Abstract
With the rapid development of mobile devices, mobile crowdsourcing has become an important research focus. According to the task allocation, scholars have proposed many methods. However, few works discuss combining social networks and mobile crowdsourcing. To maximize the utilities of mobile crowdsourcing system, this paper proposes a task allocation model considering the attributes of social networks for mobile crowdsourcing system. Starting from the homogeneity of human beings, the relationship between friends in social networks is applied to mobile crowdsourcing system. A task allocation algorithm based on the friend relationships is proposed. The GeoHash coding mechanism is adopted in the process of calculating the strength of worker relationship, which effectively protects the location privacy of workers. Utilizing synthetic dataset and the real-world Yelp dataset, the performance of the proposed task allocation model was evaluated. Through comparison experiments, the effectiveness and applicability of the proposed allocation mechanism were verified.
Highlights
In recent years, a new framework has emerged, and mobile crowdsourcing has enable workers to perform spatiotemporal tasks
Starting from the homogeneity of human beings, the relationship between friends in social networks is applied to mobile crowdsourcing system
This paper proposes a friend-based task allocation model (FRS), which can maximize the utility of mobile crowdsourcing system
Summary
A new framework has emerged, and mobile crowdsourcing has enable workers to perform spatiotemporal tasks. For SAT mode, online workers will periodically report their location to the platform, so that the platform can allocate tasks to nearby workers to optimize the effectiveness of mobile crowdsourcing. Few research works [7,10,11,12,13] considered the relationship between friends when allocating task in mobile crowdsourcing. In SAT mode, the mobile crowdsourcing platform can allocate Task 5 to Worker A and Worker. The mobile crowdsourcing platform can allocate Task 1 to Workers A and B who have similar job skills. We research the relationships among friends in social networks and apply them to task allocation model in mobile crowdsourcing.
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