Abstract
Crowdsourcing recruits workers to finish complicated tasks, but it is prone to the quality of service dilemma, that is, the platform cannot guarantee the workers’ quality of service. To solve this problem, we develop a novel quality of service improvement scheme. Firstly, to promote the workers cooperation, we propose an auction screening algorithm to estimate the rational quotation range of workers for screening workers and design a task reward function to motivate the workers to complete tasks. Secondly, to promote the platforms cooperation, we divide the rewards to the workers from the platforms into three categories and punish the platform that plays the defective strategy. Finally, the detailed experimental results show that the new scheme increases worker’s reward to complete tasks and relieves the quality of service dilemma in the crowdsourcing system effectively.
H. Xia—Supported by the National Natural Science Foundation of China (NSFC) under Grant No. 61872205, the Shandong Provincial Natural Science Foundation under Grant No. ZR2019MF018, and the Source Innovation Program of Qingdao under Grant No. 18-2-2-56-jch.
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Zhang, R., Xia, H., Cui, J., Cheng, X. (2020). A Novel Solution to Quality of Service Dilemma in Crowdsourcing Systems. In: Yu, D., Dressler, F., Yu, J. (eds) Wireless Algorithms, Systems, and Applications. WASA 2020. Lecture Notes in Computer Science(), vol 12385. Springer, Cham. https://doi.org/10.1007/978-3-030-59019-2_12
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DOI: https://doi.org/10.1007/978-3-030-59019-2_12
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