With the development of cloud computing, the coexistence of multiple cloud service
providers appears in the current cloud market. Due to heterogeneous instance types …

Mobile Crowdsensing (MCS), which assigns outsourced sensing tasks to volunteer workers,
has become an appealing paradigm to collaboratively collect data from surrounding …

Task allocation is a key problem in Mobile Crowd Sensing (MCS). Prior works have mainly
assumed that participants can complete tasks once they arrive at the location of tasks …

With the explosive popularity of mobile terminal devices, crowdsensing has become a novel
paradigm for thoroughly sensing the environment. A crucial issue in crowdsensing system …

Wireless sensor networks (WSNs) and mobile crowdsensing (MCS) are two important
paradigms in urban dynamic sensing. In both sensing paradigms, task allocation is a …

Because vehicles run in high speed environments, it is difficult to establish the topology of
the network. Moreover, data transmission may be interrupted by the handoff of various APs …

In the field of mobile crowd sensing (MCS), the traditional client–cloud architecture faces
increasing challenges in communication and computation overhead. To address these …

Mobile crowd sensing (MCS) is a new computing paradigm for the internet of things, and it is
widely accepted as a powerful means to achieve urban-scale sensing and data collection. In …

Emerging crowdsensing applications imposed a new barrier coverage problem called min–
max sink-based linear barrier coverage (min–max SLBC). In the problem, we are given a …

As an important application of wireless sensor networks (WSNs), deployment of mobile
sensors to periodically monitor (sweep cover) a set of points of interest (PoIs) arises in …