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학술지 An Integrated Approach Towards Aggressive State-Tracking Migration for Maximizing Performance Benefit in Distributed Computing
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저자
문용혁, 윤찬현
발행일
201309
출처
Cluster Computing, v.16 no.3, pp.367-378
ISSN
1386-7857
출판사
Springer
DOI
https://dx.doi.org/10.1007/s10586-011-0197-0
협약과제
12PG1400, 스마트 단말의 정보유출 방지를 위한 MTM기반 보안 핵심 기술 개발, 조현숙
초록
This paper presents a new state-tracking migration scheme that is integrated with aggressive reservation strategies such as immediate restart, greedy backfilling and selective preemption. The main contribution of this paper is an analysis of the effects of three techniques that can be used beyond the conventional migration schemes. Our simulation results suggest that state-tracking migration with selective preemption entirely outperforms the others. We also observe that the overall performance of immediate restart strategy combining to migration can be stably maintained under various job lifetime distributions. Moreover, it is found that performance would be improved by fitting jobs ruled by the immediate restart strategy rather than queued jobs into the void-intervals under the state-tracking migration scheme. © 2012 Springer Science+Business Media, LLC.
키워드
Distributed computing, Genetic algorithm, Job allocation, Multi-objective optimization, Resource reservation, State-tracking job migration
KSP 제안 키워드
Genetic Algorithm, Job Migration, Job allocation, Lifetime distributions, Multi-objective optimization(MOP), Overall performance, Resource reservation, Restart strategy, an integrated approach, distributed computing, simulation results