Secure and Cost-Efficient Task Assignment for Decentralized Mobile Crowdsensing: A Governance-Oriented Tiered Approach

Abstract

The blockchain-based Mobile Crowdsensing (MCS) system has emerged as a promising solution to achieve transparent and trustworthy task assignment, via on-chain smart contracts. It allows requesters to upload crowdsensing tasks to smart contracts, which then transparently assign tasks to different workers. Despite their trustworthiness, these blockchain-based contract-driven MCS systems still face: 1) considerable consensus latency, which is introduced by traditional blockchain systems; and 2) task assignment cost efficiency (e.g., travel distance) issues, which are limited by computational ability of smart contracts. To address these challenges, we introduce a governance-aware blockchain sharding system for MCS task assignment, called GOTTA. Specifically, GOTTA features two core components: 1) a reputation-based tiered sharding (RETIS) mechanism, and 2) ConsenFlow, a task assignment mechanism based on the Practical Byzantine Fault Tolerance consensus. RETIS addresses the consensus latency issues and the sharding-related security concerns for making final task assignment decisions. ConsenFlow is used to provide more cost-efficient MCS task assignment, and it alleviates the computational limit of smart contract–driven approaches. Theoretical analysis and designed extensive experiments confirm the effectiveness and efficiency of the proposed GOTTA, demonstrating the improvement in network throughput, system latency and cost efficiency compared with state-of-the-art solutions.