A deep neural network (DNN) has become increasingly popular in industrial Internet of
Things scenarios. Due to high demands on computational capability, it is hard for DNN …

Vehicular edge computing (VEC) is a promising paradigm to offload resource-intensive
tasks at the network edge. Owing to time-sensitive and computation-intensive vehicular …

Mobile platforms are rapidly and continuously changing, with support for new sensors, APIs,
and programming abstractions. Static analysis is gaining a growing interest, allowing …

Massive energy consumption data of buildings was generated with the development of
information technology, and the real-time energy consumption data was transmitted to …

Mobile edge computing (MEC) offers a promising technology that deploys computing
resources closer to mobile devices for improving performance. Most of the existing studies …

As vehicular applications continue to evolve, the computational capabilities of individual
vehicles alone are no longer sufficient to meet the increasing demands. This has led to the …

The high mobility and maneuverability of unmanned aerial vehicles (UAVs) enable them to
act as temporary base stations (BSs) in extreme environments, expanding the computing …

The explosive growth of the mobile application market in recent years has led to a large
concomitant mobile software industry whose components are, in many cases, startups and …

In this paper, we propose an Android-based distributed computing framework for
accelerating DNN inference on Android edge devices. We experimentally demonstrate that …

With the rapid improvement of software service in recent years, compute-intensive services
such as VR, AR, and face recognition have been developed drastically. It's hard for mobile …