Planning and Optimization of Software-Defined and Virtualized IoT Gateway Deployment for Smart Campuses

Area of Science:

• Computer Science
• Electrical Engineering
• Network Engineering

Background:

• The Internet of Things (IoT) generates vast amounts of data, necessitating robust infrastructure.
• Heterogeneous devices and geographical spread require efficient IoT gateway solutions.
• The SOFTWAY4IoT project developed a versatile software-defined IoT gateway.

Purpose of the Study:

• To propose an optimization-based planning method for deploying IoT gateways in smart campus environments.
• To determine the optimal number, placement, and device allocation for IoT gateways.
• To evaluate deployment strategies using LoRa, Wi-Fi, and BLE communication technologies.

Main Methods:

• Developed optimization models using linear programming for gateway quantification.
• Employed K-means clustering and particle swarm optimization for gateway positioning and device distribution.
• Defined communication range and data link consumption as key optimization parameters.
• Conducted case studies and experiments at the Samambaia Campus, Federal University of Goiás.

Main Results:

• Quantified the minimum number of IoT gateways required for area coverage.
• Identified optimal gateway positions and efficiently distributed IoT devices among gateways.
• Validated the effectiveness of the proposed models through experimental analysis and hypothesis testing.

Conclusions:

• The proposed optimization method provides an effective solution for planning IoT gateway deployments in smart campuses.
• The models successfully balance gateway numbers, positions, and device distribution for efficient network operation.
• The study demonstrates the practical applicability of advanced optimization techniques in IoT infrastructure planning.