Crowdsensing has received widespread attention in recent years. It is extensively employed
in smart cities and intelligent transportation systems. This paper comprehensively surveys …

Mobile network operators (MNOs) allocate computing and caching resources for mobile
users by deploying a central control system. Existing studies mainly use programming and …

Privacy-preserving online multi-task assignment is a crucial aspect of spatial crowdsensing
on untrusted platforms, where multiple real-time tasks are allocated to appropriate workers …

Due to the features of on-demand deployment and flexible observation, unmanned aerial
vehicles (UAVs) are promising for serving as the next-generation aerial sensors by using …

Attributable to the emergence of mobile edge computing (MEC), the hardware-constrained
industrial devices have further computational and service capability in industrial Internet of …

Due to the swift advancement of edge computing and mobile crowdsensing (MCS), edge-
assisted MCS (EAMCS) has emerged as a promising paradigm, leveraging sensor …

Recently, the metaverse has been a hot research topic that fuses multiple cutting-edge
techniques, including virtual reality (VR), augmented reality (AR), artificial intelligence (AI) …

The metaverse employs globally distributed computing and communication infrastructures to
construct an immersive digital world. Its continuous synchronization and hyperinteractivity …

With the rich sensing ability and extensive usage of various sensors, mobile crowdsensing
(MCS) has become a new paradigm to collect sensing data for various sensing applications …

Federated learning (FL) is a distributed machine learning paradigm that addresses the
challenges of privacy leakage and data silos by collaboratively training the global model …