Retention based energy harvesting technique for efficient internet of things aided edge devices

Abstract Energy harvesting (EH) in the internet of things (IoT) platform improves the efficiency of the connected independent devices. In particular, edge devices provide in-network communication and computation services for different user applications. Therefore, EH's need in these networks is prominent for improving energy efficiency (EE) in delivering services. In this article, Minimal Retention EH (MREH) technique is introduced for improving the EE of distributed IoT edge computing services. This technique focuses on distributed EH for the swapping computation process based on the edge nodes' EE. The need for computing resources based on the available energy is determined using probabilistic learning. This learning recommends the edge nodes for swapping computations for retention energy and preventing them from being completely drained. The learning process is performed recurrently until all the computations are shared between the edge devices without energy losses. The proposed MREH is assessed using experiments for the metrics energy utilization, lifetime of the edge nodes, delay, and service responses.