IoT Workflow Scheduling in Cloud and Edge

Abstract

IoT devices are becoming more and more common every day and play a huge part of our everyday lives and with these devices often having low processing power and availability to resources they also make use of edge and cloud servers. With all this information needed to be processed from different devices, it must be decided on what and when they are processed. From this, the IoT workflow scheduling problem is where we must organize through the workflows that are generated from various IoT devices and decide how they should be executed. To solve this problem this project proposes a Particle Swarm Optimization (PSO) based algorithm that can find a near-optimal solution to IoT workflow scheduling in cloud and edge. This solution is developed to focus on reducing both the energy and the makespan of executing a set of workflows. With this proposed solution we thoroughly evaluate and compare its performance against already existing methods using benchmark workflows showing the algorithm ability to efficiently find a near optimal solution.