【摘要】 移动群智感知网络中用户的自私性和不确定性会造成用户参与感知活动的积极性不高及任务完成率较低等问题。针对此问题,提出了一种基于拍卖模型的激励机制。首先,以最大化用户效用为目标,在所提出的逆向拍卖机制(IMRA)中,以任务为中心进行赢标者选择且基于临界价格对赢标者进行报酬支付。然后,利用双向交互的激励机制(UBIM)使临时退出的用户可将未完成的任务转售给新用户,并提出基于二部图的用户匹配算法。实验结果表明,与TRAC、IMC-SS机制相比,所提的IMRA具有更高的用户平均效用和任务覆盖率,使用UBIM后也提高了任务完成率。更多还原

【Abstract】 The selfishness and uncertainty of user behaviors in the mobile crowd sensing network make them unwilling to participate in sensing activities, which may result to a lower sensing task completion rate. To deal with these problems, an incentive mechanism based on auction model was proposed. In order to maximize the utility of each user, the proposed incentive method based on reverse auction(IMRA) leveraged a task-centric method to choose winners, and payed them according to a critical-price strategy. Furthermore, the proposed user-bidirectional interaction incentive mechanism(UBIM) helped drop-out users(buyers) to transfer their unfinished tasks to new users. Simulation results show that, compared with TRAC and IMC-SS, IMRA can achieve a better performance in terms of average user utility and tasks coverage ratio, and the task completion ratio can also be improved by UBIM.更多还原