Real-time scheduling of sporadic tasks in energy harvesting distributed reconfigurable embedded systems

This paper explores the energy-aware strategy for adaptive task allocation of sporadic task model in distributed reconfigurable embedded systems powered by a renewable energy source. It is challenging to ensure hard real-time deadlines of sporadic tasks in distributed reconfigurable embedded systems that entirely rely on energy harvesting with limited capacity storage because their release times and periods are unknown beforehand. In this regard, we propose a new scheduling algorithm for sporadic task model in energy harvesting reconfigurable distributed embedded system. The proposed approach generates an energy efficient offline task assignment heuristic. Then, the offline stage is dynamically extended online by applying a dynamic adaption algorithm. The latter performs three solutions: i) Migration, ii) Degradation of the execution mode, and iii) Removal of tasks in order to maintain schedulability and sustainability of the application software. Simulations show the efficiency of the proposed approach in term of deadline success ratio.