DEOS: Dynamic energy-oriented scheduling for sustainable wireless sensor networks

Energy is the most precious resource in wireless sensor networks. To ensure sustainable operations, wireless sensor systems need to harvest energy from environments. The time-varying environmental energy results in the dynamic change of the system's available energy. Therefore, how to dynamically schedule tasks to match the time-varying energy is a challenging problem. In contrast to traditional computing-oriented scheduling methods that focus on reducing computational energy consumption and meeting the tasks' deadlines, we present DEOS, a dynamic energy-oriented scheduling method, which treats energy as a first-class schedulable resource and dynamically schedules tasks based on the tasks' energy consumption and the system's real-time available energy. We extensively evaluate our system in indoor and outdoor settings. Results indicate that DEOS is extremely lightweight (e.g., energy consumption overhead in the worst case is only 0.039%) and effectively schedules tasks to utilize the dynamically available energy.