Abstract
With the appearance of the period of large information, the customary information preparing model and asset the executive’s model have been not able to fulfill the developing need. In this way, the recreation of the quantitative assessment strategy for cloud asset dependent on MapReduce figuring mode was advanced right now. The quantitative assessment model and record foundation of cloud assets in Hadoop stage and MapReduce processing mode were abridged. Through the quantitative assessment strategy for cloud assets dependent on MapReduce processing mode, the information was gathered and examined. The outcomes show that the quantitative assessment technique for cloud asset dependent on MapReduce processing model has a decent figuring force and the capacity to anticipate the utilization of cloud assets.
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07 June 2022
This article has been retracted. Please see the Retraction Notice for more detail: https://doi.org/10.1007/s12652-022-04088-1
References
Abouzeid A, Bajda-Pawlikowski K, Abadi D, Silberschatz A, Rasin A (2009) Hadoopdb: an architectural hybrid of mapreduce and dbms technologies for analytical workloads. Proc Vldb Endow 2(1):922–933
Beugin J, Marais J (2012) Simulation-based evaluation of dependability and safety properties of satellite technologies for railway localization. Transp Res Part C 22:42–57
Boehm M, Dusenberry MW, Eriksson D, Evfimievski AV, Manshadi FM, Pansare N et al (2016) Systemml: declarative machine learning on spark. Proc Vldb Endow 9(13):1425–1436
Burke DR, Moslemi-Tabrizi S, Smy TJ (2010) Simulation of inhomogeneous models using the finite cloud method. Simulation inhomogener modelle unter benutzung der finite-wolken-methode. Materialwiss Werkstofftech 41(5):336–340
Cohen J (2009) Graph twiddling in a mapreduce world. Comput Sci Eng 11(4):29–41
Igarashi Y, Yamaguchi T, Hachiya H (2011) Stability of quantitative evaluation method of liver fibrosis using amplitude distribution model of fibrotic liver. Jpn J Appl Phys 50(50):913–919
Jacob MV, Mazierska J, Leong K, Krupka J (2001) Novel method for calculation and measurement of unloaded q-factor of superconducting dielectric resonators. IEEE MTT-S International Microwave Symposium digest. IEEE MTT-S Int Microw Symp 3:1993–1996
Kong H, Hong MK, Kim T (2018) Security risk assessment framework for smart car using the attack tree analysis. J Ambient Intell Human Comput 9:531–551. https://doi.org/10.1007/s12652-016-0442-8
Mckenna A, Hanna M, Banks E, Sivachenko A, Cibulskis K, Kernytsky A et al (2010) The genome analysis toolkit: a mapreduce framework for analyzing next-generation dna sequencing data. Genome Res 20(9):1297–1303
Mitzithra ME, Deby F, Balayssac JP, Salin J (2015) Proposal for an alternative operativemethod for determination of polarisation resistance for the quantitative evaluation of corrosion of reinforcing steel in concrete cooling towers. Nucl Eng Des 288:42–55
Nykiel T, Mishra C, Mishra C, Kollios G, Koudas N (2010) Mrshare: sharing across multiple queries in mapreduce. Proc Vldb Endow 3(1–2):494–505
Rana KK, Tripathi S, Raw RS (2020) Inter-vehicle distance-based location aware multi-hop routing in vehicular ad-hoc network. J Ambient Intell Human Comput. https://doi.org/10.1007/s12652-020-01947-7
Richter A, Glunz SW, Werner F, Schmidt J, Cuevas A (2012) Improved quantitative description of auger recombination in crystalline silicon. Phys Rev B 86(16):4172–4181
Sanzo PD, Quaglia F, Ciciani B, Pellegrini A, Didona D, Romano P et al (2015) A flexible framework for accurate simulation of cloud in-memory data stores. Simul Modell 58:219–238
Urbina-Villalba G, Lozsán A, Rahn K, Romero-Cano MS (2009) Calculation of the stability ratio of suspensions using emulsion stability simulations. Comput Phys Commun 180(11):2129–2139
Vaidya M (2010) Mapreduce: a flexible data processing tool. Commun ACM 53(1):72–77
Zhang S, Fan W, Fan W, Winslett M (2014) Design and implementation of a real-time interactive analytics system for large spatio-temporal data. Proc Vldb Endow 7(13):1754–1759
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This article has been retracted. Please see the retraction notice for more detail:https://doi.org/10.1007/s12652-022-04088-1
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Vuppala, B., Swarnalatha, P. RETRACTED ARTICLE: Quantitative evaluation method of cloud resources based on work scheduling. J Ambient Intell Human Comput 12, 6969–6973 (2021). https://doi.org/10.1007/s12652-020-02342-y
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DOI: https://doi.org/10.1007/s12652-020-02342-y