Hui Tian

TL;DR: A new user similarity model is presented to improve the recommendation performance when only few ratings are available to calculate the similarities for each user, which not only considers the local context information of user ratings, but also the global preference of user behavior.

TL;DR: This paper proposes a heuristic offloading decision algorithm (HODA), which is semidistributed and jointly optimizes the offload decision, and communication and computation resources to maximize system utility, a measure of quality of experience based on task completion time and energy consumption of a mobile device.

TL;DR: This paper forms the energy consumption minimization problem as a mixed interger nonlinear programming (MINLP) problem, which is subject to specific application latency constraints, and proposes a reformulation-linearization-technique-based Branch-and-Bound (RLTBB) method, which can obtain the optimal result or a suboptimal result by setting the solving accuracy.

TL;DR: This paper generates asymptotically optimal schedules tolerant to out-of-date network knowledge, thereby relieving stringent requirements on feedbacks and able to dramatically reduce feedbacks at no cost of optimality.

TL;DR: A new integration architecture of the cloud, MEC, and IoT is presented, and a lightweight request and admission framework is proposed to resolve the scalability problem and satisfy the latency requirements of different services and reduce the energy consumption of IoT devices.