Sustainable Energy-Aware Task Scheduling for Wearable Medical Device Using Flower Pollination Algorithm

Abstract

Power management and energy conservation are crucial for medical wearable devices that rely on energy harvesting. These devices operate under strict power budgets and require prolonged and stable operation. To achieve this, Energy-aware task scheduling is proposed as a solution to minimize energy consumption while ensuring the continued operational capabilities of the device. our paper presents a task scheduling method using the Flower Pollination Algorithm (FPA). The proposed task scheduling focuses on managing the activity of key components such as the heart rate sensor, temperature sensor, glucose sensor, and communication module. In this paper, we aim to contribute to the field of wearable medical devices by providing a power-aware task scheduling approach that optimizes energy management. By employing the FPA algorithm, we expect significant improvements in power efficiency, long-term reliability of the system, and long-term device functionality.