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The Internet of Things (IoT) can be conveniently deployed while empoweringvarious applications, where the IoT nodes can form clusters to finish certainmissions collectively. In this paper, we propose to employ unmanned aerialvehicles (UAVs) to assist the clustered IoT data collection withblockchain-based security provisioning. In particular, the UAVs generatecandidate blocks based on the collected data, which are then audited through alightweight proof-of-stake consensus mechanism within the UAV-based blockchainnetwork. To motivate efficient blockchain while reducing the operational cost,a stake pool is constructed at the active UAV while encouraging stakeinvestment from other UAVs with profit sharing. The problem is formulated tomaximize the overall profit through the blockchain system in unit time byjointly investigating the IoT transmission, incentives through investment andprofit sharing, and UAV deployment strategies. Then, the problem is solved in adistributed manner while being decoupled into two layers. The inner layerincorporates IoT transmission and incentive design, which are tackled withlarge-system approximation and one-leader-multi-follower Stackelberg gameanalysis, respectively. The outer layer for UAV deployment is undertaken with amulti-agent deep deterministic policy gradient approach. Results show theconvergence of the proposed learning process and the UAV deployment, and alsodemonstrated is the performance superiority of our proposal as compared withthe baselines.

Incentivizing Proof-of-Stake Blockchain for Secured Data Collection in UAV-Assisted IoT: A Multi-Agent Reinforcement Learning Approach