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Volumn 1, Issue , 2002, Pages 374-381

Supporting the optimisation of distributed data mining by predicting application run times

Author keywords

Distributed data mining; Optimisation; Predicting application run times

Indexed keywords

COSTS; FORECASTING; INFORMATION SYSTEMS;

EID: 33749999018     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (4)

References (14)
  • 3
    • 84956968918 scopus 로고    scopus 로고
    • A historical application profiler for use by parallel schedulers
    • Springer-Verlag
    • Gibbons, R., (1997), "A Historical Application Profiler for Use by Parallel Schedulers", Lecture Notes in Computer Science (LNCS), 1291, Springer-Verlag, pp. 58-75.
    • (1997) Lecture Notes in Computer Science (LNCS) , vol.1291 , pp. 58-75
    • Gibbons, R.1
  • 12
    • 84947936619 scopus 로고    scopus 로고
    • Using run-time predictions to estimate queue wait times and improve scheduler performance
    • Springer-Verlag
    • Smith, W., Taylor, V., and Foster, I., (1999), "Using run-time predictions to estimate queue wait times and improve scheduler performance", Lecture Notes in Computer Science (LNCS), 1659, Springer-Verlag, pp. 202-229.
    • (1999) Lecture Notes in Computer Science (LNCS) , vol.1659 , pp. 202-229
    • Smith, W.1    Taylor, V.2    Foster, I.3
  • 13
    • 0002333171 scopus 로고    scopus 로고
    • A framework for findidng distributed data mining strategies that are intermediate between centralized strategies and in-place strategies
    • Boston
    • Turinsky, A., and Grossman, R., (2000), "A Framework for Findidng Distributed Data Mining Strategies that are Intermediate between centralized Strategies and In-place Strategies", Workshop on Distributed and Parallel Knowledge Discovery at KDD-2000, Boston, pp. 1-7.
    • (2000) Workshop on Distributed and Parallel Knowledge Discovery at KDD-2000 , pp. 1-7
    • Turinsky, A.1    Grossman, R.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.