Work

Efficient Cross-Rack Data Updates Based on Intelligent Dynamic Data Layout Using Machine-learning

Year: 2025

Type: conference-paper

Abstract: In large-scale storage systems, erasure-coded data updates often cause performance issues due to high inter-rack traffic. This paper introduces CRUD, an efficient method to reduce inter-rack traffic. CRUD uses combinatorial mathematics to create a pairwise balanced design (PBD), distributing stripes across racks to exploit data update locality. It applies a machine-learning model to classify data blocks into repeated and non-repeated updates. CRUD considers update categories, strategies, block numbers, and rack involvement to optimize stripe distribution, dynamically adjusting it to further reduce traffic. Experiments show CRUD cuts inter-rack traffic by up to 42.31% and saves 31.95% in update time compared to the best current method.

Source: International Conference on Computer Information and Big Data Applications (CIBDA)

DOI: 10.1145/3746709.3746795

Authors: Zengyuan Song, Bing Wei, Yao Song, Yi Wu

Institutions: Hainan University, China Academy of Information and Communications Technology

Language: English

Topic: Advanced Data Storage Technologies

Subfield: Computer Networks and Communications

Field: Computer Science

Domain: Physical Sciences

SDG: Industry, innovation and infrastructure

Open Access status: hybrid

OpenAlex ID: W4413812526

FWCI:

Cites: 15

Cited by:

Related to: 10