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A Dynamic Management Scheme for Internet of Things (IoT) Environments: Simulation and Performance Evaluation

Omar Said*

Department of Information Technology, College of Computers and Information Technology, Taif University, P.O. Box 11099, Taif, 21944, Saudi Arabia

* Corresponding Author: Omar Said. Email:

(This article belongs to this Special Issue: Artificial Intelligence of Things (AIoT): Emerging Trends and Challenges)

Computer Modeling in Engineering & Sciences 2022, 133(3), 673-695.


In recent years, the Internet of Things (IoT) technology has been considered one of the most attractive fields for researchers due to its aspirations and implications for society and life as a whole. The IoT environment contains vast numbers of devices, equipment, and heterogeneous users who generate massive amounts of data. Furthermore, things’ entry into and exit from IoT systems occur dynamically, changing the topology and content of IoT networks very quickly. Therefore, managing IoT environments is among the most pressing challenges. This paper proposes an adaptive and dynamic scheme for managing IoT environments is proposed. This management scheme depends on the use of previous management methodologies, considering two main factors. The first factor is network status, which is determined in real-time. The second factor is a management method’s suitability according to its desired administration. To test the proposed management scheme, a simulation environment is created using NS3. The metrics used to measure the management scheme performance are bandwidth consumption, energy consumption, packet loss, throughput, delay, usage rate of individual management techniques, and transformation. The simulation results prove that the proposed management scheme outperformed the individual 6LowPANSNMP, CoAP, and LWM2M management schemes.


Cite This Article

Said, O. (2022). A Dynamic Management Scheme for Internet of Things (IoT) Environments: Simulation and Performance Evaluation. CMES-Computer Modeling in Engineering & Sciences, 133(3), 673–695.

This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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