A mobile crowdsensing task allocation method in the scenario of environmental protection
Xiaohui Han, Yanran Li, Shuyu Li · 2023
In mobile crowdsensing (MCS) environment, total carbon emission based on various travel mode is an important factor that affects the design of incentive mechanism. Aiming at the goal of maximizing task complete rate and minimizing total carbon emission, a task allocation method named TAEP is proposed in the paper. The proposed method contains two stages: preliminary participant selection stage and task allocation stage. In the first phase, based on the joint probability of task acceptance rate and experience of participants, a rough participant selection algorithm is designed to maximize task completion rate. Besides, geographical indistinguishability is adopted to protect participants’ location privacy. In the second phase, a task allocation algorithm based on dynamic programming is given according to the result of the first stage. Candidate participants who can minimize carbon emission within the budget limit are selected as winners. Experimental results on real dataset validate the effectiveness of the proposed method.