The Location-Based Service has been widely used for mobile communication networks and
location systems. However, privacy disclosure for incomplete collection location data in LBS …

Mobile crowdsensing is a new paradigm in which a requester can recruit a group of mobile
users via a platform and coordinate them to perform some sensing tasks by using their …

Cloud computing has revolutionized organizational operations by providing convenient, on-
demand access to resources. The emergence of the Internet of Things (IoT) has introduced a …

The low-tubal-rank tensors have been recently proposed to model real-world
multidimensional data. In this paper, we study the low-tubal-rank tensor completion problem …

Mobile crowd sensing (MCS) is a relatively new paradigm for collecting real-time and
location-dependent urban sensing data. Given its applications, it is crucial to optimize the …

The broad implementation of cloud computing have led to a dramatically growing in
exchanging and using data throughout multiple parties. The main problem restricting the …

The widespread availability of smartphones have enabled the blossom of Mobile Crowd
Sensing (MCS) projects, whose goal is to involve users in participatory tasks aimed at …

Privacy issues are strongly impeding the development of mobile crowd sensing (MCS)
applications. Under the current MCS framework, processes including bidding, task …

Mobile crowdsensing (MCS) has attained much attention for gathering distributed mobile
users to complete large-scale sensing tasks. To ensure the task completion, enough users …

Truth discovery techniques are commonly used in mobile crowd sensing (MCS) applications
to infer accurate aggregated results based on quality-aware data aggregation. However, the …