0000000000638172

AUTHOR

Francesco Restuccia

FIRST

Thanks to the collective action of participating smartphone users, mobile crowdsensing allows data collection at a scale and pace that was once impossible. The biggest challenge to overcome in mobile crowdsensing is that participants may exhibit malicious or unreliable behavior, thus compromising the accuracy of the data collection process. Therefore, it becomes imperative to design algorithms to accurately classify between reliable and unreliable sensing reports. To address this crucial issue, we propose a novel Framework for optimizing Information Reliability in Smartphone-based participaTory sensing (FIRST) that leverages mobile trusted participants (MTPs) to securely assess the reliabil…

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SDR-LoRa

In this paper, we present SDR-LoRa, a full-fledged SDR implementation of a LoRa transmitter and receiver. First, we reverse-engineer the LoRa physical layer (PHY) functionalities, including the procedures of packet modulation, demodulation, and preamble detection. Based on this analysis, we develop the first Software Defined Radio (SDR) implementation of the LoRa PHY. Furthermore, we integrate LoRa with an Automatic Repeat Request (ARQ) error detection protocol. SDR-LoRa has been validated on (i) the Colosseum wireless channel emulator; and (ii) a real testbed with USRP radios and commercial-off-the-shelf (COTS) devices. Our experimental results demonstrate that the performance of SDR-LoRa …

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IncentMe: Effective Mechanism Design to Stimulate Crowdsensing Participants with Uncertain Mobility

Mobile crowdsensing harnesses the sensing power of modern smartphones to collect and analyze data beyond the scale of what was previously possible with traditional sensor networks. Given the participatory nature of mobile crowdsensing, it is imperative to incentivize mobile users to provide sensing services in a timely and reliable manner. Most importantly, given sensed information is often valid for a limited period of time, the capability of smartphone users to execute sensing tasks largely depends on their mobility pattern, which is often uncertain. For this reason, in this paper, we propose IncentMe, a framework that solves this core issue by leveraging game-theoretical reverse auction …

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