CAREER: Datacenter-Aware Local Storage Stacks

University Of Illinois At Urbana-Champaign, Urbana IL

Investigators

Abstract

We are generating data at unprecedented rates, and the bulk of this data is stored in datacenters today. However, the storage-stack infrastructure that underpins current datacenter storage services was designed in the pre-datacenter era, primarily for desktop and on-premise computers. When used as-is in datacenter systems, this storage stack incurs unnecessary performance overhead, poorly utilizes resources, and hampers sustainability objectives. Consequently, this results in elevated costs for millions of users relying on datacenter storage. This project aims to design and develop local storage stacks specifically tailored for datacenters to enhance performance, optimize resource utilization, and contribute positively to sustainability goals. The key technical approach is to ingrain datacenter-awareness into the local storage stack – in particular, the fact that datacenter systems are designed with inherent redundancy to tolerate failures. This project takes a broad view and identifies four fundamental pillars of storage stacks: performance, crash safety, efficiency, and data integrity. In four synergistic research thrusts, we will redesign and optimize the mechanisms underlying the above pillars by exploiting the inherent redundancy. This project will contribute novel techniques, system designs, protocols, and practical implementations to realize the vision of datacenter-aware storage stacks. This project also places significant emphasis on education by (i) designing new courses on storage/datacenter distributed systems, (ii) training student researchers to work on both storage hardware and software to build efficient datacenter storage and, eventually, apply the principles to other future domains, (iii) developing a "pocket" cluster educational kit to offer real systems building experience to K-12 students. This project will make all artifacts publicly available, including publications, data sets, code, and instructions to run experiments. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.