Shiwen Mao

TL;DR: The background and state-of-the-art of big data are reviewed, including enterprise management, Internet of Things, online social networks, medial applications, collective intelligence, and smart grid, as well as related technologies.

TL;DR: In this article, a deep-learning-based indoor fingerprinting system using channel state information (CSI) is presented, which includes an offline training phase and an online localization phase.

TL;DR: This paper considers MEC for a representative mobile user in an ultradense sliced RAN, where multiple base stations are available to be selected for computation offloading and proposes a double deep ${Q}$ -network (DQN)-based strategic computation offload algorithm to learn the optimal policy without knowing a priori knowledge of network dynamics.

TL;DR: In this article, the authors utilized queuing theory to bring a thorough study on the energy consumption, execution delay, and payment cost of offloading processes in a fog computing system, where three queuing models were applied, respectively, to the MD, fog, and cloud centers, and the data rate and power consumption of the wireless link were explicitly considered.

TL;DR: In this paper, a fingerprinting system for indoor localization with calibrated channel state information (CSI) phase information is proposed, where a greedy learning algorithm is incorporated to train the weights layer-by-layer to reduce computational complexity.