16 citations · 19 across the 3 of their papers we have counts for
8 papers
Towards Cost-Optimal Policies for DAGs to Utilize IaaS Clouds with Online Learning
Xiaohu Wu, Han Yu, Giuliano Casale +1
Premier cloud service providers (CSPs) offer two types of purchase options, namely on-demand and spot instances, with time-varying features in availability and price. Users like st…
A Serverless Cloud-Fog Platform for DNN-Based Video Analytics with Incremental Learning
Huaizheng Zhang, Meng Shen, Yizheng Huang +4
DNN-based video analytics have empowered many new applications (e.g., automated retail). Meanwhile, the proliferation of fog devices provides developers with more design options to…
Distributed Energy Trading and Scheduling among Microgrids via Multiagent Reinforcement Learning
Guanyu Gao, Yonggang Wen, Xiaohu Wu +1
The development of renewable energy generation empowers microgrids to generate electricity to supply itself and to trade the surplus on energy markets. To minimize the overall cost…
Baconian: A Unified Open-source Framework for Model-Based Reinforcement Learning
Linsen Dong, Guanyu Gao, Xinyi Zhang +2
Model-Based Reinforcement Learning (MBRL) is one category of Reinforcement Learning (RL) algorithms which can improve sampling efficiency by modeling and approximating system dynam…
A Framework for Allocating Server Time to Spot and On-demand Services in Cloud Computing
Xiaohu Wu, Francesco De Pellegrini, Guanyu Gao +1
Cloud computing delivers value to users by facilitating their access to computing capacity in periods when their need arises. An approach is to provide both on-demand and spot serv…
Content-Aware Personalised Rate Adaptation for Adaptive Streaming via Deep Video Analysis
Guanyu Gao, Linsen Dong, Huaizheng Zhang +2
Adaptive bitrate (ABR) streaming is the de facto solution for achieving smooth viewing experiences under unstable network conditions. However, most of the existing rate adaptation…