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Optimal Incentive Design for Cloud-Enabled Multimedia Crowdsourcing

机译：基于云的多媒体众包的最佳激励设计

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摘要

Multimedia crowdsourcing possesses a huge potential to actualize many new applications that are expected to yield tremendous benefits in diverse fields including environment monitoring, emergency rescues during natural catastrophes, online education, sports, and entertainment. Nonetheless, multimedia crowdsourcing unfolds new challenges such as big data acquisition and processing, more stringent quality of service requirements, and heterogeneity of crowdsensors. Consequently, incentive mechanisms specifically tailored to multimedia crowdsourcing applications need to be developed to fully utilize the potential of multimedia crowdsourcing. In this paper, we design an optimal incentive mechanism for the smartphone contributors to participate in a cloud-enabled multimedia crowdsourcing scheme. We establish a condition that determines whether the smartphones are eligible to participate, and provide a close form expression for the optimal duration of service from the contributors, for a given reward from the crowdsourcer. Consequently, we derive the conditions for existence of an optimal reward for the contributors from the crowdsourcer, and prove its uniqueness. We numerically illustrate the performance of our model considering logarithmic and linear cost functions for the cloud resources. The similarity of the results for different cost models corroborates the validity of our model and the results, whereas the difference in the magnitudes suggests that the strategy of the crowdsourcer as well as the strategies of the smartphone participants considerably depend on the cloud cost model.
机译：多媒体众包具有实现许多新应用的巨大潜力，这些新应用有望在各个领域产生巨大的收益，包括环境监测，自然灾害期间的紧急救援，在线教育，体育和娱乐。尽管如此，多媒体众包仍面临着新的挑战，例如大数据采集和处理，更严格的服务质量要求以及人群传感器的异构性。因此，需要开发专门针对多媒体众包应用的激励机制，以充分利用多媒体众包的潜力。在本文中，我们为智能手机贡献者设计了一种最佳的激励机制，以使其参与支持云的多媒体众包计划。我们建立一个条件来确定智能手机是否有资格参与，并为来自众筹方的给定奖励，提供来自贡献者的最佳服务持续时间的简短表述。因此，我们从众包资源推导了贡献者获得最佳奖励的条件，并证明了其独特性。我们以数字方式说明了考虑对数和线性成本函数的云资源模型的性能。不同成本模型的结果相似性证实了我们的模型和结果的有效性，而幅度的差异表明，众包策略和智能手机参与者的策略在很大程度上取决于云成本模型。

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