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Wireless Communications and Mobile Computing | Vol.16, Issue.15 | | Pages 2193-2179

Wireless Communications and Mobile Computing

CAPR: context-aware participant recruitment mechanism in mobile crowdsourcing

Hongli Zhang   Xiaojiang Du   Jiantao Shi   Zhikai Xu   Zhigang Zhou  
Abstract

With the advances of sensing, wireless communication, and mobile computing, mobile crowdsourcing has become a new paradigm for data collection and retrieval that has attracted considerable attention. This paper addresses the fundamental research issue in mobile crowdsourcing: Which participants should be selected as winners in each time slot with the aim of maximizing the total utility of the service provider in the long term? First, a double-sided combinatorial auction model is introduced to describe the relationships between the mobile users and requesters from the perspective of supply and demand at a given time. Then, the coupling between the utility values of the system in different time slots is investigated. Based on the aforementioned analyses, this paper proposes a context-aware participant recruitment mechanism, in which the mobile crowdsourcing system dynamically adjusts the participant recruitment mechanism depending on the ratio between the numbers of mobile users and requesters. Context-aware participant recruitment consists of two main components: (1) a heuristic algorithm based on the greedy strategy to determine the winning participants and (2) a critical payment scheme, which guarantees the rationality of the proposed mechanism. Finally, extensive simulations demonstrate that the proposed mechanism achieves high system utility in the long term. Copyright © 2016 John Wiley & Sons, Ltd. This paper addressed the participant recruiment problem in mobile crowdsoucing. We first introduce a double-sided combinatorial auction model to describe the interactions between the requesters and mobile users from the perspective of supply and demand. Then we propose a context-aware participant recruitment mechanism in which the SP dynamically adjust the recruitment mechanism depending on the ratio between the requesters and mobile users.

Original Text (This is the original text for your reference.)

CAPR: context-aware participant recruitment mechanism in mobile crowdsourcing

With the advances of sensing, wireless communication, and mobile computing, mobile crowdsourcing has become a new paradigm for data collection and retrieval that has attracted considerable attention. This paper addresses the fundamental research issue in mobile crowdsourcing: Which participants should be selected as winners in each time slot with the aim of maximizing the total utility of the service provider in the long term? First, a double-sided combinatorial auction model is introduced to describe the relationships between the mobile users and requesters from the perspective of supply and demand at a given time. Then, the coupling between the utility values of the system in different time slots is investigated. Based on the aforementioned analyses, this paper proposes a context-aware participant recruitment mechanism, in which the mobile crowdsourcing system dynamically adjusts the participant recruitment mechanism depending on the ratio between the numbers of mobile users and requesters. Context-aware participant recruitment consists of two main components: (1) a heuristic algorithm based on the greedy strategy to determine the winning participants and (2) a critical payment scheme, which guarantees the rationality of the proposed mechanism. Finally, extensive simulations demonstrate that the proposed mechanism achieves high system utility in the long term. Copyright © 2016 John Wiley & Sons, Ltd. This paper addressed the participant recruiment problem in mobile crowdsoucing. We first introduce a double-sided combinatorial auction model to describe the interactions between the requesters and mobile users from the perspective of supply and demand. Then we propose a context-aware participant recruitment mechanism in which the SP dynamically adjust the recruitment mechanism depending on the ratio between the requesters and mobile users.

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Hongli Zhang, Xiaojiang Du, Jiantao Shi, Zhikai Xu, Zhigang Zhou,.CAPR: context-aware participant recruitment mechanism in mobile crowdsourcing. 16 (15),2193-2179.

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