A5101587367- Cloud Computing and Resource Management
- Distributed and Parallel Computing Systems
- IoT and Edge/Fog Computing
- Image Processing and 3D Reconstruction
- Machine Learning and Data Classification
- Software System Performance and Reliability
- Blockchain Technology Applications and Security
- Parallel Computing and Optimization Techniques
- Caching and Content Delivery
- Advanced Data Storage Technologies
- Machine Learning in Materials Science
- Advanced Chemical Sensor Technologies
- Advanced Malware Detection Techniques
- Software Engineering Research
- Cybercrime and Law Enforcement Studies
- Software Testing and Debugging Techniques
- Spam and Phishing Detection
- Analytical Chemistry and Chromatography
- Neural Networks and Applications
Guilin University of Electronic Technology
2025
Huawei Technologies (China)
2020-2023
Sichuan University
2022
Westlake University
2022
The increasing popularity of cloud computing has forced providers to build economies scale meet the growing demand. Nowadays, data-centers include thousands physical machines, each hosting many virtual machines (VMs), which share main system resources, causing interference that can significantly impact on performance. Frequently, these run latency-critical workloads, whose performance is determined by tail latency, very sensitive co-running workloads. To prevent QoS violations, adopt...
Multithreaded latency-critical applications represent an important subset of workloads running on public cloud systems. Most these systems deploy powerful computing servers including Intel Hyper-Threading processors. Understanding how performance is affected by the consumption main system resources a major concern for providers in order to devise virtualization strategies that improve efficiency. With this aim, paper first characterizes impact QPS tail latency, analyzing different scenarios...
Cloud systems deploy a wide variety of shared resources and host large number tenant applications. To perform cloud research, small experimental platform is commonly used, which hides the huge system complexity provides flexibility. Despite being simpler, this should include main components (hardware software) to provide representative results. A set platforms have spread in recent years; however, most them only major component or lack deployment virtual machines (VMs) isolation. This paper...
Understanding inter-VM interference is of paramount importance to provide a sound knowledge and understand where performance degradation comes from in the current public cloud. With this aim, paper devises workload taxonomy that classifies applications according how major system resources affect their (e.g., tail latency) as function level load QPS). After that, we present three main studies addressing concerns improve cloud performance: impact on performance, hyper-threading limiting last...