Roadside traffic monitoring is increasingly performed by deploying roadside high-resolution
video cameras and then running computer vision (CV) models on the video data. Since …

Mobile video analytics applications, such as smart driving, VR/AR, and video surveillance,
have become increasingly popular due to the proliferation of mobile devices. These …

The success of IoT applications increases the number of online devices and motivates the
adoption of a fog computing paradigm to support large and widely distributed infrastructures …

Mobile edge computing has emerged as a promising paradigm to reduce the latency of
novel computation-intensive and latency-critical application applications. Considering the …

With current and future mobile applications (eg, healthcare, connected vehicles, and smart
grids) becoming increasingly compute-intensive for many mission-critical use cases, the …

Streaming applications have become widespread with the advent of big data and IoT. They
are latency-sensitive applications that aim to process vast amounts of data in near real time …

Roadside traffic monitoring is increasingly performed by deploying roadside high-resolution
video cameras and then running Computer Vision (CV) models on the video data. Since …

Machine learning is becoming an increasingly integral component of mobile applications.
However, the execution of compute-heavy neural models (eg, for computer vision tasks) on …

Internet-of-Things (IoT) big data streaming applications, such as video surveillance and
automatic driving, tend to use mobile-edge computing (MEC) infrastructure to enhance their …

IoT application development usually involves separate programming at the device side and
server side. While separate programming style is sufficient for many simple applications, it is …