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

Abstract

Energy is the most precious resource in wireless sensor networks. To ensure sustainable operations, wireless sensor systems need to harvest energy from environments. The timevarying 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. I. INTRODUCTIONTo ensure sustainable operations of wireless sensor networks, environmental energy harvesting has been regarded as the right solution for long-term applications. However, the harvested energy is usually not sufficient to allow the sensor nodes to keep active all the time. Therefore, the bottleneck in sustainable wireless sensor networks is energy instead of computing and communication capabilities. What is worse is that the availability of energy in a sustainable sensor network is intermittent and varies over time. Thus it becomes important to shift the focus from the constraint of computation and communication to the energy constraint and explore a method, which dynamically schedules tasks based on energy.In this paper, we propose dynamic energy-oriented scheduling -a method that allocates tasks to resources based on the system's instantaneous available energy and the tasks' energy consumption. The novel features are (i) the ability to decompose and recombine tasks to eliminate redundant operations, and (ii) the concurrent execution to simultaneously utilize multiple resources (e.g., sensing and communication). In addition, admission control is applied to ensure the execution of high priority tasks when there is insufficient energy. It is a challenging task to build an energy efficient and light weight scheduling method because the scheduling operation also consumes energy. This calls for a design that reduces scheduler overhead. It should be noted that dynamic energyoriented scheduling achieves a balance between the system's available energy and the energy consumption of tasks in real time. Such a realtime balance makes our work on energyoriented scheduling unique and novel. More specifically, our

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