Potentials, trends, and prospects in edge technologies: Fog, cloudlet, mobile edge, and micro data centers

Edge computing: Vision and challenges

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Fog computing and its role in the internet of things

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The case for vm-based cloudlets in mobile computing

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The Constrained Application Protocol (CoAP)

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

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Energy-Efficient Resource Allocation for Mobile-Edge Computation Offloading

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A Survey of Fog Computing

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Mobile edge computing, Fog et al.: A survey and analysis of security threats and challenges

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Fog Computing: A Platform for Internet of Things and Analytics

Bonomi, F., Milito, R., Natarajan, P., & Zhu, J. (2014) · Studies in Computational Intelligence · doi:10.1007/978-3-319-05029-4_7 · Cited by 1,222

Fog Computing: Helping the Internet of Things Realize Its Potential

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Convergence of Edge Computing and Deep Learning: A Comprehensive Survey

Wang, X., Han, Y., Leung, V. C. M., Niyato, D., Yan, X., & Chen, X. (2020) · IEEE Communications Surveys & Tutorials · doi:10.1109/comst.2020.2970550 · Cited by 1,498

Enabling technologies for fog computing in healthcare IoT systems

Mutlag, A. A., Abd Ghani, M. K., Arunkumar, N., Mohammed, M. A., & Mohd, O. (2019) · Future Generation Computer Systems · doi:10.1016/j.future.2018.07.049 · Cited by 590

Edge-Computing-Enabled Smart Cities: A Comprehensive Survey

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Federated Learning in Edge Computing: A Systematic Survey

Abreha, H. G., Hayajneh, M., & Serhani, M. A. (2022) · Sensors · doi:10.3390/s22020450 · Cited by 384

An Overview of Service Placement Problem in Fog and Edge Computing

Aït-Salaht, F., Desprez, F., & Lèbre, A. (2020) · ACM Computing Surveys · doi:10.1145/3391196 · Cited by 356

Edge Computing for Internet of Everything: A Survey

Kong, X., Wu, Y., Wang, H., & Xia, F. (2022) · IEEE Internet of Things Journal · doi:10.1109/jiot.2022.3200431 · Cited by 323

Fog/Edge Computing-Based IoT (FECIoT): Architecture, Applications, and Research Issues

Omoniwa, B., Hussain, R., Javed, M. A., Bouk, S. H., & Malik, S. A. (2018) · IEEE Internet of Things Journal · doi:10.1109/jiot.2018.2875544 · Cited by 285

Deep learning for edge computing applications: A State-of-the-Art survey

Wang, F., Zhang, M., Wang, X., Ma, X., & Liu, J. (2020) · IEEE Access · doi:10.1109/access.2020.2982411 · Cited by 259

From A to Z: Wearable technology explained

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Industry 4.0 Implementation Challenges and Opportunities: A Managerial Perspective

Bajić, B., Rikalović, A., Suzić, N., & Piuri, V. (2020) · IEEE Systems Journal · doi:10.1109/jsyst.2020.3023041 · Cited by 244

Water immersion cooling of high power density electronics

Birbarah, P., Gebrael, T., Foulkes, T., Stillwell, A., Moore, A., Pilawa-Podgurski, R. C. N., & Miljkovic, N. (2019) · International Journal of Heat and Mass Transfer · doi:10.1016/j.ijheatmasstransfer.2019.118918 · Cited by 242

The big picture on the internet of things and the smart city: a review of what we know and what we need to know

Rejeb, A., Rejeb, K., Simske, S., Treiblmaier, H., & Zailani, S. H. M. (2022) · Internet of Things · doi:10.1016/j.iot.2022.100565 · Cited by 237

A review of edge computing reference architectures and a new global edge proposal

Sittón-Candanedo, I., Alonso, R. S., Corchado, J. M., Rodrı́guez, S., & Vara, R. C. (2019) · Future Generation Computer Systems · doi:10.1016/j.future.2019.04.016 · Cited by 225

Edge computing: current trends, research challenges and future directions

Carvalho, G., Cabral, B., Pereira, V., & Bernardino, J. (2021) · Computing · doi:10.1007/s00607-020-00896-5 · Cited by 223

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

Pervasive AI for IoT Applications: A Survey on Resource-Efficient Distributed Artificial Intelligence

