Security, Cost and Energy Aware Scheduling of Real-Time IoT Workflows in a Mist Computing Environment

The rapid expansion of the Internet of Things (IoT) led to the emergence of new computing paradigms, such as mist and fog computing, in order to tackle the problem of transferring vast volumes of data to remote cloud data centers. In this paper, we propose a security, cost and energy aware scheduling heuristic for real-time workflow jobs that process IoT data with various security requirements. The environment under study is a four-tier architecture, consisting of IoT, mist, fog and cloud layers. The resources in the mist, fog and cloud tiers are considered to be heterogeneous. The proposed scheduling approach is compared to a baseline strategy, which is security aware, but not cost and energy aware. The performance of both heuristics is evaluated through extensive simulation experiments, under different values of security level probabilities for the initial IoT input data of the entry tasks of the workflow jobs. The simulation results reveal that the proposed approach, not only provides a better Quality of Service (QoS) compared to the baseline strategy, but it also achieves monetary cost and energy savings.