Cloud Cost Optimizer

The goal of this project is to design and implement a scalable multi-cloud cost optimizer capable of calculating the best scheme for deploying a given arbitrary complex workload over a public (hybrid) cloud, thus reducing the involved monetary costs. As an input, the...

Characterizing and optimizing reactive systems, a continuum language-runtime

This research project was kicked off by a paper we published in REBLS 2021. This paper aimed at comparing the costs and benefits of three different reactive streams libraries for Java: do mature and complex libraries implementing involved optimizations perform better than newer libraries sacrificing such optimizations for a simpler codebase?

Enabling Intelligent In-Network Computing for Cloud Systems

With the network infrastructure becoming highly programmable, it is time to rethink the role of networks in the cloud computing landscape beyond just packet delivery. The network itself emerges as a computing platform with a unique advantage of full network...

Intelligent Data Synchronization for Hybrid Clouds

The goal of this project is to design configurable synchronization solutions on a common platform for a wide range of edge computing scenarios relevant to Red Hat. These solutions will be thoroughly validated on a state-of-the-art testbed capable of emulating realistic environments (e.g., smart cities).

PHYSICS: oPtimized HYbrid Space-time servIce Continuum in faaS

Join Red Hat Research for the next Research Days event, “PHYSICS EU Project: Advancing FaaS applications in the cloud continuum,” on November 16, 2022, from 3PM to 4:30PM CET (4PM IST, 9AM EST).  PHYSICS is a high technology European research...