AI-Based Network Management for IoT Devices
DOI:
https://doi.org/10.48314/ceti.v1i1.25Keywords:
AI-based network management, IoT devices, Adaptive optimization, Predictive analytics, Network security, Intelligent decision-making, ScalabilityAbstract
The growth of the Internet of Things (IoT) has led to increased complexity in network management. Traditional methods struggle to cope with IoT devices' scalability, dynamic network conditions, and massive data volumes. Artificial Intelligence (AI) offers solutions to these challenges, providing intelligent decision-making, adaptive optimization, and predictive analytics. This paper reviews the application of AI in IoT network management, discusses existing techniques, and explores future directions for enhancing network performance, security, and efficiency through AI-driven approaches.
References
Haras, M., & Skotnicki, T. (2018). Thermoelectricity for IoT–A review. Nano energy, 54, 461–476. https://doi.org/10.1016/j.nanoen.2018.10.013
Alhaidari, F., & Balharith, T. Z. (2021). Enhanced round-robin algorithm in the cloud computing environment for optimal task scheduling. Computers, 10(5). https://doi.org/10.3390/computers10050063
Siddharth Singh, Singh, A., Sahu, A. K., & Siddiqui, N. A. (2024). Optimizing cloud performance: A comprehensive study of load balancing strategies and algorithms. Smart internet of things, 1(1 SE-Articles), 1–16. https://doi.org/10.22105/siot.v1i1.34
Shah, N., & Farik, M. (2015). Static load balancing algorithms in cloud computing: challenges & solutions. International journal of scientific & technology research, 4(10), 365–367. https://b2n.ir/d46065
Pradhan, P., Behera, P. K., & Ray, B. N. B. (2016). Modified round robin algorithm for resource allocation in cloud computing. Procedia computer science, 85, 878–890. https://doi.org/10.1016/j.procs.2016.05.278
Yang, M., Wang, H., & Zhao, J. (2015). Research on load balancing algorithm based on the unused rate of the cpu and memory. 2015 fifth international conference on instrumentation and measurement, computer, communication and control (IMCCC) (pp. 542–545). IMCCC. https://doi.org/10.1109/IMCCC.2015.120
Ma, C., & Chi, Y. (2022). Evaluation test and improvement of load balancing algorithms of nginx. IEEE access, 10, 14311–14324. https://doi.org/10.1109/ACCESS.2022.3146422
Mohapatra, H., & Rath, A. K. (2020). Fault-tolerant mechanism for wireless sensor network. IET wireless sensor systems, 10(1), 23–30. https://doi.org/10.1049/iet-wss.2019.0106
Lenka, R. K., Kolhar, M., Mohapatra, H., Al-Turjman, F., & Altrjman, C. (2022). Cluster-based routing protocol with static hub (CRPSH) for WSN-Assisted IoT networks. Sustainability, 14(12). https://doi.org/10.3390/su14127304
Mohapatra, H., & Rath, A. K. (2021). An IoT based efficient multi-objective real-time smart parking system. International journal of sensor networks, 37(4), 219–232. https://doi.org/10.1504/IJSNET.2021.119483
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