SeqCDC: Hashless Content-Defined Chunking for Data Deduplication

Data deduplication is critical to cloud storage providers and is widely employed to conserve server-side storage space. Data chunking is an important aspect of deduplication, being directly responsible for storage space savings and end-to-end system throughput. While deduplication systems deployed in production favor larger chunk sizes, existing data chunking algorithms are slow and offer minimal throughput increases with increasing chunk size.

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Publication Details

Published
2024-11-27
DOI
https://doi.org/10.1145/3652892.3700766
Citations
4
Primary Topic
Cloud Data Security Solutions
Type
article
Field-Weighted Citation Impact
3.12
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article

SeqCDC: Hashless Content-Defined Chunking for Data Deduplication

Sreeharsha Udayashankar, Samer Al-Kiswany, Abdelrahman Baba
4 citations
Cloud Data Security Solutions
3.12
article

SeqCDC: Hashless Content-Defined Chunking for Data Deduplication

Sreeharsha Udayashankar, Samer Al-Kiswany, Abdelrahman Baba
article en
4 citations

Abstract

Data deduplication is critical to cloud storage providers and is widely employed to conserve server-side storage space. Data chunking is an important aspect of deduplication, being directly responsible for storage space savings and end-to-end system throughput. While deduplication systems deployed in production favor larger chunk sizes, existing data chunking algorithms are slow and offer minimal throughput increases with increasing chunk size.

University of Waterloo (CA)
Openalex Percentile: Top 7%
Cloud Data Security Solutions
3.12
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SeqCDC: Hashless Content-Defined Chunking for Data Deduplication — Sreeharsha Udayashankar, Samer Al-Kiswany, et al. · (2024) | TGRS Research Map | TGRS