Journal
IEEE TRANSACTIONS ON EMERGING TOPICS IN COMPUTING
Volume 7, Issue 1, Pages 174-186Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TETC.2016.2614383
Keywords
Spatial crowdsourcing; task assignment; reliability; budget; minimum cost
Funding
- National Natural Science Foundation of China [61502178, 61632013]
- Natural Science Foundation of Guangdong Province [2016A030313480]
- China Postdoctoral Science Foundation [2015M572318]
- Fundamental Research Funds for the Central Universities
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The large quantity of mobile devices equipped with various built-in sensors and the easy access to the high-speed wireless networks have made spatial crowdsourcing receive much attention in the research community recently. Generally, the objective of spatial crowdsourcing is to outsource location-based sensing tasks (e.g., traffic monitoring and pollution monitoring) to ordinary mobile workers (e.g., users carrying smartphones) efficiently. In this paper, we study a reliable task assignment problem for spatial crowdsourcing in a large worker market. Specifically, we use worker confidence to represent the reliability of successfully completing the assigned sensing tasks, and we formulate two optimization problems, maximum reliability assignment (MRA) under a recruitment budget and minimum cost assignment (MCA) under a task reliability requirement. We reveal the special structure properties of these problems, based on which we design effective approaches to assign tasks to the most suitable workers. The performances of the proposed algorithms are verified by theoretic analysis and experimental results on both real and synthetic datasets.
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