Edge computing research: a bibliometric analysis and JEC Volume 3 Issue 2 (2024) highlights
Article Sidebar
Main Article Content
Abstract
This editorial presents a bibliometric analysis of edge computing research published in IEEE Access from 2018 to 2023, followed by an overview and discussion of the papers featured in the current issue of the Journal of Edge Computing (JEC), Volume 3, Issue 2 (2024). The IEEE Access analysis reveals key trends and themes in edge computing research, including IoT integration, AI and machine learning applications, resource management, wireless networks, and security concerns. The most cited authors, countries, and collaboration patterns are also identified. The JEC papers align well with these findings, addressing challenges and proposing novel solutions in areas such as IoT interoperability, plant disease detection using deep learning, wireless technologies in IoT projects, efficient operating systems, and adaptive IoT honeypot frameworks. The research in both IEEE Access and JEC demonstrates the rapid advancements and growing importance of edge computing in various domains.
Downloads
Article Details
This work is licensed under a Creative Commons Attribution 4.0 International License.
How to Cite
References
Alabdulatif, A., Khalil, I., Yi, X. and Guizani, M., 2019. Secure Edge of Things for Smart Healthcare Surveillance Framework. IEEE Access, 7, pp.31010–31021. Available from: https://doi.org/10.1109/ACCESS.2019.2899323. DOI: https://doi.org/10.1109/ACCESS.2019.2899323
Amin, S.U. and Hossain, M.S., 2021. Edge Intelligence and Internet of Things in Healthcare: A Survey. IEEE Access, 9, pp.45–59. Available from: https://doi.org/10.1109/ACCESS.2020.3045115. DOI: https://doi.org/10.1109/ACCESS.2020.3045115
Bakir, F., Wang, S., Ekaireb, T., Pearson, J., Krintz, C. and Wolski, R., 2024. Ambience: an operating system for IoT microservices. Journal of Edge Computing, 3(2), pp.168–206. Available from: https://doi.org/10.55056/jec.786. DOI: https://doi.org/10.55056/jec.786
Celaya-Echarri, M., Froiz-Miguez, I., Azpilicueta, L., Fraga-Lamas, P., Lopez-Iturri, P., Falcone, F. and Fernandez-Carames, T.M., 2020. Building Decentralized Fog Computing-Based Smart Parking Systems: From Deterministic Propagation Modeling to Practical Deployment. IEEE Access, 8, pp.117666–117688. Available from: https://doi.org/10.1109/ACCESS.2020.3004745. DOI: https://doi.org/10.1109/ACCESS.2020.3004745
Dang, T.N., Manzoor, A., Tun, Y.K., Kazmi, S.M.A., Haw, R., Hong, S.H., Han, Z. and Hong, C.S., 2022. Joint Communication, Computation, and Control for Computational Task Offloading in Vehicle-Assisted Multi-Access Edge Computing. IEEE Access, 10, pp.122513–122529. Available from: https://doi.org/10.1109/ACCESS.2022.3220251. DOI: https://doi.org/10.1109/ACCESS.2022.3220251
Duan, X., Li, B. and Zhao, W., 2020. Energy Consumption Minimization for Near-Far Server Cooperation in NOMA-Assisted Mobile Edge Computing System. IEEE Access, 8, pp.133269–133282. Available from: https://doi.org/10.1109/ACCESS.2020.3010571. DOI: https://doi.org/10.1109/ACCESS.2020.3010571
El-Latif, A.A.A., Abd-El-Atty, B., Hossain, M.S., Elmougy, S. and Ghoneim, A., 2018. Secure quantum steganography protocol for fog cloud internet of things. IEEE Access, 6, pp.10332–10340. Available from: https://doi.org/10.1109/ACCESS.2018.2799879. DOI: https://doi.org/10.1109/ACCESS.2018.2799879
