IOTD: intelligent offloading of tasks with deadlines in edge-fog-cloud computing environment using hybrid approach

In light of the rapidly growing and advancing Internet of Things (IoT) technology, delay sensitive tasks, deadline aware tasks, and power intensive IoT applications are on the rise, the adoption of fog computing has emerged as a promising solution for problems in IoT technology. Task offloading in the Edge-Fog-Cloud environment is difficult due to the inherent limits of IoT devices in terms of computing and storage capacity, the diversity of fog servers, and the varying characteristics of IoT tasks, such as their sensitivity to delays. However, the most challenging issue is finding the best suitable device to compute the task within the deadlines, reduce the total power consumption and minimize the computation time. The proposed IOTD algorithm aims to meet the deadlines of all tasks while minimizing the total computation time and energy consumption. The results of simulation experiments confirmed that the proposed method improves the reliability of meeting deadlines, total execution time, utilization of fog devices and total energy, compared with the state-of-the-art algorithms: Artificial Bee Colony and Osmotic Approach.