The Benagil team studies how to design more efficient and secure distributed systems by focusing on their core components (hypervisors, operating systems, runtime environments, data storage systems, and communication libraries). The team targets systems used in large-scale computing environments where efficiency and security are critical — such as large-scale distributed datastores, machine learning frameworks, data analytics platforms, and high-performance computing applications.

To improve the performance and security of these large-scale distributed systems, the Benagil team designs profiling and performance analysis techniques that scale with both the size of the system and the amount of data collected. Based on these analyses, the team enhances the efficiency and security of the core system components used in cloud infrastructures, especially the hypervisors and storage systems. The team also proposes new system mechanisms and interfaces for two emerging programming models: serverless computing and edge computing.

• Performance Analysis
  • Scalable tracing tools
  • Automatic detection of performance issues
• System Components for Cloud Computing
  • Virtualization systems
  • Storage systems
• System Components for Emerging Computing Models
  • Serverless computing
  • Edge computing