Nature inspired optimization of IoT network for delay resistant and energy efficient applications

Abstract

LoRa being an open standard has fascinated the research community due to its promising features to support IoT applications. LoRa fulfils all the requirements of low power, delay tolerance, long transmission range and scalability of the application nodes in the IoT concept. The duty cycle limitations imposed by LoRaWAN hinder the overall performance of the network. The network performance declines due to increasing in several devices communicating through the same channel, thereby degrading the network efficiency. Certain IoT deployments such as monitoring and control applications require low latency and extended network lifetime. Aspiring to attain efficient network performance, the current work proposes a nature-inspired low duty cycle MAC algorithm using the concept of the golden ratio (GR) approach to optimize the duty cycle of the LoRa network. Further, PSO algorithms have also been utilized to validate the performance of the proposed algorithm. The simulation results unveil that the proposed method outperforms the PSO algorithm by reducing the latency and power consumption by 26% and 12% respectively and extending the network lifetime by 14% as compared to the DC constraint approach.