An efficient pricing strategy of sensing tasks for crowdphotographing

The advancement of mobile Internet and ubiquitous computing is facilitating various crowdsourcing services in which individuals or organizations obtain goods and services with less time and monetary cost. Recently, crowdphotographing, an emerging self-service mode over the mobile Internet, is to recruit several users to take the pictures via incentive mechanism. Mobile users can earn the money by executing their requested sensing tasks. Thus, how to make an efficient pricing strategy is becoming a challenge issue in crowdphotographing. To this end, this paper mainly investigates the rationality and optimization of task pricing for crowdphotographing. First, we analyze the correlation among tasks pricing, location of members, and tasks. Then, a multivariable linear regression model is adopted for determining the task pricing strategy. Further, an improved pricing model is devised by considering the package of several tasks that can be packaged in terms of their locations distribution.

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