Cost-, Energy-, and Performance-Aware Cloud Optimization
Performance and Scalability of Distributed Applications
Distributed Databases and Data Management
Serverless and Data-Intensive Systems
The Cloud Optimization Working Group focuses on designing and deploying cloud, edge, and hybrid infrastructures that efficiently use compute, memory, storage, and network resources. We study resource placement, autoscaling, and dynamic management of applications, data streams, and distributed databases, emphasizing cost, energy, and performance trade-offs for data-intensive and real-time workloads. Our research spans distributed systems, real-time data processing, serverless computing, and geo-distributed databases, aiming to provide predictive and adaptive mechanisms for parallelism, data locality, and load balancing. We combine theoretical modelling, experimental evaluation on real cloud platforms, and collaborations with industry to produce open-source prototypes, reproducible benchmarks, and actionable guidelines.
