A Novel Power-Aware Task Scheduling for Energy Harvesting-Based Wearable Biomedical Devices Using FPA

Abstract

Power management and saving in energy harvesting-based biomedical wearable devices are mandatory to ensure prolonged and stable operation under a stringent power budget. Thus, power-aware task scheduling can play a key role in minimizing energy consumption to improve system durability while maintaining device functionality. This paper proposes a novel biosensor task scheduling for optimizing energy consumption through wearable biomedical devices. The proposed approach is based on Flower Pollination Algorithm (FPA). The biomedical functionality constraints are enforced with a Hamming-based Tikhonov regularization. We proposed a greedy approach to compute the Tikhonov regularization term efficiently. The algorithm has been tested for scheduling the tasks of two biosensors: a heart rate sensor and a temperature sensor on a lab-based biomedical device.