C
Cheng-Zhong Xu
Researcher at University of Macau
Publications - 595
Citations - 12239
Cheng-Zhong Xu is an academic researcher from University of Macau. The author has contributed to research in topics: Cloud computing & Computer science. The author has an hindex of 55, co-authored 525 publications receiving 9895 citations. Previous affiliations of Cheng-Zhong Xu include Claude Bernard University Lyon 1 & University of Oregon.
Papers
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Journal ArticleDOI
Performance and energy modeling for live migration of virtual machines
TL;DR: This work constructs application-oblivious models for the cost prediction by using learned knowledge about the workloads at the hypervisor (also called VMM) level and evaluates the models using five representative workloads on a Xen virtualized environment.
Book
Load Balancing in Parallel Computers: Theory and Practice
Cheng-Zhong Xu,Francis C. M. Lau +1 more
TL;DR: A survey of Nearest-Neighbor Load Balancing Algorithms and the GDE Method found that GDE on Tori and Meshes and the Diffusion Method were more correlated than previously thought.
Proceedings ArticleDOI
VCONF: a reinforcement learning approach to virtual machines auto-configuration
TL;DR: A reinforcement learning (RL) based approach, namely VCONF, to automate the VM configuration process, which employs model-based RL algorithms to address the scalability and adaptability issues in applying RL in systems management.
Proceedings ArticleDOI
Performance and energy modeling for live migration of virtual machines
TL;DR: This work constructs two application-oblivious models for the cost prediction by using learned knowledge about the workloads at the hypervisor (also called VMM) level and evaluates the models using five representative workloads on a Xen virtualized environment.
Journal ArticleDOI
An overview of energy efficiency techniques in cluster computing systems
Giorgio Luigi Valentini,Walter Lassonde,Samee U. Khan,Nasro Min-Allah,Sajjad A. Madani,Juan Li,Limin Zhang,Lizhe Wang,Nasir Ghani,Joanna Kolodziej,Hongxiang Li,Albert Y. Zomaya,Cheng-Zhong Xu,Pavan Balaji,Abhinav Vishnu,Fredric Pinel,Johnatan E. Pecero,Dzmitry Kliazovich,Pascal Bouvry +18 more
TL;DR: This survey focuses on the characteristic of two main power management technologies:static power management systems that utilize low-power components to save the energy, and dynamic power management techniques that utilize software and power-scalable components to optimize the energy consumption.