Adaptive Scheduling Architecture for IoT Environment

In the era of intelligent connected Internet of Things (IoT) devices, which are limited in computing, communication, storage, and battery life, fulfilling the functionality requirements of their supported applications is becoming increasingly challenging. Thus, it is not possible to implement all tasks on the IoT devices, especially those that need more powerful resources. Additionally, they add to the existing wireless network infrastructure burden with the large amount of data they generate. Tasks in IoTs vary depending of the requirements. Those requirements include real-time processing, low power consumption, high processing power, etc. From IoT perspective, each of the three paradigms (edge, fog, cloud) involves advantages and disadvantages. For instance, cloud is the most powerful resource to perform tasks in terms of processing, power and storage. However, for the real-time applications, it will not be a favorable choice. Hence, an intelligent adaptive scheduling scheme that takes the appropriate decision is essential. In this paper, a smart adaptive scheduling scheme for IoT environment has been proposed. The proposed scheme takes decision based on some factors that reflects the requirements. It calculates thresholds values which are adaptive to some factors. In this manner, the proposed adaptive system provides fast and proper workload assignment in IoT environment.