An osmotic approach-based dynamic deadline-aware task offloading in edge-fog-cloud computing environment

Edge-fog-cloud computing system can be divided into edge or IoT layer (tier 1), fog layer (tier 2) and cloud layer (tier 3). The devices at the edge layer generate different types of tasks which may be computation-intensive or communication intensive or having a combination of these properties. Depending on the characteristics of tasks, those may be scheduled to run at the edge or fog or cloud layers. There are many advantages of offloading some of the computationally intensive workloads, which includes improved response time, satisfying the deadlines of delay-sensitive tasks and overall reduced make span of the workloads. In this context, there is a need for designing a scheduling algorithm with the goal to minimize the overall execution time while satisfying the deadlines of the tasks and maximizing the resource utilization at fog layer. In this paper, we are proposing a task offloading and scheduling algorithm based on the osmotic approach. In the osmotic approach, the devices and tasks are classified, and the tasks are assigned to the most suitable devices based on their dynamically available capacity. The proposed scheduling algorithm is compared with traditional random task offloading and round robin task offloading algorithms using synthetic data sets and found that the proposed algorithm performance is significantly better than other algorithms.