IoT adaptive threshold energy management algorithm based on energy harvesting

Abstract

The Internet of Things (IoT) provides a promising solution to resolve pipeline conditions and oil and gas leakage detection problems. How to realize complex data monitoring and data uploading in energy-constrained sensor nodes is an urgent problem for oil and gas IoT. Energy harvesting technology and energy-efficient management have been introduced to the oil and gas IoT to improve energy utilization efficiency and good network performance. In this paper, we propose an energy management algorithm for oil and gas IoT. The scheme consists of: (1) the nodes mode switching strategy which allows sensor nodes to perform specific tasks based on the current energy level and (2) cluster head selection algorithm which considers energy harvesting and energy consumption ratios to achieve a balance between network performance and lifetime. Moreover, for the timely upload of essential data, we propose an adaptive threshold strategy that considers the energy level and importance level of sensor nodes to prioritize the transmission of important data under energy-limited conditions. The simulation results show that the proposed scheme can simultaneously prolong the network lifetime and improve energy utilization efficiency and is superior to existing schemes.