Task Allocation With Unmanned Surface Vehicles in Smart Ocean IoT

The unmanned surface vehicles (USVs) have been regarded as a promising paradigm to automatically perform emergency tasks in a dynamic maritime traffic environment. However, the performance of maritime communication between USVs and offshore platforms becomes a critical challenge, and the efficiency of task allocation for USVs in the smart ocean is low. In this article, a novel task allocation scheme for USVs in the smart ocean Internet of Things (IoT) is proposed to improve the efficiency of task allocation. First, the offshore platform is developed to provide maritime communication for USVs in the smart ocean IoT. Second, the network resource allocation process between USVs and offshore platforms is modeled as the second price sealed auction game, where the optimal bidding strategy of USV is derived by the Q-learning to maximize the utilities of USVs and offshore platforms. Third, the task allocation scheme is proposed to improve the number of allocated tasks. Finally, the performance of the proposed scheme is conducted based on extensive simulations. The simulation results show that the proposed scheme can significantly improve the number of allocated tasks compared with the conventional schemes.