An Energy-Efficient Middleware for Computation Offloading in Real-Time Embedded Systems

Embedded systems have limited resources, such as computation capabilities and battery life. The Dynamic Voltage and Frequency Scaling (DVFS) technique is used to save energy by running the processor of the embedded system at low voltage and frequency levels. However, this prolongs the execution time, which may cause potential deadline misses for real-time tasks. In this paper, we propose a general-purpose middleware to reduce the energy consumption in embedded systems without violating the real-time constraints. The algorithms in the middleware adopt the computation offloading concept to reduce the workload on the processor of the embedded system by sending the computation-intensive tasks to a powerful server. The algorithms are further combined with the DVFS technique to find the running frequency (or speed) such that the energy consumption is minimized and the real-time constraints are satisfied. The evaluation shows that our approach reduces the average energy consumption down to nearly 60%, compared to executing all the tasks locally at the maximum processor speed.