Fernandez-Carames, T.M. and Fraga-Lamas, P., 2019. A Review on the Application of Blockchain to the Next Generation of Cybersecure Industry 4.0 Smart Factories. IEEE Access, 7, pp.45201–45218. Available from: https://doi.org/10.1109/ACCESS.2019.2908780. DOI: https://doi.org/10.1109/ACCESS.2019.2908780
Fernández-Caramés, T.M. and Fraga-Lamas, P., 2018. A Review on the Use of Blockchain for the Internet of Things. IEEE Access, 6, pp.32979–33001. Available from: https://doi.org/10.1109/ACCESS.2018.2842685. DOI: https://doi.org/10.1109/ACCESS.2018.2842685
Filali, A., Abouaomar, A., Cherkaoui, S., Kobbane, A. and Guizani, M., 2020. Multiaccess edge computing: A survey. IEEE Access, 8, pp.197017–197046. Available from: https://doi.org/10.1109/ACCESS.2020.3034136. DOI: https://doi.org/10.1109/ACCESS.2020.3034136
Fraga-Lamas, P., Fernández-Caramés, T.M., Blanco-Novoa, O. and Vilar-Montesinos, M.A., 2018. A Review on Industrial Augmented Reality Systems for the Industry 4.0 Shipyard. IEEE Access, 6, pp.13358–13375. Available from: https://doi.org/10.1109/ACCESS.2018.2808326. DOI: https://doi.org/10.1109/ACCESS.2018.2808326
Fraga-Lamas, P., Lopez-Iturri, P., Celaya-Echarri, M., Blanco-Novoa, O., Azpilicueta, L., Varela-Barbeito, J., Falcone, F. and Fernandez-Carames, T.M., 2020. Design and Empirical Validation of a Bluetooth 5 Fog Computing Based Industrial CPS Architecture for Intelligent Industry 4.0 Shipyard Workshops. IEEE Access, 8, pp.45496–45511. Available from: https://doi.org/10.1109/ACCESS.2020.2978291. DOI: https://doi.org/10.1109/ACCESS.2020.2978291
Froiz-Miguez, I., Fraga-Lamas, P. and Fernandez-Carames, T.M., 2023. Design, Implementation, and Practical Evaluation of a Voice Recognition Based IoT Home Automation System for Low-Resource Languages and Resource-Constrained Edge IoT Devices: A System for Galician and Mobile Opportunistic Scenarios. IEEE Access, 11, pp.63623–63649. Available from: https://doi.org/10.1109/ACCESS.2023.3286391. DOI: https://doi.org/10.1109/ACCESS.2023.3286391
Gheisari, M., Pham, Q.V., Alazab, M., Zhang, X., Fernandez-Campusano, C. and Srivastava, G., 2019. ECA: An edge computing architecture for privacy-preserving in IoT-Based smart city. IEEE Access, 7, pp.155779–155786. Available from: https://doi.org/10.1109/ACCESS.2019.2937177. DOI: https://doi.org/10.1109/ACCESS.2019.2937177
Hamim, S.A. and Jony, A.I., 2024. Enhanced deep learning model architecture for plant disease detection in Chilli plants. Journal of Edge Computing, 3(2), pp.135–146. Available from: https://doi.org/10.55056/jec.758. DOI: https://doi.org/10.55056/jec.758
Han, C., Zhang, P., Wang, W., Wang, Y. and Zhang, Z., 2019. Delay-Optimal Joint Processing in Computation-Constrained Fog Radio Access Networks. IEEE Access, 7, pp.58857–58865. Available from: https://doi.org/10.1109/ACCESS.2019.2913147. DOI: https://doi.org/10.1109/ACCESS.2019.2913147
Hao, Y., Chen, M., Hu, L., Hossain, M.S. and Ghoneim, A., 2018. Energy Efficient Task Caching and Offloading for Mobile Edge Computing. IEEE Access, 6, pp.11365–11373. Available from: https://doi.org/10.1109/ACCESS.2018.2805798. DOI: https://doi.org/10.1109/ACCESS.2018.2805798
