QoS-Aware Task Allocation and Scheduling in Three-Tier Cloud-Fog-IoT Architecture Using Double Auction

There is a lot of time-sensitive data provided by IoT applications that needs to be analysed. A Fog-Integrated Cloud Architecture is available to process these data. Due to the QoS requirements of IoT applications, the perishable nature of fog cloud resources, and the competition among users and service providers, task allocation in such an architecture is challenging. In this paper, we propose a competitive bidding (CompBid) strategy and a QoS-based task allocation and scheduling (QoTAS) algorithm using double auctions that aim to maximize user and service provider profit while also satisfying QoS requirements. A remote patient monitoring system is used to compare QoTAS performance to that of two previous studies, DPDA and MADA. In both the truthful and CompBid strategies, QoTAS achieves a higher task allocation ratio and resource utilization than DPDA and MADA. It has 89% more system utility than DPDA and 54% more user utility than MADA. Furthermore, the CompBid strategy increases QoTAS system utility by 25%.