Space-efficient B-tree Implementation for Memory-Constrained Flash Embedded Devices

TL;DR

This paper presents new B-tree variants optimized for memory-limited embedded devices, enabling efficient data indexing for IoT applications with significant performance improvements.

Contribution

It introduces and experimentally evaluates B-tree variants tailored for flash storage on resource-constrained embedded devices, filling a gap in existing hardware-dependent optimizations.

Findings

Small devices can efficiently perform B-tree indexing.

Storage-specific optimizations significantly improve performance.

Embedded B-tree variants outperform traditional implementations.

Abstract

Small devices collecting data for agricultural, environmental, and industrial monitoring enable Internet of Things (IoT) applications. Given their critical role in data collection, there is a need for optimizations to improve on-device data processing. Edge device computing allows processing of the data closer to where it is collected and reduces the amount of network transmissions. The B-tree has been optimized for flash storage on servers and solid-state drives, but these optimizations often require hardware and memory resources not available on embedded devices. The contribution of this work is the development and experimental evaluation of multiple variants for B-trees on memory-constrained embedded devices. Experimental results demonstrate that even the smallest devices can perform efficient B-tree indexing, and there is a significant performance advantage for using storage-specific optimizations.