Cover Image

Optimizing BOINC scheduling using genetic algorithm based on thermal profile

Berkeley Open Infrastructure for Network Computing (BOINC) is an open source middleware for volunteer and grid computing. Main function of BOINC is to use the idle time of computer to run some computation at background. Universiti Teknologi Petronas (UTP) campus grid used BOINC as middleware in comp...

Full description

Saved in:
Bibliographic Details
Main Authors: Binti, N.N., Zakaria, M.N.B., Aziz, I.B.A., Binti, N.S.
Format: Conference or Workshop Item
Published: Institute of Electrical and Electronics Engineers Inc. 2014
Online Access:https://www.scopus.com/inward/record.uri?eid=2-s2.0-84938815118&doi=10.1109%2fICCOINS.2014.6868837&partnerID=40&md5=6b83c459943540d76885a603e4317fff
http://eprints.utp.edu.my/31165/
Tags: Add Tag
No Tags, Be the first to tag this record!
id my.utp.eprints.31165
record_format eprints
spelling my.utp.eprints.311652022-03-25T09:01:54Z Optimizing BOINC scheduling using genetic algorithm based on thermal profile Binti, N.N. Zakaria, M.N.B. Aziz, I.B.A. Binti, N.S. Berkeley Open Infrastructure for Network Computing (BOINC) is an open source middleware for volunteer and grid computing. Main function of BOINC is to use the idle time of computer to run some computation at background. Universiti Teknologi Petronas (UTP) campus grid used BOINC as middleware in computer labs. However, computer can only process jobs during weekday and office hour because they want to reduce energy used for cooling power. In order to fully utilize the computer in labs, we proposed new jobs scheduling algorithm can run based on thermal constraInternational The proposed algorithm is combination of thermal profile and heuristic approach. We use genetic algorithm to find the best combination of clients and jobs based on clients order and least execution time. Then we compare our algorithm with brute force method. Result from simulation it shows that proposed algorithm successfully distribute and execute job based on thermal constraints in an effective and efficient way compare to brute force method. © 2014 IEEE. Institute of Electrical and Electronics Engineers Inc. 2014 Conference or Workshop Item NonPeerReviewed https://www.scopus.com/inward/record.uri?eid=2-s2.0-84938815118&doi=10.1109%2fICCOINS.2014.6868837&partnerID=40&md5=6b83c459943540d76885a603e4317fff Binti, N.N. and Zakaria, M.N.B. and Aziz, I.B.A. and Binti, N.S. (2014) Optimizing BOINC scheduling using genetic algorithm based on thermal profile. In: UNSPECIFIED. http://eprints.utp.edu.my/31165/
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 Berkeley Open Infrastructure for Network Computing (BOINC) is an open source middleware for volunteer and grid computing. Main function of BOINC is to use the idle time of computer to run some computation at background. Universiti Teknologi Petronas (UTP) campus grid used BOINC as middleware in computer labs. However, computer can only process jobs during weekday and office hour because they want to reduce energy used for cooling power. In order to fully utilize the computer in labs, we proposed new jobs scheduling algorithm can run based on thermal constraInternational The proposed algorithm is combination of thermal profile and heuristic approach. We use genetic algorithm to find the best combination of clients and jobs based on clients order and least execution time. Then we compare our algorithm with brute force method. Result from simulation it shows that proposed algorithm successfully distribute and execute job based on thermal constraints in an effective and efficient way compare to brute force method. © 2014 IEEE.
format Conference or Workshop Item
author Binti, N.N.
Zakaria, M.N.B.
Aziz, I.B.A.
Binti, N.S.
spellingShingle Binti, N.N.
Zakaria, M.N.B.
Aziz, I.B.A.
Binti, N.S.
Optimizing BOINC scheduling using genetic algorithm based on thermal profile
author_facet Binti, N.N.
Zakaria, M.N.B.
Aziz, I.B.A.
Binti, N.S.
author_sort Binti, N.N.
title Optimizing BOINC scheduling using genetic algorithm based on thermal profile
title_short Optimizing BOINC scheduling using genetic algorithm based on thermal profile
title_full Optimizing BOINC scheduling using genetic algorithm based on thermal profile
title_fullStr Optimizing BOINC scheduling using genetic algorithm based on thermal profile
title_full_unstemmed Optimizing BOINC scheduling using genetic algorithm based on thermal profile
title_sort optimizing boinc scheduling using genetic algorithm based on thermal profile
publisher Institute of Electrical and Electronics Engineers Inc.
publishDate 2014
url https://www.scopus.com/inward/record.uri?eid=2-s2.0-84938815118&doi=10.1109%2fICCOINS.2014.6868837&partnerID=40&md5=6b83c459943540d76885a603e4317fff
http://eprints.utp.edu.my/31165/
_version_ 1738657209585238016
score 13.211869

Similar Items