Tiered Object Storage using Persistent Memory

TL;DR

This paper introduces a tiered object storage model leveraging persistent memory to selectively store object fields, significantly improving performance and reducing memory footprint in data-intensive applications.

Contribution

It proposes a novel tiered object storage approach with a linear-programming based optimization for field placement, enhancing efficiency over traditional storage methods.

Findings

Up to 50% improvement in execution time.

Reduced serialization/deserialization costs.

Lower memory footprint for object operations.

Abstract

Most data intensive applications often access only a few fields of the objects they are operating on. Since NVM provides fast, byte-addressable access to durable memory, it is possible to access various fields of an object stored in NVM directly without incurring any serialization and deserialization cost. This paper proposes a novel tiered object storage model that modifies a data structure such that only a chosen subset of fields of the data structure are stored in NVM, while the remaining fields are stored in a cheaper (and a traditional) storage layer such as HDDs/SSDs. We introduce a novel linear-programming based optimization framework for deciding the field placement. Our proof of concept demonstrates that a tiered object storage model improves the execution time of standard operations by up to 50\% by avoiding the cost of serialization/deserialization and by reducing the memory footprint of operations.