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Green data center by incentive-based job scheduling approach

Data centers (DC) need electrical energy (power) for high speed computing and for rooms/facilities cooling purposes. DCs are therefore fast becoming high consumer of electrical energy. Heavy computing loads on servers in DC lead to high heat dissipation that eventually amplifies the cooling demand i...

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Main Authors: Jung, L.T., Haruna, A.A.
Format: Conference or Workshop Item
Published: Institute of Electrical and Electronics Engineers Inc. 2019
Online Access:https://www.scopus.com/inward/record.uri?eid=2-s2.0-85062850814&doi=10.1109%2fICOS.2018.8632811&partnerID=40&md5=0f7379efd12ecc680f9a3dd886775bbc
http://eprints.utp.edu.my/23567/
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spelling my.utp.eprints.235672021-08-19T07:56:33Z Green data center by incentive-based job scheduling approach Jung, L.T. Haruna, A.A. Data centers (DC) need electrical energy (power) for high speed computing and for rooms/facilities cooling purposes. DCs are therefore fast becoming high consumer of electrical energy. Heavy computing loads on servers in DC lead to high heat dissipation that eventually amplifies the cooling demand in DC. High heat with inadequate cooling could lead to more frequent system failures thereby more jobs in DC to miss their job completion deadlines. Unfortunately, the conventional DC job scheduling approaches do not provide compensation to the resource users on their jobs that missed the deadlines. The absence of compensation may dissuade users from submitting jobs to the DCs. The energy consumed for cooling in DC dominates about one third of total DC energy consumption. While free air cooling strategy is used elsewhere, it is not generally applicable in tropical countries such as that in Malaysia. A constant artificial cooling (air conditioning) is needed to sustain the DC operation. To solve this issue in the tropical region, incentive-based scheduling algorithms were devised to significantly reduce the electricity consumption cost in DC and also to be able to compensate users (as an incentive) for their submitted jobs that missed the job completion deadline(s). Ultimately, the proposed job scheduling approach is aimed to produce green DCs. © 2018 IEEE. Institute of Electrical and Electronics Engineers Inc. 2019 Conference or Workshop Item NonPeerReviewed https://www.scopus.com/inward/record.uri?eid=2-s2.0-85062850814&doi=10.1109%2fICOS.2018.8632811&partnerID=40&md5=0f7379efd12ecc680f9a3dd886775bbc Jung, L.T. and Haruna, A.A. (2019) Green data center by incentive-based job scheduling approach. In: UNSPECIFIED. http://eprints.utp.edu.my/23567/
institution Universiti Teknologi Petronas
building UTP Resource Centre
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Petronas
content_source UTP Institutional Repository
url_provider http://eprints.utp.edu.my/
description Data centers (DC) need electrical energy (power) for high speed computing and for rooms/facilities cooling purposes. DCs are therefore fast becoming high consumer of electrical energy. Heavy computing loads on servers in DC lead to high heat dissipation that eventually amplifies the cooling demand in DC. High heat with inadequate cooling could lead to more frequent system failures thereby more jobs in DC to miss their job completion deadlines. Unfortunately, the conventional DC job scheduling approaches do not provide compensation to the resource users on their jobs that missed the deadlines. The absence of compensation may dissuade users from submitting jobs to the DCs. The energy consumed for cooling in DC dominates about one third of total DC energy consumption. While free air cooling strategy is used elsewhere, it is not generally applicable in tropical countries such as that in Malaysia. A constant artificial cooling (air conditioning) is needed to sustain the DC operation. To solve this issue in the tropical region, incentive-based scheduling algorithms were devised to significantly reduce the electricity consumption cost in DC and also to be able to compensate users (as an incentive) for their submitted jobs that missed the job completion deadline(s). Ultimately, the proposed job scheduling approach is aimed to produce green DCs. © 2018 IEEE.
format Conference or Workshop Item
author Jung, L.T.
Haruna, A.A.
spellingShingle Jung, L.T.
Haruna, A.A.
Green data center by incentive-based job scheduling approach
author_facet Jung, L.T.
Haruna, A.A.
author_sort Jung, L.T.
title Green data center by incentive-based job scheduling approach
title_short Green data center by incentive-based job scheduling approach
title_full Green data center by incentive-based job scheduling approach
title_fullStr Green data center by incentive-based job scheduling approach
title_full_unstemmed Green data center by incentive-based job scheduling approach
title_sort green data center by incentive-based job scheduling approach
publisher Institute of Electrical and Electronics Engineers Inc.
publishDate 2019
url https://www.scopus.com/inward/record.uri?eid=2-s2.0-85062850814&doi=10.1109%2fICOS.2018.8632811&partnerID=40&md5=0f7379efd12ecc680f9a3dd886775bbc
http://eprints.utp.edu.my/23567/
_version_ 1738656490382688256
score 13.211869

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