Hou, Y., Garg, S., Hui, L., Jayakody, D.N.K., Jin, R. and Hossain, M.S., 2020. A data security enhanced access control mechanism in mobile edge computing. IEEE Access, 8, pp.136119–136130. Available from: https://doi.org/10.1109/ACCESS.2020.3011477. DOI: https://doi.org/10.1109/ACCESS.2020.3011477
Irshad, R.R., Hussain, S., Hussain, I., Ahmad, I., Yousif, A., Alwayle, I.M., Alattab, A.A., Alalayah, K.M., Breslin, J.G., Badr, M.M. and Rodrigues, J.J.P.C., 2023. An Intelligent Buffalo-Based Secure Edge-Enabled Computing Platform for Heterogeneous IoT Network in Smart Cities. IEEE Access, 11, pp.69282–69294. Available from: https://doi.org/10.1109/ACCESS.2023.3288815. DOI: https://doi.org/10.1109/ACCESS.2023.3288815
Jiang, L., Huang, G., Huang, C. and Wang, W., 2019. Data mining and optimization of a port vessel behavior behavioral model under the internet of things. IEEE Access, 7, pp.139970–139983. Available from: https://doi.org/10.1109/ACCESS.2019.2943654. DOI: https://doi.org/10.1109/ACCESS.2019.2943654
Li, M., Zhu, L., Zhang, Z., Du, X. and Guizani, M., 2018. PROS: A privacy-preserving route-sharing service via vehicular fog computing. IEEE Access, 6, pp.66188–66197. Available from: https://doi.org/10.1109/ACCESS.2018.2878792. DOI: https://doi.org/10.1109/ACCESS.2018.2878792
Li, S., Li, B. and Zhao, W., 2020. Joint Optimization of Caching and Computation in Multi-Server NOMA-MEC System via Reinforcement Learning. IEEE Access, 8, pp.112762–112771. Available from: https://doi.org/10.1109/ACCESS.2020.3002895. DOI: https://doi.org/10.1109/ACCESS.2020.3002895
Luan, L., Xiao, W., Hwang, K., Hossain, M.S., Muhammad, G. and Ghoneim, A., 2020. Memo box: Health assistant for depression with medicine carrier and exercise adjustment driven by edge computing. IEEE Access, 8, pp.195568–195577. Available from: https://doi.org/10.1109/ACCESS.2020.3031725. DOI: https://doi.org/10.1109/ACCESS.2020.3031725
Morozov, D.S., Yefimenko, A.A., Nikitchuk, T.M., Kolomiiets, R.O. and Semerikov, S.O., 2024. The sweet taste of IoT deception: an adaptive honeypot framework for design and evaluation. Journal of Edge Computing, 3(2), pp.207–223. Available from: https://doi.org/10.55056/jec.607. DOI: https://doi.org/10.55056/jec.607
Nduwayezu, M., Pham, Q.V. and Hwang, W.J., 2020. Online Computation Offloading in NOMA-Based Multi-Access Edge Computing: A Deep Reinforcement Learning Approach. IEEE Access, 8, pp.99098–99109. Available from: https://doi.org/10.1109/ACCESS.2020.2997925. DOI: https://doi.org/10.1109/ACCESS.2020.2997925
Neto, A.J.V., Zhao, Z., Rodrigues, J.J.P.C., Camboim, H.B. and Braun, T., 2018. Fog-based crime-assistance in smart IoT transportation system. IEEE Access, 6, pp.11101–11111. Available from: https://doi.org/10.1109/ACCESS.2018.2803439. DOI: https://doi.org/10.1109/ACCESS.2018.2803439
Pham, H.G.T., Pham, Q.V., Pham, A.T. and Nguyen, C.T., 2020. Joint Task Offloading and Resource Management in NOMA-Based MEC Systems: A Swarm Intelligence Approach. IEEE Access, 8, pp.190463–190474. Available from: https://doi.org/10.1109/ACCESS.2020.3031614. DOI: https://doi.org/10.1109/ACCESS.2020.3031614
Pham, Q.V., Fang, F., Ha, V.N., Piran, M.J., Le, M., Le, L.B., Hwang, W.J. and Ding, Z., 2020. A Survey of Multi-Access Edge Computing in 5G and Beyond: Fundamentals, Technology Integration, and State-of-the-Art. IEEE Access, 8, pp.116974–117017. Available from: https://doi.org/10.1109/ACCESS.2020.3001277. DOI: https://doi.org/10.1109/ACCESS.2020.3001277
