An Incentive Mechanism in Mobile Crowdsourcing Based on Multi-Attribute Reverse Auctions.

Ying Hu,Yingjie Wang,Xiangrong Tong,Yingshu Li

doi:10.3390/s18103453

Abstract

In order to avoid malicious competition and select high quality crowd workers to improve the utility of crowdsourcing system, this paper proposes an incentive mechanism based on the combination of reverse auction and multi-attribute auction in mobile crowdsourcing. The proposed online incentive mechanism includes two algorithms. One is the crowd worker selection algorithm based on multi-attribute reverse auction that adopts dynamic threshold to make an online decision for whether accept a crowd worker according to its attributes. Another is the payment determination algorithm which determines payment for a crowd worker based on its reputation and quality of sensing data, that is, a crowd worker can get payment equal to the bidding price before performing task only if his reputation reaches good reputation threshold, otherwise he will get payment based on his data sensing quality. We prove that our proposed online incentive mechanism has the properties of computational efficiency, individual rationality, budget-balance, truthfulness and honesty. Through simulations, the efficiency of our proposed online incentive mechanism is verified which can improve the efficiency, adaptability and trust degree of the mobile crowdsourcing system.

Highlights

In recent years, the development of smart devices, has led to a new paradigm for data collection and problem solving
In order to verify the effectiveness of the multi-attribute reverse auction algorithm, we prove the efficiency of different algorithms for selecting crowd workers by calculating the increase speed in total payments paid to crowd workers
We design an online incentive mechanism based on multi-attribute reverse auction

Summary

Introduction

The development of smart devices (e.g., smart mobile phones, smart watches, etc.), has led to a new paradigm for data collection and problem solving. Data Corporation (IDC), the total number of smart mobile phone users in the world will amount to. 2.53 billion at the end of 2018, which accounts for about 36% of the global population. This indicates that there are a large number of potential participants for crowd-sensing applications. Along with smart devices’ users round-the-clock, these smart devices with powerful sensing capabilities can interact with the surrounding environment, so users with smart devices may collect sensing data for sensing tasks. The users with smart devices have the right to select the appropriate sensing task based on their locations, preferences and sensing capabilities

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