Baccour, E., Mhaisen, N., Abdellatif, A. A., Erbad, A., Mohamed, A. M. S., Hamdi, M., & Guizani, M. (2022) · IEEE Communications Surveys & Tutorials · doi:10.1109/comst.2022.3200740 · Cited by 223

Challenges and recommended technologies for the industrial internet of things: A comprehensive review

Younan, M., Houssein, E. H., Elhoseny, M., & Ali, A. A. (2019) · Measurement · doi:10.1016/j.measurement.2019.107198 · Cited by 214

Towards the Decentralised Cloud

Ferrer, A. J., Marquès, J. M., & Jorba, J. (2019) · ACM Computing Surveys · doi:10.1145/3243929 · Cited by 199

Architectural Design Alternatives Based on Cloud/Edge/Fog Computing for Connected Vehicles

Wang, H., Liu, T., Kim, B., Lin, C., Shiraishi, S., Xie, J. L., & Han, Z. (2020) · IEEE Communications Surveys & Tutorials · doi:10.1109/comst.2020.3020854 · Cited by 199

Fog computing for sustainable smart cities in the IoT era: Caching techniques and enabling technologies - an overview

Zahmatkesh, H., & Al-Turjman, F. M. (2020) · Sustainable Cities and Society · doi:10.1016/j.scs.2020.102139 · Cited by 171

Applying machine learning techniques for caching in next-generation edge networks: A comprehensive survey

Shuja, J., Bilal, K., Alasmary, W., Sinky, H., & Alanazi, E. (2021) · Journal of Network and Computer Applications · doi:10.1016/j.jnca.2021.103005 · Cited by 162

Fog Computing Applications in Smart Cities: A Systematic Survey

Javadzadeh, G., & Rahmani, A. M. (2019) · Wireless Networks · doi:10.1007/s11276-019-02208-y · Cited by 138

Smart city big data analytics: An advanced review

Soomro, K., Bhutta, M. N. M., Khan, Z., & Tahir, M. A. (2019) · Wiley Interdisciplinary Reviews Data Mining and Knowledge Discovery · doi:10.1002/widm.1319 · Cited by 136

Heuristic Edge Server Placement in Industrial Internet of Things and Cellular Networks

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A Survey on Mobile Edge Computing for Video Streaming: Opportunities and Challenges

Khan, M. A., Baccour, E., Chkirbene, Z., Erbad, A., Hamila, R., Hamdi, M., & Gabbouj, M. (2022) · IEEE Access · doi:10.1109/access.2022.3220694 · Cited by 126

Quality of service‐aware approaches in fog computing

Kashani, M. H., Rahmani, A. M., & Navimipour, N. J. (2020) · International Journal of Communication Systems · doi:10.1002/dac.4340 · Cited by 119

Edge computing server placement with capacitated location allocation

Lähderanta, T., Leppänen, T., Ruha, L., Lovén, L., Harjula, E., Ylianttila, M., Riekki, J. P., & Sillanpää, M. J. (2021) · Journal of Parallel and Distributed Computing · doi:10.1016/j.jpdc.2021.03.007 · Cited by 116

Adaptive and Priority-Based Resource Allocation for Efficient Resources Utilization in Mobile-Edge Computing

Sharif, Z., Jung, L. T., Razzak, I., & Alazab, M. (2021) · IEEE Internet of Things Journal · doi:10.1109/jiot.2021.3111838 · Cited by 114

Auto-scaling techniques in container-based cloud and edge/fog computing: Taxonomy and survey

Dogani, J., Namvar, R., & Khunjush, F. (2023) · Computer Communications · doi:10.1016/j.comcom.2023.06.010 · Cited by 111

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

Assessing the reliability of fog computing for smart mobility applications in VANETs

Pereira, J. R., Ricardo, L., Luís, M., Senna, C. R., & Sargento, S. (2018) · Future Generation Computer Systems · doi:10.1016/j.future.2018.11.043 · Cited by 104

Industry 4.0 Implementation Challenges and Opportunities: A Technological Perspective

Rikalović, A., Suzić, N., Bajić, B., & Piuri, V. (2021) · IEEE Systems Journal · doi:10.1109/jsyst.2021.3101673 · Cited by 101

