Energy efficient dynamic resource management in cloud computing based on logistic regression model and median absolute deviation

Al-Ayyoub, 2016, Towards improving resource management in cloud systems using a multiagent framework, Int. J. Cloud Comput., 5, 112, 10.1504/IJCC.2016.075112 Al-Ayyoub, 2015, Multiagent based dynamic resource provisioning and monitoring for cloud computing systems infrastructure, Cluster Comput., 18, 919, 10.1007/s10586-015-0449-5 Ratten, 2015, Cloud computing technology innovation advances: a set of research propositions, Int. J. Cloud Appl. Comput. (IJCAC), 5, 69 Emeakaroha, 2012, Towards autonomic detection of sla violations in cloud infrastructures, Future Gener. Comput. Syst., 28, 1017, 10.1016/j.future.2011.08.018 Alhamad, 2011, 469 Mell, 2011, The NIST definition of cloud computing, NIST, Tech. Rep., 09 Freedman, 2005 WALKER, 1967, Estimation of the probability of an event as a function of several independent variables, Biometrika, 54, 167, 10.1093/biomet/54.1-2.167 Cox, 1958, The regression analysis of binary sequences (with discussion), J. R. Stat. Soc. Ser. B, 20, 215 Logistic Regression Wikipedia Page. [Online]. Available: https://en.m.wikipedia.org/wiki/Logisticregression. Zhao, 2001, Comparison of logistic regression and linear regression in modeling percentage data, Appl. Environ. Microbiol., 67, 2129, 10.1128/AEM.67.5.2129-2135.2001 Zhao, 2000, Inoculum size of clostridium botulinum 56a spores influences time-to-detection and percent growthpositive samples, J. Food Sci., 65, 1369, 10.1111/j.1365-2621.2000.tb10614.x Wardat, 2018, Cloud data centers revenue maximization using server consolidation: Modeling and evaluation, 172 Jennings, 2015, Resource management in clouds: survey and research challenges, J. Netw. Syst. Manag., 23, 567, 10.1007/s10922-014-9307-7 Das, 2010, Virtualcloud-a cloud environment simulator, Indian Inst. Technol., Tech. Rep., 10 Beloglazov, 2012, Energy-aware resource allocation heuristics for efficient management of data centers for cloud computing, Future Gener. Comput. Syst., 28, 755, 10.1016/j.future.2011.04.017 Beloglazov, 2013, Managing overloaded hosts for dynamic consolidation of virtual machines in cloud data centers under quality of service constraints, IEEE Trans. Parallel Distrib. Syst., 24, 1366, 10.1109/TPDS.2012.240 2012, Optimal online deterministic algorithms and adaptive heuristics for energy and performance efficient dynamic consolidation of virtual machines in cloud data centers, Concurr. Comput. Pract. Exp., 24, 1397, 10.1002/cpe.1867 Choudhary, 2015, Green data center using spearmans ranking algorithm, Int. J. Comput. Sci. Inf. Technol., 6 Cleveland, 1979, Robust locally weighted regression and smoothing scatterplots, J. Am. Stat. Assoc., 74, 829, 10.1080/01621459.1979.10481038 Lodhi, 2015, Enhanced minimum utilization vm selection mechanism for clouds, Int. J. Comput. Sci. Inf. Technol., 6 Calheiros, 2009 Beloglazov, 2010 Monitis [online] [Accessed 2017 February] Available: http://portal.monitis.com. Ferreto, 2011, Server consolidation with migration control for virtualized data centers, Future Gener. Comput. Syst., 27, 1027, 10.1016/j.future.2011.04.016 Younge, 2010, Efficient resource management for cloud computing environments, 357 Salimian, 2016, An adaptive fuzzy threshold-based approach for energy and performance efficient consolidation of virtual machines, Computing, 98, 641, 10.1007/s00607-015-0474-5 Zkik, 2017, Secure mobile multi cloud architecture for authentication and data storage, Int. J. Cloud Appl. Comput. (IJCAC), 7, 62