Real-time scheduling refers to the problem in which there is a deadline associated with the execution of a task. In new generation embedded systems, tasks execute in devices that use a rechargeable energy storage unit (e.g. battery or ultracapacitor) and a recharging system (e.g. photovoltaic cells). In this paper, we address the scheduling problem for a uniprocessor platform with unique voltage and frequency, that is powered by a renewable energy storage unit. First, we describe our model where two constraints need to be studied: energy and deadlines. Since executing tasks require a certain amount of energy, traditional task scheduling like Earliest Deadline as Soon as possible (EDS) and Earliest Deadline as Late as possible (EDL) are no longer convenient. We present an on-line scheduling scheme, called EDeg (Earliest Deadline with energy guarantee), that jointly accounts for characteristics of the energy source, capacity of the energy storage as well as energy consumption of the tasks, and time. In order to demonstrate the benefits of our algorithm, we compare it by means of simulation with the classical EDS and EDL. And we show that EDeg outperforms these energy non-clairvoyant algorithms in terms of both deadline miss rate and size of the energy storage unit.
AbstractWe consider the problem of real-time scheduling in uniprocessor devices powered by energy harvesters. In particular, we focus on mixed sets of tasks with time and energy constraints: hard deadline periodic tasks and soft aperiodic tasks without deadlines. We present an optimal aperiodic servicing algorithm that minimizes the response times of aperiodic tasks without compromising the schedulability of hard deadline periodic tasks. The server, called Slack Stealing with energy Preserving (SSP), is designed based on a slack stealing mechanism that profits whenever possible from available spare processing time and energy. We analytically establish the optimality of SSP. Our simulation results validate our theoretical analysis.
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