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The high pace and increase in cloud computing technology and associated applications, especially large scale data centres, have demanded energy efficient and Quality of Service (QoS) oriented computing platform. To meet these requirements, virtualization and Virtual Machine (VM) consolidation has emerged as an effective solution. The optimization in VM consolidation by means of efficient dynamic resource-utilization prediction, VM selection and placement can achieve optimal solution for energy efficient and QoS oriented cloud computing system. In this paper, an evolutionary computing algorithm called Adaptive Genetic Algorithm (A-GA) based VM consolidation approach has been developed. A-GA based placement policy and its implementation with different VM selection policies like Minimum Migration Time (MMT), Maximum Correlation (MC) and Random Selection (RS), along with different CPU utilization estimation approaches like Inter Quartile Range (IQR), Local Regression (LR), Local Robust Regression (LRR), static THReshold (THR) and Median Absolute Deviation (MAD) has revealed that A-GA based consolidation with MMT selection policy and combined IQR and LRR can enable optimal VM consolidation for large scale infrastructures. In addition, the proposed A-GA policy has exhibited better performance as compared to other meta-heuristics such as Ant Colony Optimization (ACO) and Best Fit Decreasing. The proposed consolidation system can be used for large scale cloud infrastructures where energy conservation, minimal Service Level Agreement (SLA) violation and QoS assurance is inevitable.
Daniela Borissova, Ivan Mustakerov and Dilian Korsemov
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 D.M. Blough, P. Santi, “Investigating upper bounds on network lifetime extension for cell-based energy conservation techniques in stationary ad hoc networks,” Proc. of the 8th annual int. conf. on Mobile computing and networking. MobiCom ’02 . New York, NY, USA: ACM, 2002
1. Bouzon, M., K. Govindan, C. Rodriguez. Evaluating Barriers for Reverse Logistics Implementation undera Multiple Stakeholders’ Perspective Analysis Using Grey Decision Making Approach. Resources. - Conservation and Recycling, 2017, Science Direct (in Press).
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3. Chen, Y. C., Lien, H. P. Lien, G. H. Tzeng. Measures and Evaluation
contexts (“Science fiction stories are”, “Nature conservation issues are”). Nevertheless, there could also be relevant results not mentioning the term journal , such as “a study published in Science” or “The findings, which have been published in Science magazine”, where these are indirectly flagged as academic journals.
Many news stories do not explicitly name their sources. For instance, internationally, newspapers (The New York Times, Le Figaro and Le Monde, El País and La Vanguardia, La Repubblica, and the International Herald Tribune) seem to cite journal
, in retrospect, the discovery could have been made simply by inspection of the public data available at the UCSC Genome Browser https://genome.ucsc.edu/ . This website brings together dozens of different types of genomic data that are calculated or measured, for example, predicted transcription factor binding regions, cross-species conservation levels, and so on. Each type of data is superimposed on the reference genome, and users can open up and visualize any number of the data sets to observe them in juxtaposition with each other. Two of the data tracks show a
 S. Basagni, A. Carosi, and C. Petrioli, “Controlled Vs. Uncontrolled Mobility in Wireless Sensor Networks: Some Performance Insights,” in 2007 IEEE 66th Vehicular Technology Conference, Sep. 2007. pp. 269-273. https://doi.org/10.1109/vetecf.2007.70
 D. M. Blough and P. Santi, “Investigating upper bounds on network lifetime extension for cell-based energy conservation techniques in stationary ad hoc networks,” in Proceedings of the 8th annual international conference on Mobile computing and networking - MobiCom