With the rapid development of the Internet of Things (IoT) applications and services, the need for high Quality of Service (QoS) and computation power has been dramatically increased. In order to meet these needs, a promising computing system based on the integration of fog and cloud computing has been recently introduced. However, this system is still in its infancy and it is associated with many challenging issues. Task scheduling problem is one of the most important ones in this context. Motivated by this, in this paper, we propose a real-time randomized algorithm to address this problem in the large-scale fog-cloud computing systems. The proposed algorithm uses the Power of Two Choices (Po2C) approach to maximize QoS while minimizing monetary cost. The efficiency of the proposed Po2C is evaluated using extensive experiments. The results demonstrate that the proposed algorithm significantly outperforms the baseline scheduling strategies. Specifically, our algorithm improves the deadline violation cost by up to 58% in comparison with the Round Robin strategy