Pham, Q.V., Le, L.B., Chung, S.H. and Hwang, W.J., 2019. Mobile Edge Computing with Wireless Backhaul: Joint Task Offloading and Resource Allocation. IEEE Access, 7, pp.16444–16459. Available from: https://doi.org/10.1109/ACCESS.2018.2883692. DOI: https://doi.org/10.1109/ACCESS.2018.2883692
Pham, Q.V., Leanh, T., Tran, N.H., Park, B.J. and Hong, C.S., 2018. Decentralized computation offloading and resource allocation for mobile-edge computing: A matching game approach. IEEE Access, 6, pp.75868–75885. Available from: https://doi.org/10.1109/ACCESS.2018.2882800. DOI: https://doi.org/10.1109/ACCESS.2018.2882800
Pundir, S., Wazid, M., Singh, D.P., Das, A.K., Rodrigues, J.J.P.C. and Park, Y., 2020. Intrusion Detection Protocols in Wireless Sensor Networks Integrated to Internet of Things Deployment: Survey and Future Challenges. IEEE Access, 8, pp.3343–3363. Available from: https://doi.org/10.1109/ACCESS.2019.2962829. DOI: https://doi.org/10.1109/ACCESS.2019.2962829
Rahman, M.A., Hossain, M.S., Loukas, G., Hassanain, E., Rahman, S.S., Alhamid, M.F. and Guizani, M., 2018. Blockchain-Based Mobile Edge Computing Framework for Secure Therapy Applications. IEEE Access, 6, pp.72469–72478. Available from: https://doi.org/10.1109/ACCESS.2018.2881246. DOI: https://doi.org/10.1109/ACCESS.2018.2881246
Rahman, M.A., Rashid, M.M., Shamim Hossain, M., Hassanain, E., Alhamid, M.F. and Guizani, M., 2019. Blockchain and IoT-Based Cognitive Edge Framework for Sharing Economy Services in a Smart City. IEEE Access, 7, pp.18611–18621. Available from: https://doi.org/10.1109/ACCESS.2019.2896065. DOI: https://doi.org/10.1109/ACCESS.2019.2896065
Shvaika, D.I., Shvaika, A.I. and Artemchuk, V.O., 2024. Advancing IoT interoperability: dynamic data serialization using ThingsBoard. Journal of Edge Computing, 3(2), pp.126–135. Available from: https://doi.org/10.55056/jec.745. DOI: https://doi.org/10.55056/jec.745
Tang, C., Wei, X., Zhu, C., Chen, W. and Rodrigues, J.J., 2018. Towards smart parking based on fog computing. IEEE Access, 6, pp.70172–70185. Available from: https://doi.org/10.1109/ACCESS.2018.2880972. DOI: https://doi.org/10.1109/ACCESS.2018.2880972
Tang, C., Zhu, C., Wei, X., Wu, H., Li, Q. and Rodrigues, J.J.P.C., 2020. Intelligent Resource Allocation for Utility Optimization in RSU-Empowered Vehicular Network. IEEE Access, 8, pp.94453–94462. Available from: https://doi.org/10.1109/ACCESS.2020.2995797. DOI: https://doi.org/10.1109/ACCESS.2020.2995797
Tun, Y.K., Kim, D.H., Alsenwi, M., Tran, N.H., Han, Z. and Hong, C.S., 2020. Energy efficient communication and computation resource slicing for eMBB and URLLC coexistence in 5G and beyond. IEEE Access, 8, pp.136024–136035. Available from: https://doi.org/10.1109/ACCESS.2020.3011167. DOI: https://doi.org/10.1109/ACCESS.2020.3011167
Ud Din, I., Guizani, M., Hassan, S., Kim, B.S., Khurram Khan, M., Atiquzzaman, M. and Ahmed, S.H., 2019. The Internet of Things: A Review of Enabled Technologies and Future Challenges. IEEE Access, 7, pp.7606–7640. Available from: https://doi.org/10.1109/ACCESS.2018.2886601. DOI: https://doi.org/10.1109/ACCESS.2018.2886601
Vakaliuk, T.A., Andreiev, O.V., Dubyna, O.F., Korenivska, O.L. and Andreieva, Y.O., 2024. Use of wireless technologies in IoT projects. Journal of Edge Computing, 3(2), pp.147–167. Available from: https://doi.org/10.55056/jec.750. DOI: https://doi.org/10.55056/jec.750
