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A Hybrid Intelligent Simulation System for Building IoT Networks: Performance Comparison of Different Router
Admir Barolli1, Shinji Sakamoto2, Kevin Bylykbashi3
1Department of Information Technology, Aleksander Moisiu University of Durres, L.1, Rruga e Currilave, 2001 Durres, Albania.
Sensors (Basel, Switzerland)
|October 27, 2022
Summary
This study introduces a hybrid intelligent system for optimizing wireless mesh network (WMN) node placement for Internet of Things (IoT) deployments. The random inertia weight method (RIWM) demonstrated superior performance in enhancing network connectivity and device coverage.
Area of Science:
- Computer Science
- Network Engineering
- Artificial Intelligence
Background:
- The proliferation of Internet of Things (IoT) devices necessitates robust network infrastructure capable of high throughput.
- Wireless Local Area Networks (WLANs), particularly Wireless Mesh Networks (WMNs) adhering to IEEE 802.11s, offer advantages for IoT but face challenges like optimal node placement.
- Effective node placement is critical for maximizing WMN performance in IoT environments.
Purpose of the Study:
- To propose and implement a hybrid intelligent system for solving the WMN node placement problem.
- To optimize mesh node positioning for enhanced mesh connectivity and comprehensive IoT device coverage.
- To evaluate the efficacy of different router replacement methods within the proposed system.
Main Methods:
- Development of a hybrid intelligent system integrating Particle Swarm Optimization (PSO), Simulated Annealing (SA), and Distributed Genetic Algorithm (DGA).
- Implementation and comparison of three router replacement methods: Constriction Method (CM), Random Inertia Weight Method (RIWM), and Rational Decrement of Vmax Method (RDVM).
- Simulation-based performance analysis focusing on mesh connectivity and client coverage metrics.
Main Results:
- The Random Inertia Weight Method (RIWM) outperformed the Constriction Method (CM) and Rational Decrement of Vmax Method (RDVM).
- RIWM achieved the highest level of mesh connectivity among the evaluated methods.
- RIWM demonstrated superior coverage of IoT clients compared to CM and RDVM.
Conclusions:
- The proposed hybrid intelligent system effectively addresses the WMN node placement problem for IoT networks.
- RIWM is identified as the most effective router replacement strategy for maximizing both connectivity and coverage in WMNs.
- The findings provide valuable insights for designing efficient and scalable IoT network infrastructures.
Keywords:
Internet of Thingsdistributed genetic algorithmparticle swarm optimizationsimulated annealingwireless mesh networksMore Related Videos
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