Online Task Allocation of Spatial Crowdsourcing Based on Dynamic Utility

YU Dunhui; ZHANG Lingli; FU Cong

doi:10.11999/JEIT170930

Volume 40 Issue 7

Jul. 2018

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YU Dunhui, ZHANG Lingli, FU Cong. Online Task Allocation of Spatial Crowdsourcing Based on Dynamic Utility[J]. Journal of Electronics & Information Technology, 2018, 40(7): 1699-1706. doi: 10.11999/JEIT170930

Citation:

YU Dunhui, ZHANG Lingli, FU Cong. Online Task Allocation of Spatial Crowdsourcing Based on Dynamic Utility[J]. Journal of Electronics & Information Technology, 2018, 40(7): 1699-1706. doi: 10.11999/JEIT170930

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Online Task Allocation of Spatial Crowdsourcing Based on Dynamic Utility

doi: 10.11999/JEIT170930

YU Dunhui ZHANG Lingli FU Cong

Funds:

The National Key Basic Research and Department Program of China (2014CB340404), The National Natural Science Foundation of China (61373037, 61672387)

Received Date: 2017-10-09
Rev Recd Date: 2018-04-08
Publish Date: 2018-07-19

Abstract

Abstract

In order to improve the overall effectiveness of the online assignment of crowdsourcing tasks, an online task assignment method is proposed for the space-time crowdsourcing environment. To deal with the problem of online task assignment in spatiotemporal crowdsourcing environment, a K-NearestNeighbor (KNN) algorithm is firstly proposed based on crowdsourcing task to select the candidate crowdsourcing workers. Then a threshold selection algorithm based on dynamic utility is designed to realize the optimal allocation of crowdsourcing workers and tasks. Experimental results show that the proposed algorithm is effective and feasible, and can guarantee the reliability of crowdsourcing workers and optimize the overall efficiency of the platform.
- Task assignment、Spatial crowdsourcing、K-NearestNeighbor (KNN) algorithm、Threshold selection algorithm,

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References(16)

References

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