Distributed spatial crowdsourcing based task allocation in Ocean Internet of Things

In the current Ocean Internet of Things (OIoT), the data collected by underwater nodes need to be transmitted to the data center through the multi-hop path, which consumes a lot of resources. Based on our observations, there are a large number of ships with sufficient energy in OIoT; using these ships to transmit information will effectively save the energy of underwater nodes and improve transmission efficiency. However, how to transmit underwater node information to ships with different routes is a challenging issue. To address this problem, we propose a distributed spatial crowdsourcing task allocation scheme based on OIoT. In this scheme, the underwater nodes use the distributed spatial crowdsourcing method to assign tasks to ships in OIoT and use ships’ communication ability to transfer information to the data center. First, we propose a spatial crowdsourcing task allocation algorithm based on ship confidence (ShipCon-SCTA), in which underwater nodes are task publishers and ships are workers. It distinguishes the quality of the ship and preferentially selects high-quality ships to improve the stability of data transmission. Second, when no ship accepts the task, we use the ship and its adjacent nodes as the secondary task publisher. Third, due to the need for data aggregation, homomorphic encryption is used to ensure the task’s security. Finally, we use the ship’s actual position data to conduct simulation experiments. The experimental results show the scheme’s feasibility and effectiveness.