Blockchain-empowered multi-skilled crowdsourcing for mobile web 3.0

As the next generation of the world wide web, web 3.0 is envisioned as a decentralized internet which improves data security and self-sovereign identity. The mobile web 3.0 mainly focuses on decentralized internet for mobile users and mobile applications. With the rapid development of mobile crowdsourcing research, existing mobile crowdsourcing models can achieve efficient allocation of tasks and responders. Benefiting from the inherent decentralization and immutability, more and more crowdsourcing models over mobile web 3.0 have been deployed on blockchain systems to enhance data verifiability. However, executing these crowdsourcingoriented smart contracts on a blockchain may incur a large amount of gas consumption, leading to significant costs for the system and increasing users' expenses. In addition, the existing crowdsourcing model does not take into account the expected quality of task completion in the matching link between tasks and responders, which will cause some tasks to fail to achieve effects and damage the interests of task publishers. In order to solve these problems, this paper proposes a decentralized multi-skill mobile crowdsourcing model with guaranteed task quality and gas optimization (DMCQG), which performs task matching while considering skill coverage and expected quality of task completion, and guarantees the final completion quality of each task. In addition, DMCQG also optimizes the gas value consumed by smart contracts at the code level, reducing the cost of crowdsourcing task participation. In order to verify whether DMCQG is effective, we deployed the model on the Ethereum platform for testing. Through inspection, it was proved that the final expected quality of the tasks matched by DMCQG was better than other models. And it is verified that after optimization, the gas consumption of DMCQG is significantly reduced.