Learning-Automata-Based Energy Efficient Model for Device Lifetime Enhancement in LoRaWAN Networks

Over the past few years, Internet of Things (IoT) has become one of the foremost critical innovations of the 21st century. The broad set of applications for IoT gadgets includes consumer, commercial, industrial, and infrastructure spaces. It can also be used for environmental purposes, such as monitoring forest areas and preventing forest fires, which is critical for flora and animal conservation. For this purpose, the proper energy management is crucial, so that it is possible to continuously monitor the forest areas. In this paper, a method for extending the lifetime of devices that surveil such locations is presented. The created system employs technology based on the LoRaWAN protocol, which is a highly promising technology for wide access networks and sensor applications. A learning-automata-based energy efficient model is proposed to increase the device lifetime and therefore, the lifetime of the entire network. The suggested energy-efficient approach is tested using simulation results, which show that it increases device longevity.