battery-aware static scheduling for distributed real-time embedded systems
This paper addresses battery-aware static scheduling in battery-powered distributed real-time embedded systems. As suggested by previous work, reducing the discharge current level and shaping its distribution are essential for extending the battery lifespan. We propose two battery-aware static scheduling schemes. The first one optimizes the discharge power profile in order to maximize the utilization of the battery capacity. The second one targets distributed systems composed of voltage-scalable processing elements (PEs). It performs variable-voltage scheduling via efficient slack time re-allocation, which helps reduce the average discharge power consumption as well as flatten the discharge power profile. Both schemes guarantee the hard real-time constraints and precedence relationships in the real-time distributed embedded system specification. Based on previous work, we develop a battery lifespan evaluation metric which is aware of the shape of the discharge power profile. Our experimental results show that the battery lifespan can be increased by up to 29\% by optimizing the discharge power file alone. Our variable-voltage scheme increases the battery lifespan by up to 76\% over the non-voltage-scalable scheme and by up to 56\% over the variable-voltage scheme without slack-time re-allocation.
scheduling distributed real-time real-time embedded systems embedded systems paper shape batteries scheme optimality power profiles order capacities distributed systems process efficiency timing power consumption constraint relationships evaluation metrication experimentation scalability variability allocation