Energy Aware Tikhonov-Regularized FPA Technique for Task Scheduling in Wearable Biomedical Devices

Harvesting the energy from environmental sources is a promising solution for perpetual and continuous operation of biomedical wearable devices. Although the energy harvesting technology ensures the availability of energy source, yet power management is crucial 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 chapter proposes a novel biosensor task scheduling of energy harvesting-based biomedical wearable devices for optimizing energy consumption, and hence maximizing the voltage across the energy storage element. 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. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.