Yun Luo

TL;DR: A system model and dynamic schedules of data/control-constrained computing tasks are investigated, including the execution time and energy consumption for mobile devices, and NSGA-III (non-dominated sorting genetic algorithm III) is employed to address the multi-objective optimization problem of task offloading in cloud-edge computing.

TL;DR: A multiobjective computation offloading method, named MCO, is proposed to address the above challenge and is designed to achieve the goal of energy saving for all the mobile device while satisfying the deadline constraints of the workflows.

TL;DR: A machine learning model is deployed to predict tweet sentiment, as well as gain an insight into the correlation between twitter sentiment and stock prices, to evaluate the direct correlation between tweet sentiments and stock market prices.

TL;DR: Density biased sampling for outlier detection is formally investigated, a novel density biased sampling approach is proposed, and Locality Sensitive Hashing is used for counting the nearest neighbours of a point to attain scalable density estimation.

TL;DR: This paper formally analyse the vulnerability of the solution based on symmetric encryption scheme, and proposes a new scheme based on the decisional Diffie‐Hellman assumption that can be much more efficient and be approximately 8000 times faster than the solution for a 32‐bit input and short‐term security.