Blockchain-Based Mobile CrowdSensing system for Clearance Rate Maximization and Data Validity Preservation

Mobile CrowdSensing (MCS) has recently emerged as a powerful paradigm that capitalizes the power of crowd-sourcing for public sensing in a variety of domains. However, the quality of the collected data is not guaranteed, due to the heterogeneity of the devices used which increases the risk of noisy or malicious data. Also, the decentralized nature of MCS systems makes them susceptible to a single-node failure problems. Recently, the blockchain technology has become a viable paradigm that lends itself well to decentralization yet facilitates data verification. In this paper, we are concerned with the challenge of clearance rate (CR) maximization in blockchain-based MCS systems. CR is the percentage of tasks achieved during sensing campaigns. We present a blockchain-based MCS system designed to maximize CR through a three-stage reverse auction mechanism for participant-task matching. The system also addresses the interconnected challenges of low participant engagement, efficient task allocation, and data validity. Using extensive simulations, we compared the proposed framework to the recent literature, and we demonstrate higher effectiveness in terms of CR maximization and data validity preservation.