Today, cloud computation offloading may not be an appropriate solution for delay-sensitive
applications due to the long distance between end-devices and remote datacenters. In …

The advancements and progress in artificial intelligence (AI) and machine learning, and the
numerous availabilities of mobile devices and Internet technologies together with the …

Machine learning (ML) plays a key role in Intelligent Industrial Internet of Things (IIoT)
applications. Processing of the computation-intensive ML tasks can be largely enhanced by …

In order to meet people's demands for intelligent and user-friendly Internet of Things (IoT)
services, the amount of computation is increasing rapidly and the requirements of task delay …

In edge-enabled Internet of Things (IoT), Quality of Experience (QoE)-guaranteed offloading
decision is to decide which IoT tasks can be offloaded to edge servers with QoE guarantee …

Abstract In Mobile Edge Computing (MEC), offloading tasks from mobile devices to edge
servers may accelerate the processing speed and save the energy of the devices, hence …

Crowdsourcing enables a paradigm to conduct the manual annotation and the analytics by
those recruited workers, with their rewards relevant to the quality of the results. Existing …

Video, as a key driver in the global explosion of digital information, can create tremendous
benefits for human society. Governments and enterprises are deploying innumerable …

The existing research on dependent task offloading and resource allocation assumes that
edge servers can provide computational and communication resources free of charge. This …

Many crowdsourcing platforms are emerging, leveraging the resources of recruited workers
to execute various outsourcing tasks, mainly for those computing-intensive video analytics …