CAPR: context‐aware participant recruitment mechanism in mobile crowdsourcing
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.
Document Details
- Document Type
- Pub Defense Publication
- Publication Date
- May 16, 2016
- Source ID
- 10.1002/wcm.2675
Entities
People
- Hongli Zhang
- Jiantao Shi
- Xiaojiang Du
- Zhigang Zhou
- Zhikai Xu
Organizations
- Army Research Office
- Harbin Institute of Technology
- National Natural Science Foundation of China
- National Science Foundation
- Program 973
- Temple University