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

IoT Implementation of Kalman Filter to Improve Accuracy of Air Quality Monitoring and Prediction

Lai, X., Yang, T., Wang, Z., & Chen, P. (2019) · Applied Sciences · doi:10.3390/app9091831 · Cited by 106

An improved multi-objective genetic algorithm with heuristic initialization for service placement and load distribution in edge computing

Maia, A. M., Ghamri-Doudane, Y. M., Vieira, D., & de Castro, M. F. (2021) · Computer Networks · doi:10.1016/j.comnet.2021.108146 · Cited by 96

TIDCS: A Dynamic Intrusion Detection and Classification System Based Feature Selection

Chkirbene, Z., Erbad, A., Hamila, R., Mohamed, A. M. S., Guizani, M., & Hamdi, M. (2020) · IEEE Access · doi:10.1109/access.2020.2994931 · Cited by 94

Vehicular software-defined networking and fog computing: Integration and design principles

Nobre, J. C., Souza, A. M. D., do Rosário, D. L., Both, C. B., Villas, L. A., Cerqueira, E., Braun, T. I., & Gerla, M. (2018) · Ad Hoc Networks · doi:10.1016/j.adhoc.2018.07.016 · Cited by 89

Systematic Review on Security and Privacy Requirements in Edge Computing: State of the Art and Future Research Opportunities

Yahuza, M., Idris, M. Y. I., Wahab, A. W. A., Ho, A. T. S., Khan, S., Musa, S. N., & Taha, A. Z. (2020) · IEEE Access · doi:10.1109/access.2020.2989456 · Cited by 87

Moving to the Edge-Cloud-of-Things: Recent Advances and Future Research Directions

Bangui, H., Rakrak, S., Raghay, S., & Bühnová, B. (2018) · Electronics · doi:10.3390/electronics7110309 · Cited by 86

Cloudlet Computing: Recent Advances, Taxonomy, and Challenges

Babar, M., Khan, M. S., Ali, F., Imran, M. A., & Shoaib, M. (2021) · IEEE Access · doi:10.1109/access.2021.3059072 · Cited by 82

Towards effective offloading mechanisms in fog computing

Sofla, M. S., Kashani, M. H., Mahdipour, E., & Mirzaee, R. F. (2021) · Multimedia Tools and Applications · doi:10.1007/s11042-021-11423-9 · Cited by 82

On Resilience in Cloud Computing

Welsh, T., & Benkhelifa, E. (2020) · ACM Computing Surveys · doi:10.1145/3388922 · Cited by 75

Prosumer in smart grids based on intelligent edge computing: A review on Artificial Intelligence Scheduling Techniques

Slama, S. B. (2021) · Ain Shams Engineering Journal · doi:10.1016/j.asej.2021.05.018 · Cited by 75

5G Multi-Access Edge Computing: A Survey on Security, Dependability, and Performance

Nencioni, G., Garroppo, R. G., & Olimid, R. F. (2023) · IEEE Access · doi:10.1109/access.2023.3288334 · Cited by 87

Current state and prospects of edge computing within the Internet of Things (IoT) ecosystem

Sodiya, E. O., Umoga, U. J., Obaigbena, A., Jacks, B. S., Ugwuanyi, E. D., Daraojimba, A. I., & Lottu, O. A. (2024) · International Journal of Science and Research Archive · doi:10.30574/ijsra.2024.11.1.0287 · Cited by 72

Privacy-Aware Cloud Auditing for GDPR Compliance Verification in Online Healthcare

Barati, M., Aujla, G. S., Llanos, J. T., Adu-Duodu, K., RANA, O. F., Carr, M., & Ranjan, R. K. (2021) · IEEE Transactions on Industrial Informatics · doi:10.1109/tii.2021.3100152 · Cited by 71

Edge-Oriented Computing: A Survey on Research and Use Cases

Sulieman, N. A., Celsi, L. R., Li, W., Zomaya, A. Y., & Villari, M. (2022) · Energies · doi:10.3390/en15020452 · Cited by 69

Service Migration from Cloud to Multi-tier Fog Nodes for Multimedia Dissemination with QoE Support

do Rosário, D. L., Schimuneck, M., Camargo, J., Nobre, J. C., Both, C. B., Rochol, J., & Gerla, M. (2018) · Sensors · doi:10.3390/s18020329 · Cited by 67

