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Adaptive Energy Management Scheme In Real-Time Energy Harvesting Embedded Systems, Shruti Khare
Adaptive Energy Management Scheme In Real-Time Energy Harvesting Embedded Systems, Shruti Khare
Master's Theses
The main purpose of this thesis was to develop an online adaptive energy management scheme for energy harvesting embedded systems. Two energy prediction schemes were used, namely Exponentially Weighted Moving Average (EWMA) and Adaptive Forward Prediction (AFP), to schedule all the tasks with least deadline miss rate. The AFP scheme has a mean relative error of 6-10% which is much lower than exponentially weighted moving average (EWMA) algorithm with an error of 30%. The large difference in the error percentage between the two prediction algorithms is due to the adaptive nature of AFP as it tracks small changes in input …