面向模糊逻辑控制的移动群智感知多任务分配

Multi-task Allocation Based on Fuzzy Logic Controlin Mobile Crowd Sensing

移动群智感知是一种新兴的感知范例,它采用参与者携带的移动设备感知实时信息.目前有关任务分配的大多数研究都缺乏计算实际参与者密度并对其进行详细分析的方法.在本文中,首先,基于参与者的出行时间和空间,采用模糊逻辑控制方法得到不同时空的参与者密度.另外,根据参与者密度,我们可以计算在特定时空下的任务所需要的有效样本数量.然后,本文通过考虑任务的属性和参与者方因素,可以获得所有任务的效用.最后,本文提出了一种全局贪婪算法来分配任务,以确保最大化所有任务的效用.仿真结果表明,在不同时空的任务数量、参与者数量以及参与者承载的最大工作负载的情况下,本文提出的全局贪婪算法在最大化所有任务的效用方面均优于其他基准算法.

Mobile crow d sensingis an emerging sensing paradigm thatemploys mobile devices carried by participants to sense real-time information.M ost of the previous studies on task allocation in practical applications lack thew ay of calculating real participant density and detailed analyzing of it.In thisw ork,at first,a fuzzy logic control method is employed to obtain the participantdensity in different time and space based on participants’travel time and space.Further,according to the participant density,w e can calculate the effective quantity of samples a task required in a specific time and space.Then,the utility of alltasks can be obtained by considering both the attributes of tasks and the participant-side factors.At last,a global greedy algorithm is proposed to maximize the utility of all tasks.The simulation results show thatthe proposed global greedy algorithm is superior to other baselines in terms ofthe utility of all tasks w ith the quantity of tasks,the quantity of participants,and the maximum w orkload carried by the participants in different time and space.