Maximizing the Utilization of Fog Computing in Internet of Vehicle Using SDN

Kadhim, A. J., & Seno, S. A. H. (2018) · IEEE Communications Letters · doi:10.1109/lcomm.2018.2878710 · Cited by 66

Edge MLOps: An Automation Framework for AIoT Applications

Raj, E., Buffoni, D., Westerlund, M., & Ahola, K. (2021) · IEEE International Conference on Cloud Engineering · doi:10.1109/ic2e52221.2021.00034 · Cited by 59

A review on trust management in fog/edge computing: Techniques, trends, and challenges

Nikravan, M., & Kashani, M. H. (2022) · Journal of Network and Computer Applications · doi:10.1016/j.jnca.2022.103402 · Cited by 56

Tracking GDPR Compliance in Cloud-Based Service Delivery

Barati, M., & Rana, O. (2022) · IEEE Transactions on Services Computing · doi:10.1109/tsc.2020.2999559 · Cited by 51

An Adaptive Mechanism for Dynamically Collaborative Computing Power and Task Scheduling in Edge Environment

Xu, Y., Chen, L., Lu, Z., Du, X., Wu, J., & Hung, P. C. K. (2021) · IEEE Internet of Things Journal · doi:10.1109/jiot.2021.3119181 · Cited by 51

Taking Cloud Computing to the Extreme Edge: A Review of Mist Computing for Smart Cities and Industry 4.0 in Africa

Dogo, E. M., Salami, A. F., Aigbavboa, C. O., & Nkonyana, T. (2018) · EAI/Springer Innovations in Communication and Computing · doi:10.1007/978-3-319-99061-3_7 · Cited by 51

Edge Computing Based Applications in Vehicular Environments: Comparative Study and Main Issues

Mendiboure, L., Chalouf, M. A., & Krief, F. (2019) · Journal of Computer Science and Technology · doi:10.1007/s11390-019-1947-3 · Cited by 50

LBRO: Load Balancing for Resource Optimization in Edge Computing

Nayyer, M. Z., Raza, I., Hussain, S. A., Jamal, M. H., Gillani, Z., Hur, S., & Ashraf, I. (2022) · IEEE Access · doi:10.1109/access.2022.3205741 · Cited by 49

Collaborative joint caching and transcoding in mobile edge networks

Bilal, K., Baccour, E., Erbad, A., Mohamed, A. M. S., & Guizani, M. (2019) · Journal of Network and Computer Applications · doi:10.1016/j.jnca.2019.02.004 · Cited by 49

Security challenges in fog-computing environment: a systematic appraisal of current developments

Yakubu, J., Abdulhamid, S. M., Christopher, H. A., Chiroma, H., & Abdullahi, M. (2019) · Journal of Reliable Intelligent Environments · doi:10.1007/s40860-019-00081-2 · Cited by 49

SDN based communications privacy-preserving architecture for VANETs using fog computing

Arif, M., Wang, G., Bălaş, V. E., Geman, O., Castiglione, A., & Chen, J. (2020) · Vehicular Communications · doi:10.1016/j.vehcom.2020.100265 · Cited by 46

Application and Research of IoT Architecture for End-Net-Cloud Edge Computing

Zhang, Y., Yu, H., Zhou, W., & Man, M. (2022) · Electronics · doi:10.3390/electronics12010001 · Cited by 45

Secure Edge Computing Management Based on Independent Microservices Providers for Gateway-Centric IoT Networks

Jin, W., Xu, R., You, T., Hong, Y.-G., & Kim, D. (2020) · IEEE Access · doi:10.1109/access.2020.3030297 · Cited by 45

Cloud-Edge Orchestration for Smart Cities: A Review of Kubernetes-based Orchestration Architectures

Böhm, S., & Wirtz, G. (2022) · EAI Endorsed Transactions on Smart Cities · doi:10.4108/eetsc.v6i18.1197 · Cited by 44

FogJam: A Fog Service for Detecting Traffic Congestion in a Continuous Data Stream VANET

