Collaborative Research: CNS CORE: Medium: The Case for Blended Storage

In recent years, data storage technology has been designed for one of two objectives: either improved performance or a lower cost per bit. Consequently, significant effort has gone into building new storage systems that are organized either to be very fast (but expensive) or very cheap (but slow). This proposal takes a different approach: it makes the case for blended storage systems, i.e., software systems that combine multiple different storage technologies, to achieve both high performance and low cost per bit.

Widely-used storage data structures and algorithms are designed for a single storage medium in mind, which leads to poor performance when they are run on multiple different storage technologies with different characteristics. Therefore, the proposal rethinks the fundamental data structures and algorithms that underpin modern storage systems for blended storage, including: indexing, data placement, logging, caching, prefetching and approximate membership structures. The proposal will design and implement these data structures and algorithms in a prototype key-value store that is designed specifically for blended storage.

The proposed research will redesign widely-used data structures and algorithms for key-value stores to take advantage of blended storage technologies for fast data access at a low cost. Since key-value stores underpin many cloud data systems, the immediate benefits will include high performing data systems at a reduced cost. These will in turn translate to cost-effective cloud services for end users. The PIs will release the software artifacts under open-source licenses to enable other researchers and will work with hardware and cloud providers to transition the research into practice. The education plan will elevate storage-centric systems design as an integral part of systems education.

The project repository will be hosted on Github at https://github.com/princeton-sns and maintained indefinitely.

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.