Cover Image

INCENTIVE-SCHEDULING ALGORITHMS TO PROVIDE GREEN COMPUTATIONAL DATA CENTER

The increased of computational loads in grid servers are dissipating more heat and eventually amplifies the cooling demand in Data Center (DC), and at the same time lead to more submitted jobs missing their job completion deadlines. Accordingly, power supply for cooling such systems in a DC is up un...

Full description

Saved in:
Bibliographic Details
Main Author: HARUNA, AHMED ABBA
Format: Thesis
Language:English
Published: 2017
Subjects:
Q Science (General)
Online Access:http://utpedia.utp.edu.my/22040/1/PhD%20Thesis_Ahmed%20Abba%20Haruna%20%28G02513%29.pdf
http://utpedia.utp.edu.my/22040/
Tags: Add Tag
No Tags, Be the first to tag this record!
id my-utp-utpedia.22040
record_format eprints
spelling my-utp-utpedia.220402021-10-12T14:55:21Z http://utpedia.utp.edu.my/22040/ INCENTIVE-SCHEDULING ALGORITHMS TO PROVIDE GREEN COMPUTATIONAL DATA CENTER HARUNA, AHMED ABBA Q Science (General) The increased of computational loads in grid servers are dissipating more heat and eventually amplifies the cooling demand in Data Center (DC), and at the same time lead to more submitted jobs missing their job completion deadlines. Accordingly, power supply for cooling such systems in a DC is up until 40% to 50% of the total power consumption. To mitigate the cost of electricity, Gas District Cooling (GDC) may be deployed to provide electricity and chilled water to DC facilities with relatively low running cost. Using GDC-DC control model, a GDC can be made to channel wasted energy to cool a DC, effectively reducing CO2 emission. However, it has not been shown how a job scheduler can exploit the GDC-DC model, especially which runs on small-scale DCs. Hence, this study proposed a cooling-efficient job scheduling algorithm for small-scale DC (cooling energy consumption saving can be effective at any conditions e.g. 25 job controlled resources used in this research) that could not accommodate a full-scale GDC-DC model (cooling energy consumption saving can only be effective at specific conditions; needed 6500 job controlled resources). A control strategy was deployed such that the computational job schedulers can reduce the cooling energy consumption in DC by shifting heavy jobs to be executed at night time but light jobs at day time. The experiment results significantly show that the proposed method able to reduce the cooling electricity consumption by 23%. This however may lead to more missed deadlines and unfortunately the controlled resource grid scheduling does not provide compensation to the resource users upon deadlines that missed. Furthermore, the absence of compensation for missed deadlines may dissuade users from submitting jobs to the grid. To solve this issue, green incentive based scheduling algorithms were devised to significantly save cooling electricity consumption cost in DC and also be able to compensate users for their submitted jobs that missed the job completion deadline(s). 2017-05 Thesis NonPeerReviewed application/pdf en http://utpedia.utp.edu.my/22040/1/PhD%20Thesis_Ahmed%20Abba%20Haruna%20%28G02513%29.pdf HARUNA, AHMED ABBA (2017) INCENTIVE-SCHEDULING ALGORITHMS TO PROVIDE GREEN COMPUTATIONAL DATA CENTER. PhD thesis, Universiti Teknologi PETRONAS.
institution Universiti Teknologi Petronas
building UTP Resource Centre
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Petronas
content_source UTP Electronic and Digitized Intellectual Asset
url_provider http://utpedia.utp.edu.my/
language English
topic Q Science (General)
spellingShingle Q Science (General)
HARUNA, AHMED ABBA
INCENTIVE-SCHEDULING ALGORITHMS TO PROVIDE GREEN COMPUTATIONAL DATA CENTER
description The increased of computational loads in grid servers are dissipating more heat and eventually amplifies the cooling demand in Data Center (DC), and at the same time lead to more submitted jobs missing their job completion deadlines. Accordingly, power supply for cooling such systems in a DC is up until 40% to 50% of the total power consumption. To mitigate the cost of electricity, Gas District Cooling (GDC) may be deployed to provide electricity and chilled water to DC facilities with relatively low running cost. Using GDC-DC control model, a GDC can be made to channel wasted energy to cool a DC, effectively reducing CO2 emission. However, it has not been shown how a job scheduler can exploit the GDC-DC model, especially which runs on small-scale DCs. Hence, this study proposed a cooling-efficient job scheduling algorithm for small-scale DC (cooling energy consumption saving can be effective at any conditions e.g. 25 job controlled resources used in this research) that could not accommodate a full-scale GDC-DC model (cooling energy consumption saving can only be effective at specific conditions; needed 6500 job controlled resources). A control strategy was deployed such that the computational job schedulers can reduce the cooling energy consumption in DC by shifting heavy jobs to be executed at night time but light jobs at day time. The experiment results significantly show that the proposed method able to reduce the cooling electricity consumption by 23%. This however may lead to more missed deadlines and unfortunately the controlled resource grid scheduling does not provide compensation to the resource users upon deadlines that missed. Furthermore, the absence of compensation for missed deadlines may dissuade users from submitting jobs to the grid. To solve this issue, green incentive based scheduling algorithms were devised to significantly save cooling electricity consumption cost in DC and also be able to compensate users for their submitted jobs that missed the job completion deadline(s).
format Thesis
author HARUNA, AHMED ABBA
author_facet HARUNA, AHMED ABBA
author_sort HARUNA, AHMED ABBA
title INCENTIVE-SCHEDULING ALGORITHMS TO PROVIDE GREEN COMPUTATIONAL DATA CENTER
title_short INCENTIVE-SCHEDULING ALGORITHMS TO PROVIDE GREEN COMPUTATIONAL DATA CENTER
title_full INCENTIVE-SCHEDULING ALGORITHMS TO PROVIDE GREEN COMPUTATIONAL DATA CENTER
title_fullStr INCENTIVE-SCHEDULING ALGORITHMS TO PROVIDE GREEN COMPUTATIONAL DATA CENTER
title_full_unstemmed INCENTIVE-SCHEDULING ALGORITHMS TO PROVIDE GREEN COMPUTATIONAL DATA CENTER
title_sort incentive-scheduling algorithms to provide green computational data center
publishDate 2017
url http://utpedia.utp.edu.my/22040/1/PhD%20Thesis_Ahmed%20Abba%20Haruna%20%28G02513%29.pdf
http://utpedia.utp.edu.my/22040/
_version_ 1739832938322722816
score 13.211869

Similar Items