EGE: A New Energy-Aware GPU Based Erasure Coding Scheduler for Cloud Storage Systems

Mehdi Pirahandeh; Deok Hwan Kim

doi:10.1109/ICUFN.2018.8436594

EGE: A New Energy-Aware GPU Based Erasure Coding Scheduler for Cloud Storage Systems

Mehdi Pirahandeh, Deok Hwan Kim

Inha University

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

11 Scopus citations

Abstract

Redundant array of inexpensive disks (RAID) based storage systems performance is limited to the sequential nature of the central processing unit (CPU), and they consume high amounts of energy because they need erasure coding for striping data and parity into storage devices. This paper proposed an energy-aware GPU based scheduling. The proposed scheduler differs from existing RAID in that it can reduce the number of CPU cycles and coding time. The proposed system generates parity by using a GPU, stripes parity at the initiator server and stripes data at the target server. We also apply an energy-aware scheduling scheme based on solid state disk-based data storage and hard disk drive-based parity storage. Experimental results show that the energy consumption by GPU-RAID is 45% less than Linux-RAID.

Original language	English
Title of host publication	ICUFN 2018 - 10th International Conference on Ubiquitous and Future Networks
Publisher	IEEE Computer Society
Pages	619-621
Number of pages	3
ISBN (Print)	9781538646465
DOIs	https://doi.org/10.1109/ICUFN.2018.8436594
State	Published - 14 Aug 2018
Event	10th International Conference on Ubiquitous and Future Networks, ICUFN 2018 - Prague, Czech Republic Duration: 3 Jul 2018 → 6 Jul 2018

Publication series

Name	International Conference on Ubiquitous and Future Networks, ICUFN
Volume	2018-July
ISSN (Print)	2165-8528
ISSN (Electronic)	2165-8536

Conference

Conference	10th International Conference on Ubiquitous and Future Networks, ICUFN 2018
Country/Territory	Czech Republic
City	Prague
Period	3/07/18 → 6/07/18

Bibliographical note

Publisher Copyright:
© 2018 IEEE.

Keywords

cloud storage system
energy-aware scheduling
hybrid storage
solid state disk (SSD)

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1109/ICUFN.2018.8436594

Cite this

Pirahandeh, M., & Kim, D. H. (2018). EGE: A New Energy-Aware GPU Based Erasure Coding Scheduler for Cloud Storage Systems. In ICUFN 2018 - 10th International Conference on Ubiquitous and Future Networks (pp. 619-621). Article 8436594 (International Conference on Ubiquitous and Future Networks, ICUFN; Vol. 2018-July). IEEE Computer Society. https://doi.org/10.1109/ICUFN.2018.8436594

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title = "EGE: A New Energy-Aware GPU Based Erasure Coding Scheduler for Cloud Storage Systems",

abstract = "Redundant array of inexpensive disks (RAID) based storage systems performance is limited to the sequential nature of the central processing unit (CPU), and they consume high amounts of energy because they need erasure coding for striping data and parity into storage devices. This paper proposed an energy-aware GPU based scheduling. The proposed scheduler differs from existing RAID in that it can reduce the number of CPU cycles and coding time. The proposed system generates parity by using a GPU, stripes parity at the initiator server and stripes data at the target server. We also apply an energy-aware scheduling scheme based on solid state disk-based data storage and hard disk drive-based parity storage. Experimental results show that the energy consumption by GPU-RAID is 45% less than Linux-RAID.",

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Pirahandeh, M & Kim, DH 2018, EGE: A New Energy-Aware GPU Based Erasure Coding Scheduler for Cloud Storage Systems. in ICUFN 2018 - 10th International Conference on Ubiquitous and Future Networks., 8436594, International Conference on Ubiquitous and Future Networks, ICUFN, vol. 2018-July, IEEE Computer Society, pp. 619-621, 10th International Conference on Ubiquitous and Future Networks, ICUFN 2018, Prague, Czech Republic, 3/07/18. https://doi.org/10.1109/ICUFN.2018.8436594

EGE: A New Energy-Aware GPU Based Erasure Coding Scheduler for Cloud Storage Systems. / Pirahandeh, Mehdi; Kim, Deok Hwan.
ICUFN 2018 - 10th International Conference on Ubiquitous and Future Networks. IEEE Computer Society, 2018. p. 619-621 8436594 (International Conference on Ubiquitous and Future Networks, ICUFN; Vol. 2018-July).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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EGE: A New Energy-Aware GPU Based Erasure Coding Scheduler for Cloud Storage Systems

Abstract

Publication series

Conference

Bibliographical note

Keywords

UN SDGs

Access to Document

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