With the rapid development of mobile crowdsensing applications, task allocation has
emerged as a new problem to be solved. Many task allocation strategies have been …

Anomaly detection on data collected by devices, such as sensors and IoT objects, is
inevitable for many critical systems, eg, an anomaly in the data of a patient's health …

Recently, to provide a low-latency mobile computing platform, Mobile Edge Computing
(MEC) is proposed. In this paper, we first summarized the feature capabilities of MEC, such …

Many mobile applications have been developed to apply deep learning for video analytics.
Although these advanced deep learning models can provide us with better results, they also …

Intelligent Video surveillance systems, leveraging edge computing, have become
increasingly prevalent in various facilities, providing advanced monitoring and management …

Deep Neural Network (DNN) is becoming adopted for video analytics on mobile devices. To
reduce the delay of running DNNs, many mobile devices are equipped with Neural …

The COVID-19 epidemic has made online video conferencing extremely popular throughout
the world, with many schools, companies and government sectors using video conferencing …

Edge-cloud collaborative video analytics is transforming the way data is being handled,
processed, and transmitted from the ever-growing number of surveillance cameras around …

This paper presents a game-theoretic scalable offloading system that provides seamless
video streaming services by effectively offloading parts of video traffic in all video streaming …

The pervasive application of Internet of Things (IoT) has pushed the proliferation of edge
computing. There exists potential in edge computing to satisfy the concerns of task delay …