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A location-constrained crowdsensing task allocation method for improving user satisfaction

Author

Listed:
  • Huihui Chen
  • Bin Guo
  • Zhiwen Yu
  • Liming Chen

Abstract

Mobile crowdsensing is a special data collection manner which collects data by smart phones taken by people every day. It is essential to pick suitable workers for different outdoor tasks. Constrained by participants’ locations and their daily travel rules, they are likely to accomplish light outdoor tasks by their way without extra detours. Previous researchers found that people prefer to accomplish a certain number of tasks at a time; thus, we focus on assigning light outdoor tasks to workers by considering two optimization objectives, including (1) maximizing the ratio of light tasks for different workers and (2) maximizing the worker’s satisfaction on assigned tasks. This task allocation problem is a non-deterministic polynomial-time-hard due to two reasons, that is, tasks and workers are many-to-many relationships and workers move from different places to different places. Considering both optimization objectives, we design the global-optimizing task allocation algorithm, which greedily selects the most appropriate participant until either no participant can be chosen or no tasks can be assigned. For the purpose of emulating real scenarios, different scales of maps, tasks, and workers are simulated to evaluate algorithms. Experimental results verify that the proposed global-optimizing method outperforms baselines on both maximization objectives.

Suggested Citation

  • Huihui Chen & Bin Guo & Zhiwen Yu & Liming Chen, 2019. "A location-constrained crowdsensing task allocation method for improving user satisfaction," International Journal of Distributed Sensor Networks, , vol. 15(10), pages 15501477198, October.
  • Handle: RePEc:sae:intdis:v:15:y:2019:i:10:p:1550147719883987
    DOI: 10.1177/1550147719883987
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    References listed on IDEAS

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    1. Rajagopal, 2014. "The Human Factors," Palgrave Macmillan Books, in: Architecting Enterprise, chapter 9, pages 225-249, Palgrave Macmillan.
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