Ieee Access Special Section Editorial: Human-Driven Edge Computing

The advent of Fifth Generation (5G) and the Internet of Things (IoT) is expected not only to make it possible to collect and disseminate information for various crowd-sensing services in densely populated environments but also to put forward a higher request on these services with the rapid evolution of artificial intelligence and edge computing, which provides cloud computing and cache capabilities to reduce the computational load of cellular networks, displacing it at the edges of such networks. However, the costs for deployment and maintenance of mobile edge computing (MEC) are still high. Human-driven edge computing (HEC) is a novel model which integrates the elements of human, devices, internet and information, and combines the power of MEC architecture and the large-scale sensing ability of mobile crowd-sensing (MCS). Realizing better data spreading and environmental coverage in smart cities based on HEC has aroused a great deal of research interest from academia and industry. Although the studies of human-driven edge computing for 5G and the IoT are attractive, there are many open research problems, such as fusion analysis, efficient resource usage, low latency communication, large-scale search, and data security and privacy.