A Blockchain-Powered Crowdsourcing Method With Privacy Preservation in Mobile Environment

Crowdsourcing is a booming technique that enables participants to exchange data directly, thus making it possible to answer latency-sensitive service requests and relieve the burden of core networks. With some incentives, providers compete to furnish service requests, thus pledging the quality of experience (QoE) for requestors. However, the decentralized communication in crowdsourcing increases the probability of information tapering. Furthermore, providers' arbitrary selection of the requests poses great threat to the efficient and profitable service provision for the requestors. To deal with these challenges, we propose a blockchain-powered crowdsourcing method, named BPCM, while considering the privacy preservation in mobile environment. Specifically, a mobile crowdsourcing framework based on blockchain is designed first to preserve the privacy of the participants and keep the integrity of the service request and provision. Then, density-based spatial clustering of applications with noise (DBSCAN) and improved dynamic programming (IDP) are adopted to cluster the requestors and generate service strategies, respectively. Furthermore, simple additive weighting (SAW) and multiple criteria decision making (MCDM) are utilized to select the optimal strategy that achieves the tradeoffs among maximizing the service time, increasing the profits, and reducing the energy consumption for the providers. Finally, comprehensive experiments are conducted to verify the accuracy and effectiveness of BPCM.

I. Introduction

Crowdsourcing, as an efficient method in machine computation, provides such a scenario where the tasks are outsourced to the recruited human workers who regularly collect information, process data, and execute the transmitted tasks for requestors, thus increasing the service quality [1]–[4]. The crowdsourcing requestors usually divide the transmitted tasks into substantial atomic tasks which are offloaded to different providers to make the large tasks be executed as quickly as possible [5]. Each provider has to sacrifice battery capacity for the implementation of the transmitted tasks, thus generating energy consumption, and therefore, the requestors are obliged to compensate for the providers in forms of monetary rewards, reputation approval, and so forth [2]. Technically, instead of depending on specific networks, crowdsourcing is fertilized by device-to-device (D2D) communication in a great deal.