Modeling Effective IoT Task Scheduling in a Simulated Edge and Fog Cloud Environment

Applications of modern IoT devices produce a large number of tasks that are often real-time, requiring short response times and eliminating delays. Edge and Fog computing is a suitable platform for processing of IoT applications. Our contribution is the design and implementation of an algorithm that provides pseudo-optimal scheduling of IoT tasks on microcloud computing machines by minimizing the completion time of the last task in the schedule. The algorithm ensures that the deadlines of all scheduled IoT tasks are met, according to their requirements. Our novel approach is to design and implement a scheduling algorithm that aims to achieve both criteria. We designed experiments and used simulations to compare our algorithm with the Earliest Deadline First algorithm. We showed that our new approach presented in the Improved EDF algorithm achieves both criteria (makespan and deadline fulfill rate for each task) significantly better than the standard algorithm.