Wang, D., Bai, B., Lei, K., Zhao, W., Yang, Y. and Han, Z., 2019. Enhancing Information Security via Physical Layer Approaches in Heterogeneous IoT With Multiple Access Mobile Edge Computing in Smart City. IEEE Access, 7, pp.54508–54521. Available from: https://doi.org/10.1109/ACCESS.2019.2913438. DOI: https://doi.org/10.1109/ACCESS.2019.2913438
Wang, W., Fan, L., Huang, P. and Li, H., 2019. A new data processing architecture for multi-scenario applications in aviation manufacturing. IEEE Access, 7, pp.83637–83650. Available from: https://doi.org/10.1109/ACCESS.2019.2925114. DOI: https://doi.org/10.1109/ACCESS.2019.2925114
Waqas, M., Niu, Y., Ahmed, M., Li, Y., Jin, D. and Han, Z., 2019. Mobility-Aware Fog Computing in Dynamic Environments: Understandings and Implementation. IEEE Access, 7, pp.38867–38879. Available from: https://doi.org/10.1109/ACCESS.2018.2883662. DOI: https://doi.org/10.1109/ACCESS.2018.2883662
Wu, C., Wang, W. and Sun, H., 2021. Dense Aggregation Based Efficient Network for Image Semantic Segmentation in Edge Intelligent Tasks. IEEE Access, 9, pp.21–29. Available from: https://doi.org/10.1109/ACCESS.2020.3046041. DOI: https://doi.org/10.1109/ACCESS.2020.3046041
Xia, Z., Du, J., Ren, Y. and Han, Z., 2022. Distributed Artificial Intelligence Enabled Aerial-Ground Networks: Architecture, Technologies and Challenges. IEEE Access, 10, pp.105447–105457. Available from: https://doi.org/10.1109/ACCESS.2022.3210337. DOI: https://doi.org/10.1109/ACCESS.2022.3210337
Ye, D., Yu, R., Pan, M. and Han, Z., 2020. Federated Learning in Vehicular Edge Computing: A Selective Model Aggregation Approach. IEEE Access, 8, pp.23920–23935. Available from: https://doi.org/10.1109/ACCESS.2020.2968399. DOI: https://doi.org/10.1109/ACCESS.2020.2968399
Yeow, K., Gani, A., Ahmad, R.W., Rodrigues, J.J.P.C. and Ko, K., 2018. Decentralized Consensus for Edge-Centric Internet of Things: A Review, Taxonomy, and Research Issues. IEEE Access, 6, pp.1513–1524. Available from: https://doi.org/10.1109/ACCESS.2017.2779263. DOI: https://doi.org/10.1109/ACCESS.2017.2779263
Zhao, P., Zhao, W., Bao, H. and Li, B., 2020. Security Energy Efficiency Maximization for Untrusted Relay Assisted NOMA-MEC Network with WPT. IEEE Access, 8, pp.147387–147398. Available from: https://doi.org/10.1109/ACCESS.2020.3015786. DOI: https://doi.org/10.1109/ACCESS.2020.3015786
Zhao, W., Wang, B., Bao, H. and Li, B., 2020. Secure Energy-Saving Resource Allocation on Massive MIMO-MEC System. IEEE Access, 8, pp.137244–137253. Available from: https://doi.org/10.1109/ACCESS.2020.3011694. DOI: https://doi.org/10.1109/ACCESS.2020.3011694
Zhao, W., Xu, L., Qi, B., Hu, J., Wang, T. and Runge, T., 2020. Vivid: Augmenting Vision-Based Indoor Navigation System with Edge Computing. IEEE Access, 8, pp.42909–42923. Available from: https://doi.org/10.1109/ACCESS.2020.2978123. DOI: https://doi.org/10.1109/ACCESS.2020.2978123
Zhao, Y., Wang, W., Li, Y., Colman Meixner, C., Tornatore, M. and Zhang, J., 2019. Edge Computing and Networking: A Survey on Infrastructures and Applications. IEEE Access, 7, pp.101213–101230. Available from: https://doi.org/10.1109/ACCESS.2019.2927538. DOI: https://doi.org/10.1109/ACCESS.2019.2927538