Peixoto, M. L. M., Mota, E., Maia, A., Junior, W. V. L., Salahuddin, M. A., Boutaba, R., & Villas, L. A. (2022) · Ad Hoc Networks · doi:10.1016/j.adhoc.2022.103046 · Cited by 44

The role of 5G network in revolutionizing agriculture for sustainable development: A comprehensive review

Rehman, W. U., Koondhar, M. A., Afridi, S. K., Albasha, L., Smaili, I. H., Touti, E., Aoudia, M., Zahrouni, W., Mahariq, I., & Ahmed, M. M. R. (2025) · Energy Nexus · doi:10.1016/j.nexus.2025.100368 · Cited by 48

Fog and edge computing: concepts, tools and focus areas

Hurbungs, V., Bassoo, V., & Fowdur, T. P. (2021) · International Journal of Information Technology · doi:10.1007/s41870-020-00588-5 · Cited by 44

A Survey on Matching Theory for Distributed Computation Offloading in IoT-Fog-Cloud Systems: Perspectives and Open Issues

Tran‐Dang, H., & Kim, D. (2022) · IEEE Access · doi:10.1109/access.2022.3219427 · Cited by 44

Sharing Health Information Using a Blockchain

Elvas, L. B., Serrão, C., & Ferreira, J. C. (2023) · Healthcare · doi:10.3390/healthcare11020170 · Cited by 43

Optimized Placement of Scalable IoT Services in Edge Computing

Maia, A. M., Ghamri-Doudane, Y. M., Vieira, D., & Franklin de Castro, M. (2019) · HAL · Cited by 43

Optimization of Data and Energy Migrations in Mini Data Centers for Carbon-Neutral Computing

da Silva, M. D. M., Gamatié, A., Sassatelli, G., Poss, M., & Robert, M. (2022) · IEEE Transactions on Sustainable Computing · doi:10.1109/tsusc.2022.3197090 · Cited by 42

A Systematic Review of Energy Efficiency Metrics for Optimizing Cloud Data Center Operations and Management

Safari, A., Sorouri, H., Rahimi, A., & Oshnoei, A. (2025) · Electronics · doi:10.3390/electronics14112214 · Cited by 42

Energy-Efficient and delay-guaranteed computation offloading for fog-based IoT networks

Shahryari, O., Pedram, H., Khajehvand, V., & Fooladi, M. D. T. (2020) · Computer Networks · doi:10.1016/j.comnet.2020.107511 · Cited by 42

Edge Computing vs. Cloud Computing: Challenges and Opportunities in Industry 4.0

Bajić, B., Ćosić, I., Katalinić, B., Morača, S., Lazarević, M., & Rikalović, A. (2019) · Annals of DAAAM for ... & proceedings of the ... International DAAAM Symposium · doi:10.2507/30th.daaam.proceedings.120 · Cited by 41

Dynamic Microservice Allocation for Virtual Reality Distribution With QoE Support

Alencar, D., Both, C. B., Antunes, R. S., Oliveira, H. M. N. D. S., Cerqueira, E., & do Rosário, D. L. (2021) · IEEE Transactions on Network and Service Management · doi:10.1109/tnsm.2021.3076922 · Cited by 40

Horizontal Review on Video Surveillance for Smart Cities: Edge Devices, Applications, Datasets, and Future Trends

Ezzat, M. A., Abd El Ghany, M. A., Almotairi, S., & Salem, M. A.-M. (2021) · Sensors · doi:10.3390/s21093222 · Cited by 39

Genetic-based optimization in fog computing: Current trends and research opportunities

Guerrero, C., Lera, I., & Juiz, C. (2022) · Swarm and Evolutionary Computation · doi:10.1016/j.swevo.2022.101094 · Cited by 39

Analytical models for availability evaluation of edge and fog computing nodes

Pereira, P., Araujo, J., Melo, C., Santos, V., & Maciel, P. (2021) · The Journal of Supercomputing · doi:10.1007/s11227-021-03672-0 · Cited by 38

A Survey of Cloudlet-Based Mobile Augmentation Approaches for Resource Optimization

Nayyer, M. Z., Raza, I., & Hussain, S. A. (2018) · ACM Computing Surveys · doi:10.1145/3241738 · Cited by 36

Fog Computing Potentials, Applications, and Challenges

Haouari, F., Faraj, R., & Alja’am, J. M. (2018) · International Conference on Computer and Applications (ICCA) · doi:10.1109/comapp.2018.8460182 · Cited by 35

