An Erasure-Coded Storage System for Edge Computing

Lixin Liang,Huan He,Qiuming Luo,Jian Zhao,Chengjian Liu,Xiaowen Chu

doi:10.1109/access.2020.2995973

Abstract

Emerging computing paradigm edge computing expects to store and process data at the network edge with reduced latency and improved network bandwidth. To the best of our knowledge, key performance issues such as coding performance of erasure-coded storage systems haven't been investigated for edge computing. In this paper, we present an erasure-coded storage system for edge computing. Unlike the data center and cloud storage systems, it employs edge devices to perform encoding and decoding operations, which can be a performance bottleneck of the whole storage system due to limited computing power. Hence, we present a comprehensive study of the performance of erasure coding to see if it can match the network performance of 5G and Wi-Fi 6 at the network edge. We use the popular edge device Jetson Nano and two state-of-the-art coding libraries: Jerasure and G-CRS. Our evaluation results reveal unsatisfied performance for Jerasure and high variance for G-CRS. To obtain better and stable performance, we accelerate erasure code with OpenMP on a multi-core CPU. Our work demonstrates our acceleration can bring stable performance and match the network bandwidth of 5G and Wi-Fi 6 for some commonly used cases. Besides, our work offers a better understanding of erasure-coded storage systems for edge computing and can be served as a reference to any further optimization for such kind of systems at the network edge.

Highlights

The proliferation of Internet of Things introduces the generation of zillions bytes of data by mobile and IoT devices [1]
We present an erasure-coded storage system for edge computing
Our work offers a better understanding of erasure-coded storage systems for edge computing and can be served as a reference to further optimization of such systems at the network edge

Summary

INTRODUCTION

The proliferation of Internet of Things introduces the generation of zillions bytes of data by mobile and IoT devices [1]. We can use Jerasure and G-CRS to represent the encoding and decoding performance of erasurecoded storage systems at the network edge. Our initial evaluation results demonstrate unsatisfied performance for Jerasure and high variance for G-CRS This motivates us to present a solution of parallel erasure coding on multi-core CPU with OpenMP. G-CRS suffers unstable performance even its average throughput can match the network bandwidth of 5G and Wi-Fi 6 This leaves the acceleration of erasure coding on multi-core CPU with OpenMP [16] to become a better choice for some cases. 2) We conduct extensive experiments to validate whether the performance of erasure coding can match the network bandwidth 5G and Wi-Fi 6 on edge device Jetson Nano with two state-of-art erasure coding libraries: Jerasure and G-CRS.

AND RELATED WORK

PERFORMANE EVALUATION

Findings

CONCLUSION