energy-efficient algorithm for mixed-criticality systems in e-learning environment

Background: low-energy consumption is a vital concern in e-learning due to high-volume processing and the fact that mobile technologies are usually battery-operated devices.methods: the method is simulated by developing a discrete-event simulation in c#. the validation of the proposed method is performed on generated task sets as used in similar work. the characteristic of randomly produced tasks is similar to the well-known techniques of task generation in mixed-criticality (mc) systems.results: the simulation results show that energy consumption can be improved up to 23% in comparison to similar approaches. the most important factor for this satisfaction was the reservation times of critical tasks to further reduce the processor frequency.conclusions: the internet of thing (iot) is poised to be one of the most disruptive technologies in e-learning environment. the iot is a kind of mc system that integrates multiple things with different criticalities into the same platform. mobile technologies provide education to people through mobile devices. these devices are usually battery-operated and owing to high-volume processing, low-energy consumption becomes a vital concern in e-learning. therefore, this paper was discussed about the mc system in general. finally, the paper was proposed a scheduling technique to minimize the energy consumption of e-learning devices that use the iot.