Hekate a tool for gauging Data Deduplication Performance

Lars Nielsen; Daniel Enrique Lucani Rötter

doi:10.1109/SmartCloud52277.2021.00019

Hekate a tool for gauging Data Deduplication Performance

Lars Nielsen, Daniel Enrique Lucani Rötter

Publikation: Bidrag til bog/antologi/rapport/proceeding › Konferencebidrag i proceedings › Forskning › peer review

2 Citationer (Scopus)

Abstract

In this paper, we introduce HEKATE a tool for gauging the performance of data deduplication. In particular, HEKATE allows to test classic, chunk-based deduplication as well as the emerging concept of generalized deduplication, which leverages different data transformations prior to deduplication. We show that HEKATE can be used to evaluate performance with different system configurations and deduplication schemes. In fact, we use six real-world data sets to showcase HEKATE ’s
ability to test performance over a wide range of conditions. We also use this evaluation to showcase how HEKATE can provide insights into data deduplication performance in real systems and optimal configurations given specific data characteristics of an expected workload. HEKATE can also be used to determine the suitability of various deduplication approaches for each data set.

Originalsprog	Engelsk
Titel	Proceedings - 2021 IEEE 6th International Conference on Smart Cloud, SmartCloud 2021
Antal sider	6
Forlag	IEEE
Publikationsdato	2021
Sider	67-72
ISBN (Elektronisk)	978-1-6654-4374-6
DOI	https://doi.org/10.1109/SmartCloud52277.2021.00019
Status	Udgivet - 2021

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Scale-loT
Lucani Rötter, D. E. (Deltager)
01/01/2018 → 31/12/2022
Projekter: Projekt › Forskning

Citationsformater

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title = "Hekate a tool for gauging Data Deduplication Performance",

abstract = "In this paper, we introduce HEKATE a tool for gauging the performance of data deduplication. In particular, HEKATE allows to test classic, chunk-based deduplication as well as the emerging concept of generalized deduplication, which leverages different data transformations prior to deduplication. We show that HEKATE can be used to evaluate performance with different system configurations and deduplication schemes. In fact, we use six real-world data sets to showcase HEKATE {\textquoteright}sability to test performance over a wide range of conditions. We also use this evaluation to showcase how HEKATE can provide insights into data deduplication performance in real systems and optimal configurations given specific data characteristics of an expected workload. HEKATE can also be used to determine the suitability of various deduplication approaches for each data set.",

keywords = "deduplication, performance, storage",

author = "Lars Nielsen and {Lucani R{\"o}tter}, {Daniel Enrique}",

year = "2021",

doi = "10.1109/SmartCloud52277.2021.00019",

language = "English",

pages = "67--72",

booktitle = "Proceedings - 2021 IEEE 6th International Conference on Smart Cloud, SmartCloud 2021",

publisher = "IEEE",

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AU - Nielsen, Lars

AU - Lucani Rötter, Daniel Enrique

PY - 2021

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N2 - In this paper, we introduce HEKATE a tool for gauging the performance of data deduplication. In particular, HEKATE allows to test classic, chunk-based deduplication as well as the emerging concept of generalized deduplication, which leverages different data transformations prior to deduplication. We show that HEKATE can be used to evaluate performance with different system configurations and deduplication schemes. In fact, we use six real-world data sets to showcase HEKATE ’sability to test performance over a wide range of conditions. We also use this evaluation to showcase how HEKATE can provide insights into data deduplication performance in real systems and optimal configurations given specific data characteristics of an expected workload. HEKATE can also be used to determine the suitability of various deduplication approaches for each data set.

AB - In this paper, we introduce HEKATE a tool for gauging the performance of data deduplication. In particular, HEKATE allows to test classic, chunk-based deduplication as well as the emerging concept of generalized deduplication, which leverages different data transformations prior to deduplication. We show that HEKATE can be used to evaluate performance with different system configurations and deduplication schemes. In fact, we use six real-world data sets to showcase HEKATE ’sability to test performance over a wide range of conditions. We also use this evaluation to showcase how HEKATE can provide insights into data deduplication performance in real systems and optimal configurations given specific data characteristics of an expected workload. HEKATE can also be used to determine the suitability of various deduplication approaches for each data set.

KW - deduplication

KW - performance

KW - storage

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U2 - 10.1109/SmartCloud52277.2021.00019

DO - 10.1109/SmartCloud52277.2021.00019

M3 - Article in proceedings

SP - 67

EP - 72

BT - Proceedings - 2021 IEEE 6th International Conference on Smart Cloud, SmartCloud 2021

PB - IEEE

ER -

Hekate a tool for gauging Data Deduplication Performance

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