File Download
  Links for fulltext
     (May Require Subscription)
Supplementary

Conference Paper: Security-driven heuristics and a fast genetic algorithm for trusted grid job scheduling

TitleSecurity-driven heuristics and a fast genetic algorithm for trusted grid job scheduling
Authors
KeywordsDistributed supercomputing
Genetic algorithms
Grid computing
Heterogeneous computing
NAS benchmark
On-line job scheduling
Parameter-sweep applications
Security-driven heuristics
Issue Date2005
PublisherIEEE, Computer Society.
Citation
Proceedings - 19Th Ieee International Parallel And Distributed Processing Symposium, Ipdps 2005, 2005, v. 2005 How to Cite?
AbstractIn this paper, our contributions are two-fold: First, we enhance the Min-Min and Sufferage heuristics under three risk modes driven by security concerns. Second, we propose a new Space-Time Genetic Algorithm (STGA) for trusted job scheduling, which is very fast and easy to implement. Under our new model, a job can possibly fail if the site security level is lower than the job security demand. We consider three security-driven heuristic modes: secure, risky, and f-risky. The secure mode always dispatches jobs to secure sites meeting the job security demands. The risky mode allocates jobs to any available resource site, taking whatever the risk it may face. The f-risky mode tries to limit the risk to be at most certain probability f. Our extensive simulation results indicated that the proposed STGA is highly effective in scheduling two types of practical workloads: NAS (Numerical Aerodynamic Simulation) and PSA (parameter-sweep application). The STGA outperforms the Min-Min and Sufferage heuristics under three risk modes, in terms of a wide range of performance metrics including makespan, average response time, site utilization, slowdown ratio, and job failure rate.
Persistent Identifierhttp://hdl.handle.net/10722/45823
ISSN
References

 

DC FieldValueLanguage
dc.contributor.authorSong, Sen_HK
dc.contributor.authorKwok, YKen_HK
dc.contributor.authorHwang, Ken_HK
dc.date.accessioned2007-10-30T06:36:20Z-
dc.date.available2007-10-30T06:36:20Z-
dc.date.issued2005en_HK
dc.identifier.citationProceedings - 19Th Ieee International Parallel And Distributed Processing Symposium, Ipdps 2005, 2005, v. 2005en_HK
dc.identifier.issn1063-6374en_HK
dc.identifier.urihttp://hdl.handle.net/10722/45823-
dc.description.abstractIn this paper, our contributions are two-fold: First, we enhance the Min-Min and Sufferage heuristics under three risk modes driven by security concerns. Second, we propose a new Space-Time Genetic Algorithm (STGA) for trusted job scheduling, which is very fast and easy to implement. Under our new model, a job can possibly fail if the site security level is lower than the job security demand. We consider three security-driven heuristic modes: secure, risky, and f-risky. The secure mode always dispatches jobs to secure sites meeting the job security demands. The risky mode allocates jobs to any available resource site, taking whatever the risk it may face. The f-risky mode tries to limit the risk to be at most certain probability f. Our extensive simulation results indicated that the proposed STGA is highly effective in scheduling two types of practical workloads: NAS (Numerical Aerodynamic Simulation) and PSA (parameter-sweep application). The STGA outperforms the Min-Min and Sufferage heuristics under three risk modes, in terms of a wide range of performance metrics including makespan, average response time, site utilization, slowdown ratio, and job failure rate.en_HK
dc.format.extent253397 bytes-
dc.format.extent3564 bytes-
dc.format.mimetypeapplication/pdf-
dc.format.mimetypetext/plain-
dc.languageengen_HK
dc.publisherIEEE, Computer Society.en_HK
dc.relation.ispartofProceedings - 19th IEEE International Parallel and Distributed Processing Symposium, IPDPS 2005en_HK
dc.rights©2005 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.en_HK
dc.rightsCreative Commons: Attribution 3.0 Hong Kong License-
dc.subjectDistributed supercomputingen_HK
dc.subjectGenetic algorithmsen_HK
dc.subjectGrid computingen_HK
dc.subjectHeterogeneous computingen_HK
dc.subjectNAS benchmarken_HK
dc.subjectOn-line job schedulingen_HK
dc.subjectParameter-sweep applicationsen_HK
dc.subjectSecurity-driven heuristicsen_HK
dc.titleSecurity-driven heuristics and a fast genetic algorithm for trusted grid job schedulingen_HK
dc.typeConference_Paperen_HK
dc.identifier.openurlhttp://library.hku.hk:4550/resserv?sid=HKU:IR&issn=1063-6374&volume=&spage=&epage=&date=2005&atitle=Security-Driven+Heuristics+and+A+Fast+Genetic+Algorithm+for+Trusted+Grid+Job+Schedulingen_HK
dc.identifier.emailKwok, YK:ykwok@eee.hku.hken_HK
dc.identifier.authorityKwok, YK=rp00128en_HK
dc.description.naturepublished_or_final_versionen_HK
dc.identifier.doi10.1109/IPDPS.2005.397en_HK
dc.identifier.scopuseid_2-s2.0-33745181847en_HK
dc.identifier.hkuros105769-
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-33745181847&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.volume2005en_HK
dc.identifier.scopusauthoridSong, S=8875389000en_HK
dc.identifier.scopusauthoridKwok, YK=7101857718en_HK
dc.identifier.scopusauthoridHwang, K=7402426691en_HK

Export via OAI-PMH Interface in XML Formats


OR


Export to Other Non-XML Formats