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

TL;DR

This paper introduces a wireless powered spatial crowdsourcing framework with a game-theoretic task allocation and a strategyproof mobile base station deployment to enhance efficiency and prevent manipulation.

Contribution

It proposes a novel two-phase framework combining Stackelberg game for task and power allocation with a Moulin-based mechanism for truthful base station deployment.

Findings

Effective task and power allocation demonstrated through numerical experiments.

The deployment mechanism successfully prevents dishonest reporting by workers.

Framework improves overall utility and robustness in wireless powered spatial crowdsourcing.

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.