Double Auction-Based Dynamic Role Assignment Algorithm

With the increasing dynamics and task complexity of the Internet of Things (IoT) systems, task assignment optimization has become very difficult and device load imbalance is constantly increasing. Currently, no method exists that can dynamically assign tasks according to the changes in the IoT environment and promote collaborative optimization of IoT devices. The heterogeneity of task value depreciation and device collaboration have not been investigated in prior studies. To resolve these problems, this study proposes the double auction-based dynamic role assignment algorithm (DA-DRAA), which encourages more devices to participate in an IoT system and optimizes the combination between tasks and devices, thereby reducing the device load. The experimental results show that DA-DRAA has certain advantages in improving the efficiency of the system, indicating the effectiveness of our method.