Dynamic Sensor Renting in RF-powered Crowdsensing Service Market with Blockchain
Shaohan Feng, Wenbo Wang, Dusit Tao Niyato, Dong In Kim, Ping Wang · 2019
Embedding sensors on wireless devices for collaborative environment sensing has been envisioned as a cost-effective solution for IoT applications. However, existing IoT platforms faces challenges, e.g., unsustainablility due to the limited on-device battery and tremendous cost of deploying middlewares for centralized task dispatching. In this paper, we employ wireless energy transfer and permissionless blockchains to construct a sustainable and decentralized IoT crowdsensing platform. Therein, IoT sensing cloud composed of multiple co-located sensors is wirelessly powered by RF-energy beacons for data sensing and transmission. The data is then forwarded to the blockchain for distributed data/transaction verification and trading. The data users access the crowdsensing service by renting sensors from the sensing clouds. Both the sensing clouds and data users are self-interested and aim to maximize their individual profits. The sensing clouds handle the interference of concurrent wireless transmissions and the on-chain transaction cost. Meanwhile, each user distributes its limited budget over the sensing clouds to optimize the service quality. We formulate a Stackelberg differential game to analyze the interaction among the sensing clouds and data users. Then, we investigate the Stackelberg equilibrium by capitalizing on Pontryagin's maximum principle. Furthermore, we provide a series of insightful numerical results about the Stackelberg equilibrium.