Load Tuning for Solar Energy Powered Embedded System Using ILP

In this paper direct-coupled solar energy powered multicore architectures that provide direct power supply between photovoltaic (PV) generation and the load without the adoption of battery. We present SolarTune, a real-time scheduling technique with load tuning for sporadic tasks on solar energy powered multicore systems. The objective is to fully utilize the available solar energy while meeting the deadlines of tasks. Scheduling and power management method for multicore real-time embedded systems. This work mathematically proves that by allocating the new task to the core with the lowest utilization, we can achieve the lowest overall energy dissipation. This method, combined with a new integer linear programming (ILP) algorithm with forms the heuristic algorithm to dynamically refine the task scheduling based on the predictions of the availability of solar energy. With periodical tasks in a multi-core platform, this partitioned scheduling method is optimal for energy dissipation if the proposed utilization based scheduling and ILP algorithm is applied on each core. Experimental results show that new algorithm achieves better performance in terms of deadline miss rate, comparing to the best of existing algorithm. When applied on a multi-core platform, the heuristic algorithm achieves better efficiency.