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Volumn 44, Issue 7, 2014, Pages 771-775

A note on software tools and techniques for monitoring and prediction of cloud services

Author keywords

[No Author keywords available]

Indexed keywords

DISTRIBUTED DATABASE SYSTEMS; FORECASTING; RESEARCH; WEB SERVICES;

EID: 84902549207     PISSN: 00380644     EISSN: 1097024X     Source Type: Journal    
DOI: 10.1002/spe.2266     Document Type: Review
Times cited : (11)

References (19)
  • 1
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    • Runtime measurements in the cloud: Observing, analyzing, and reducing variance
    • Schad J, Dittrich J, Quiané-Ruiz J,. Runtime measurements in the cloud: observing, analyzing, and reducing variance. Proceedings of the VLDB Endowment 2010; 3 (1-2): 460-471.
    • (2010) Proceedings of the VLDB Endowment , vol.3 , Issue.12 , pp. 460-471
    • Schad, J.1    Dittrich, J.2    Quiané-Ruiz, J.3
  • 3
    • 0032592464 scopus 로고    scopus 로고
    • The network weather service: A distributed resource performance forecasting service for metacomputing
    • Wolski R, Spring N, Hayes J,. The network weather service: a distributed resource performance forecasting service for metacomputing. Future Generation Computer Systems 1999; 15 (5-6): 757-768.
    • (1999) Future Generation Computer Systems , vol.15 , Issue.56 , pp. 757-768
    • Wolski, R.1    Spring, N.2    Hayes, J.3
  • 6
    • 84902535524 scopus 로고    scopus 로고
    • Amazon Cloud Watch, 2014. Available at: http://aws.amazon.com/cloudwatch/ .
    • (2014) Amazon Cloud Watch
  • 7
    • 84902554043 scopus 로고    scopus 로고
    • Monitis
    • Monitis, 2014. Available at: http:// portal.monitis.com/.
    • (2014)
  • 8
    • 84902554044 scopus 로고    scopus 로고
    • Nimsoft
    • Nimsoft, 2014. http://www.nimsoft.com/solutions/nimsoft-monitor/cloud.
    • (2014)
  • 13
    • 84902549426 scopus 로고    scopus 로고
    • Analyzing performance traces using temporal formulas
    • DOI: 10.1002/spe.2256.
    • Ryckbosch F, Diwan A,. Analyzing performance traces using temporal formulas. Journal of Software: Practice and Experience 2014; 44 (7): 777-792. DOI: 10.1002/spe.2256.
    • (2014) Journal of Software: Practice and Experience , vol.44 , Issue.7 , pp. 777-792
    • Ryckbosch, F.1    Diwan, A.2
  • 14
    • 84902543463 scopus 로고    scopus 로고
    • CPU load prediction for cloud environment based on a dynamic ensemble model
    • DOI: 10.1002/spe.2231.
    • Cao J, Fu J, Li M, Chen J,. CPU load prediction for cloud environment based on a dynamic ensemble model. Software: Practice and Experience 2013; 44 (7): 793-804. DOI: 10.1002/spe.2231.
    • (2013) Software: Practice and Experience , vol.44 , Issue.7 , pp. 793-804
    • Cao, J.1    Fu, J.2    Li, M.3    Chen, J.4
  • 15
    • 84902545698 scopus 로고    scopus 로고
    • Generic event-based monitoring and adaptation methodology for heterogeneous distributed systems
    • DOI: 10.1002/spe.2254.
    • Inzinger C, Hummer W, Satzger B, Leitner P, Dustdar S,. Generic event-based monitoring and adaptation methodology for heterogeneous distributed systems. Journal of Software: Practice and Experience 2014; 44 (7): 805-822. DOI: 10.1002/spe.2254.
    • (2014) Journal of Software: Practice and Experience , vol.44 , Issue.7 , pp. 805-822
    • Inzinger, C.1    Hummer, W.2    Satzger, B.3    Leitner, P.4    Dustdar, S.5
  • 16
    • 84902535864 scopus 로고    scopus 로고
    • A novel monitoring mechanism by event trigger for Hadoop system performance analysis
    • DOI: 10.1002/spe.2230.
    • Liao C-S, Chuang C-P, Chang R-S,. A novel monitoring mechanism by event trigger for Hadoop system performance analysis. Journal of Software: Practice and Experience 2013; 44 (7): 823-834. DOI: 10.1002/spe.2230.
    • (2013) Journal of Software: Practice and Experience , vol.44 , Issue.7 , pp. 823-834
    • Liao, C.-S.1    Chuang, C.-P.2    Chang, R.-S.3
  • 18
    • 84902544848 scopus 로고    scopus 로고
    • Feature-based high-availability mechanism for quantile tasks in real-time data stream processing
    • DOI: 10.1002/spe.2244.
    • Ding W, Han Y, Wang J, Zhao Z,. Feature-based high-availability mechanism for quantile tasks in real-time data stream processing. Journal of Software: Practice and Experience 2013; 44 (7): 855-871. DOI: 10.1002/spe.2244.
    • (2013) Journal of Software: Practice and Experience , vol.44 , Issue.7 , pp. 855-871
    • Ding, W.1    Han, Y.2    Wang, J.3    Zhao, Z.4
  • 19
    • 84902532584 scopus 로고    scopus 로고
    • Design and implementation of task scheduling strategies for massive remote sensing data processing across multiple data centers
    • DOI: 10.1002/spe.2229.
    • Zhang W, Wang L, Ma Y, Liu D,. Design and implementation of task scheduling strategies for massive remote sensing data processing across multiple data centers. Journal of Software: Practice and Experience 2013; 44 (7): 873-886. DOI: 10.1002/spe.2229.
    • (2013) Journal of Software: Practice and Experience , vol.44 , Issue.7 , pp. 873-886
    • Zhang, W.1    Wang, L.2    Ma, Y.3    Liu, D.4


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.