A Smart Classroom Based on Deep Learning and Osmotic IoT Computing

Pacheco, A., Cano, P., Flores, E., Trujillo, E., & Márquez, P. (2018) · Congreso Internacional de Innovación y Tendencias en Ingeniería (CONIITI) · doi:10.1109/coniiti.2018.8587095 · Cited by 34

A multi-Agent based model for task scheduling in cloud-fog computing platform

Fellir, F., Attar, A. E., Nafil, K., & Chung, L. (2020) · IEEE International Conference on Informatics, IoT, and Enabling Technologies (ICIoT) · doi:10.1109/iciot48696.2020.9089625 · Cited by 34

Proactive auto-scaling technique for web applications in container-based edge computing using federated learning model

Dogani, J., & Khunjush, F. (2024) · Journal of Parallel and Distributed Computing · doi:10.1016/j.jpdc.2024.104837 · Cited by 32

Building Information Modeling and Digital Twins for Functional and Technical Design of Smart Buildings with Distributed IoT Networks—Review and New Challenges Discussion

Walczyk, G., & Ożadowicz, A. (2024) · Future Internet · doi:10.3390/fi16070225 · Cited by 32

Real-time Data Analytics Edge Computing Application for Industry 4.0: The Mahalanobis-Taguchi Approach

Bajić, B., Suzić, N., Simeunović, N., Morača, S., & Rikalović, A. (2020) · International Journal of Industrial Engineering and Management · doi:10.24867/ijiem-2020-3-260 · Cited by 31

Cyber Attacks Detection based on Deep Learning for Cloud-Dew Computing in Automotive IoT Applications

Moussa, M. M., & Alazzawi, L. (2020) · IEEE International Conference on Smart Cloud (SmartCloud) · doi:10.1109/smartcloud49737.2020.00019 · Cited by 31

Collaboration of Heterogeneous Edge Computing Paradigms: How to Fill the Gap Between Theory and Practice

Cai, Q., Zhou, Y., Liu, L., Qi, Y., Pan, Z., & Zhang, H. (2023) · IEEE Wireless Communications · doi:10.1109/mwc.014.2200283 · Cited by 31

Flat and hierarchical system deployment for edge computing systems

Wang, E., Li, D., Dong, B., Zhou, H., & Zhu, M. (2019) · Future Generation Computer Systems · doi:10.1016/j.future.2019.12.004 · Cited by 30

Intelligent Video Analytics for Human Action Recognition: The State of Knowledge

Kulbacki, M., Segen, J., Chaczko, Z., Rozenblit, J. W., Kulbacki, M., Klempous, R., & Wojciechowski, K. W. (2023) · Sensors · doi:10.3390/s23094258 · Cited by 31

Map-type Modelling and Analysis of Children Stunting Case Data in Indonesia with Interactive Multimedia Method

Moniaga, J. V., Ohyver, M., Siregar, J., & Yauwito, P. H. (2019) · Procedia Computer Science · doi:10.1016/j.procs.2019.09.010 · Cited by 29

A multi‐queue priority‐based task scheduling algorithm in fog computing environment

Fahad, M., Shojafar, M., Abbas, M., Ahmed, I., & Ijaz, H. (2022) · Concurrency and Computation Practice and Experience · doi:10.1002/cpe.7376 · Cited by 29

HS-DCell: A Highly Scalable DCell-Based Server-Centric Topology for Data Center Networks

Wang, G., Zhang, Y., Yu, J., Ma, M., Hu, C., Fan, J., & Zhang, L. (2024) · IEEE/ACM Transactions on Networking · doi:10.1109/tnet.2024.3398628 · Cited by 28

F2c2C-DM: A Fog-to-cloudlet-to-Cloud Data Management Architecture in Smart City

Sinaeepourfard, A., Krogstie, J., Petersen, S. A., & Ahlers, D. (2019) · IEEE World Forum on Internet of Things (WF-IoT) · doi:10.1109/wf-iot.2019.8767226 · Cited by 28

Data offloading in IoT environments: modeling, analysis, and verification

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CF-CloudOrch: container fog node-based cloud orchestration for IoT networks

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