Task Allocation and Mobile Base Station Deployment in Wireless Powered Spatial Crowdsourcing

Yutao Jiao, Ping Wang, D. Niyato, Jun Zhao, B. Lin, Dong In Kim
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Abstract

Wireless power transfer (WPT) is a promising technology to prolong the lifetime of sensor and communication devices, i.e., workers, in completing crowdsourcing tasks by providing continuous and cost-effective energy supplies. In this paper, we propose a wireless powered spatial crowdsourcing (SC) framework which consists of two mutual dependent phases: task allocation phase and data crowdsourcing phase. In the task allocation phase, we propose a Stackelberg game based mechanism for the SC platform to efficiently allocate spatial tasks and wireless charging power to each worker. In the data crowdsourcing phase, the workers may have an incentive to misreport its real working location to improve its own utility, which manipulates the SC platform. To address this issue, we present a strategyproof deployment mechanism for the SC platform to deploy its mobile base station. We apply the Moulin’s generalized median mechanism and analyze the worst-case performance in maximizing the SC platform’s utility. Finally, numerical experiments reveal the effectiveness of the proposed framework in allocating tasks and charging power to workers while avoiding the dishonest worker’s manipulation.
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无线供电空间众包中的任务分配与移动基站部署
无线电力传输(WPT)是一种很有前途的技术,可以通过提供持续的、具有成本效益的能源供应来延长传感器和通信设备(即工人)完成众包任务的寿命。本文提出了一个无线供电空间众包(SC)框架,该框架包括两个相互依赖的阶段:任务分配阶段和数据众包阶段。在任务分配阶段,我们提出了一种基于Stackelberg博弈的SC平台有效分配空间任务和无线充电功率的机制。在数据众包阶段,工人可能有动机误报其实际工作地点,以提高其自身的效用,从而操纵SC平台。为了解决这个问题,我们提出了一种防策略部署机制,用于SC平台部署其移动基站。我们应用Moulin广义中值机制,分析了SC平台效用最大化的最坏情况。最后,数值实验表明,该框架在避免不诚实员工操纵的同时,有效地为员工分配任务和充电功率。
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