Mobile crowdsourcing is an emerging crowdsourcing paradigm, which generates large-
scale sensing tasks and sensing data. One of the major issues in mobile crowdsourcing is …

With the development of Mobile Crowd Sensing Networks (MCSN), more and more Mobile
Crowdsourcing applications emerge. The mobile sensing technologies and theories have …

Conventional data collection methods that use Wireless Sensor Networks (WSNs) suffer
from disadvantages such as deployment location limitation, geographical distance, as well …

Widespread use of advanced mobile devices has led to the emergence of a new class of
crowdsourcing called spatial crowdsourcing. Spatial crowdsourcing advances the potential …

Mobile crowdsensing has been a promising and cost-effective sensing paradigm for the
Internet of Things by exploiting the proliferation and prevalence of sensor-rich mobile …

Existing studies on task recommendation in crowdsourcing systems provide additional
insights into the field from their perspectives, methodologies, frameworks, and disciplines …

Worker recruitment is an important problem in mobile crowdsourcing (MCS), which aims to
find sufficient and suitable participants to perform tasks. However, existing worker …

With the widespread prevalence of smart devices, mobile crowdsensing (MCS) becomes a
new trend to encourage mobile nodes to participate in cooperative data collection in various …

Task assignment is a fundamental problem in spatial crowdsourcing. Since workers and
tasks accept each other within a limited range, there are incomplete and tied preference lists …

Benefiting from unified sensors and long-term traffic engagement, for-hire vehicles (FHVs)
are widely considered the mainstay for vehicular crowd sensing (VCS) tasks. However …