In our exploration of the vast landscape of big data, a major hurdle has come into sharp focus: our current systems aren’t quite up to the task of efficiently handling the massive influx of data. Networked systems, like Content Delivery Networks and Cloud services, offer potential solutions, but they don’t seamlessly fit modern applications.
In this talk, I’ll share our experiences in building networked systems for data-intensive communities, such as the High Energy Particle Physics Community at CERN. We will look at the problems these communities face and explore fundamental system design principles for addressing these big data challenges. Additionally, we’ll discuss the specific types of systems needed to tackle these issues effectively. Lastly, I’ll provide insights into future research in the ever-evolving landscape of big data and networked system design.
Susmit Shannigrahi is an assistant professor at Tennessee Tech, where he focuses on developing next-generation systems for data-intensive applications. He also serves as the director of the Next Generation Internet Research Lab at Tennessee Tech.
His current research projects include creating a peer-to-peer storage federation for handling large scientific datasets, improving networking for AR/VR, and designing a reliable file transfer protocol for big data. You can find more information about his work on his website: www.tntech-ngin.net.