Priority-Aware Task Assignment in Opportunistic Network-Based Mobile Crowdsourcing

Mobile crowdsourcing technology is a special type of crowdsourcing that outsources location-based human tasks to workers with mobile devices. The user recruitment and task assignment strategies are critically important for successful mobile crowdsourcing. A number of task assignment algorithms for opportunistic network-based mobile crowdsourcing have been proposed for different design goals. However, none of them considers the priority of tasks. In this article, we introduce the priority-aware task assignment that maximizes the successful task rate of prioritized tasks by keeping with the overall makespan of the tasks as short as possible. To this end, the priority-aware offline task assignment (PFTA) and online task assignment (PNTA) are proposed. Since the task assignment problem is NP-hard, the proposed PFTA and PNTA rely on the greedy strategy based on the priority of tasks and/or the workload of tasks. In addition, the approximation ratio of PFTA and the competitive ratio of PNTA are analyzed. The performance of the proposed schemes are evaluated using real mobility traces, and the simulation results demonstrate that PFTA and PNTA achieve their design goals.