Energy-Efficient Access Point Deployment for Industrial IoT Systems

Internet of Things (IoT) technologies have impacted many fields by opening up much deeper and more extensive integration of communications connectivity, sensing, and embedded processing. The industrial sector is among the areas that have been impacted greatly — for example, IoT has the potential to provide novel capabilities for more effective tracking, control and optimization of industrial processes. To maintain reliable embedded processing and connectivity in industrial IoT (IIoT) systems, including systems that involve intensive use of smart wearable technologies, energy consumption is often a critical consideration. With this motivation, this paper develops an energy-efficient deployment strategy for access points in IIoT systems. The developed strategy is based on a novel genetic algorithm called the Access Point Placement Genetic Algorithm (AP2GA). Simulation results with our proposed deployment strategy demonstrate the effectiveness of AP2GA in optimizing energy consumption for IIoT systems.