Mobile crowdsourcing platform for intelligent car park systems

Viriyasitavat, Wantanee; Sangaroonsilp, Pattaraporn; Sumritkij, Jiranda; Tarananopas, Natnaree

doi:10.1109/icsec.2015.7401398

Cited by 3 publications

(1 citation statement)

References 3 publications

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“…Dietze et al 16 studied the prevalent malicious activity through crowdsourcing platforms based on the real data, and furthermore identified different types of workers for hosting the applications. Viriyasitavat et al 23 put the crowdsourcing into the research on Intelligent Transportation System (ITS), mainly for collecting and releasing data about the real‐time traffic conditions. Barron et al 24 developed a mobile crowdsourcing platform for urban infrastructure maintenance to monitor and assist coordinate the urban planning.…”

Section: Related Workmentioning

confidence: 99%

An incentive mechanism for crowdsourcing markets with social welfare maximization in cloud‐edge computing

Qing

Zhang

et al. 2018

Concurrency and Computation

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Crowdsourcing is emerging as a powerful paradigm that utilizes the distributed devices to sense, collect, and upload data to satisfy the requirements of the users. Currently, with the popularity of edge computing, edge device users can act as recruiters or participants to publish or perform crowdsourcing tasks and share feedback. However, due to the individual selfishness, it is still a challenge to maximize the social welfare distribution of all the participants and the recruiters for the crowdsourcing market. In view of this challenge, an incentive mechanism for the crowdsourcing market with social welfare maximization in the cloud-edge computing is designed in this paper. Technically, a double action model under the cloud-edge computing framework is proposed first, which aims to maximize the social welfare maximization and meanwhile meet the demands of incentive compatibility, individual rationality, market clearing, and budget constraint. Secondly, a corresponding incentive mechanism is designed based on the double auction model to achieve the market fairness. Experimental evaluation and comparison analysis are conducted to validate the efficiency and effectiveness of the mechanism.

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Section: Related Workmentioning

confidence: 99%