S., de Macedo, D. D. J., & Pioli, L. (2024) · Internet of Things · doi:10.1016/j.iot.2024.101359 · Cited by 4

Quality of experience-aware application deployment in fog computing environments using machine learning

Jenifer, P., & Sujana, J. A. J. (2025) · PeerJ Computer Science · doi:10.7717/peerj-cs.3143 · Cited by 2

A Survey on Edge/Fog Caching Based on Deep Learning Algorithms

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