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Worker Selection for Reliably Crowdsourcing Location-Dependent Tasks

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Part of the Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering book series (LNICST,volume 162)

Abstract

Obtaining accurate information about specific locations is of great importance to today’s many crowdsourced smartphone applications. To verify information about a location, smartphone users are selected to go to the location and answer a yes/no question about the location. Our research focuses on the location-aware worker selection problem, which is the problem of selecting a group of workers who, together, can give the most accurate answer to the location-based question. We define the location-aware worker selection problem, mathematically formulate it, and then show that an optimal solution is exponential in time complexity. We present our heuristic solutions that take into account both the reliability of the users and the level of convenience for each user to complete the task. We evaluate and compare our approaches to three other heuristic algorithms via simulation.

Keywords

  • Crowdsourcing
  • Mobile sensing
  • Worker selection

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  • DOI: 10.1007/978-3-319-29003-4_5
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Correspondence to Kevin Emery .

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© 2015 Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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Emery, K., Sallee, T., Han, Q. (2015). Worker Selection for Reliably Crowdsourcing Location-Dependent Tasks. In: Sigg, S., Nurmi, P., Salim, F. (eds) Mobile Computing, Applications, and Services. MobiCASE 2015. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 162. Springer, Cham. https://doi.org/10.1007/978-3-319-29003-4_5

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  • DOI: https://doi.org/10.1007/978-3-319-29003-4_5

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-29002-7

  • Online ISBN: 978-3-319-29003-4

  • eBook Packages: Computer ScienceComputer Science (R0)