SOBER-MCS: Sociability-Oriented and Battery Efficient Recruitment for Mobile Crowd-Sensing
نویسندگان
چکیده
منابع مشابه
Mobile Crowd Sensing
People-centric sensing with smart phones can be used for large scale sensing of the physical world at low cost by leveraging the available sensors on the phones. Despite its benefits, mobile people-centric sensing has two main issues: (i) incentivizing the participants, and (ii) reliability of the sensed data. Unfortunately, the existing solutions to solve these issue either requires infrastruc...
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With the explosive popularization of the wireless mobile terminal devices, the combination of mobile sensing and crowdsourcing brings about a novel sensing paradigm of Internet of Things (IoT). By means of analyzing the data collected from mobile terminal, the crowd sensing can sense user’s situation intelligently and provide personalized service. It summarizes the latest researches both at hom...
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We investigate emerging mobile crowd sensing (MCS) systems, in which new cloud-based platforms sequentially allocate homogenous sensing jobs to dynamically-arriving users with uncertain service qualities. Given that human beings are selfish in nature, it is crucial yet challenging to design an efficient and truthful incentive mechanism to encourage users to participate. To address the challenge...
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Mobile Crowd Sensing (MCS) is a promising paradigm in which mobile users collect and share sensor data from their local environment using wireless mobile devices. The inherent openness of this platform and the selfishness of individuals make it easy to contribute low-quality sensor data, so the recruitment of suitable participants who are trustable and contribute high-quality sensor data, becom...
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ژورنال
عنوان ژورنال: Sensors
سال: 2018
ISSN: 1424-8220
DOI: 10.3390/s18051593