Balancing Quality of Service and Lifetime in Solar-Powered IoT via Hyper-Adaptive Duty Cycling

Lei Liu

Abstract


Networks for energy-harvesting Internet of Things (EH-IoT) offer promising opportunities for long-term, autonomous operation in various applications, including infrastructure surveillance, smart agriculture, and environmental monitoring. However, the unpredictable nature of energy collection—especially from solar sources—poses significant challenges in maintaining continuous operation and ensuring timely data transmission. Many studies today don't have a complete method for managing how often devices send and sleep, which is important for saving energy, handling data buildup, and changing schedules as needed. A new method called Hyper-Adaptive Duty Cycling is suggested, which adjusts when devices transmit data and when they rest based on the amount of energy they harvest, the volume of data they need to send, and their remaining battery level. This method focuses on keeping the quality of service high while using special rules and short, powerful bursts of energy to send more data. This method is tested over three years using simulations with real data from solar panels. It managed to send data at a high rate of 78.29%, kept data buffers almost empty, but used more energy, which made the network last only about 24.6 days. Conversely, a method that uses a fixed schedule lasted longer, about 28.1 days, but only sent 32% of the data. These results show the balance between sending data quickly with good quality and making sure the network lasts longer. Our method gives a flexible way to manage energy in IoT networks that can be adjusted based on what the network is doing and the environment it's in, helping designers choose the best approach for their specific needs.


Keywords


Hyper-Adaptive Duty Cycling; Quality of Service; Solar-Powered IoT; Energy-Harvesting Sensor Networks; Network Lifetime Optimization

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References


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DOI (PDF): https://doi.org/10.20508/ijrer.v15i4.16778.g9135

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