This paper provides a state-of-the-art literature review on economic analysis and pricing
models for data collection and wireless communication in Internet of Things (IoT). Wireless …

Participatory sensing is a powerful paradigm that takes advantage of smartphones to collect
and analyze data beyond the scale of what was previously possible. Given that participatory …

Federated learning (FL) rests on the notion of training a global model in a decentralized
manner. Under this setting, mobile devices perform computations on their local data before …

Vehicular fog computing (VFC) has emerged as a promising solution to relieve the overload
on the base station and reduce the processing delay during the peak time. The computation …

Device-to-device communication underlaying cellular networks allows mobile devices such
as smartphones and tablets to use the licensed spectrum allocated to cellular services for …

Device-to-device (D2D) communication is viewed as one promising technology for boosting
the capacity of wireless networks and the efficiency of resource management. D2D …

Mobile crowdsensing (MCS) is vulnerable to faked sensing attacks, as selfish smartphone
users sometimes provide faked sensing results to the MCS server to save their sensing costs …

An incentive mechanism is important for mobile crowdsensing to recruit sufficient
participants to complete large-scale sensing tasks with high quality. Previous incentive …

With the rich set of embedded sensors installed in smartphones and the large number of
mobile users, we witness the emergence of many innovative commercial mobile …

The mobile crowdsensing paradigm facilitates a broad range of emerging sensing
applications by leveraging ubiquitous mobile users to cooperatively perform certain sensing …