Publicações científicas - CONSIDERAÇÕES FINAIS

6 CONSIDERAÇÕES FINAIS

6.2 Publicações científicas

Diante da importância de contribuições científicas para construção da tese de doutorado, na Tabela 22 estão listadas as publicações científicas referentes ao período do doutorado (2014 a 2019).

Os trabalhos foram realizados nesse período e estão diretamente relacionados ao conteúdo central da tese.

Tabela 22 - Lista de publicações científicas no período do doutorado

# Título Autores Evento/Periódico Ano

Performance evaluation of agricultural municipalities in Paraíba State from

Brazil with Data Envelopment Analysis (DEA), the

models with SBM and SBM with super

efficiency MARQUES JUNIOR, F. D.; THOMAZ, A. C. F.; PEREIRA, W. F.; LOPES, A. L. M. 12th International Conference on Data Envelopment Analysis, University of Malaya, Kuala Lumpur – Malaysia. 2014 2 Electing efficient elements in SDNFV environments MARQUES JUNIOR, F.D; EUFRAZINO TEIXEIRA, G; LOPES DIAS, K; FREIRE CUNHA, P.; DAMASCENO DE MELO, M. 58th The Operational Research Society Annual Conference – DEA Stream, Portsmouth, England, 6-9 September 2016. 2016 3 A Multiobjective way to select the best

settings using Super-Efficiency SBM DEA models to deliver network virtualization services - a stochastic case of study MARQUES JUNIOR, F. D.; DIAS, K. L.; CUNHA, P. R. F.; DOMINGUES, M. A. O 15th International Conference on Data Envelopment Analysis, Prague – Czech Republic, 2017. 2017 4 Evaluating the fractal behaviour of Virtual Networks through of an Inter- temporal DEA model

- Introducing the Windows Multiplicative model MARQUES JUNIOR, F. D.; EMROUZNEJAD, A; DIAS, K. L.; CUNHA, P. R. F.; DE CASTRO E SILVA, JORGE L. DEA40: International Conference on Data Envelopment Analysis, 2018, Birmingham, UK 2018 5 SMDEA output- oriented results MARQUES JUNIOR, F. D.; EMROUZNEJAD, Mendeley public Dataset 2018

A.; DIAS, K. L.; CUNHA, P. R. F.; DE CASTRO E SILVA, JORGE L. 6 Windows Multiplicative CCR- O DEA Model MARQUES JUNIOR, F. D.; EMROUZNEJAD, A; DIAS, K. L.; CUNHA, P. R. F.; DE CASTRO E SILVA, JORGE L. Mendeley public Dataset 2018 7 Super-Cobb- Douglas - SMDEA CCR-I – results Marques Júnior, Francisco Daladier; Emrouznejad, Ali; Dias, Kelvin; Freire

Cunha, Paulo Roberto; de Castro e Silva, Jorge Luiz; Eufrazino Teixeira, Gervasio Mendeley public Dataset 2018 8 Optimising virtual networks over time

by using Windows Multiplicative DEA model MARQUES JUNIOR, F. D.; EMROUZNEJAD, A; DIAS, K. L.; CUNHA, P. R. F.; DE CASTRO E SILVA, JORGE L.

Expert System with Application Journal da Elsevier – Qualis A1 2019 9 Ranking virtual networks accurately using output-oriented multiplicative DEA model with variable return to scale MARQUES JUNIOR, F. D.; EMROUZNEJAD, A; MIRANDA LOPES, A. L.; DIAS, K. L.; CUNHA, P. R. F.; DE CASTRO E SILVA, JORGE L. XVI EUROPEAN WORKSHOP ON EFFICIENCY AND PRODUCTIVITY ANALYSIS (EWEPA) LONDON, JUNE 10- 13 2019 2019

REFERÊNCIAS

Alcalde Cuesta, F., González Sequeiros, P., & Lozano Rojo, Á. (2016). Exploring the topological sources of robustness against invasion in biological and technological networks. Scientific Reports, 6, 20666. Retrieved from

https://doi.org/10.1038/srep20666

Andersen, P., & Petersen, N. C. (1993). A Procedure for Ranking Efficient Units in Data Envelopment Analysis. Management Science, 39(10), 1261–1264.

https://doi.org/10.1287/mnsc.39.10.1261

Baccelli, F., & Hong, D. (2002). AIMD, fairness and fractal scaling of TCP traffic. In Proceedings.Twenty-First Annual Joint Conference of the IEEE Computer and Communications Societies (Vol. 1, pp. 229–238 vol.1).

https://doi.org/10.1109/INFCOM.2002.1019264

Banker, R. D., Charnes, A., & Cooper, W. W. (1984). Some models for estimating technical and scale inefficiencies in data envelopment analysis. Management Science, 30(9), 1078–1092. https://doi.org/10.1287/mnsc.30.9.1078

Banker, R. D., Cooper, W. W., Seiford, L. M., Thrall, R. M., & Zhu, J. (2004). Returns to scale in different DEA models. European Journal of Operational Research, 154(2), 345–362. https://doi.org/https://doi.org/10.1016/S0377-2217(03)00174-7

Banker, R. D., & Maindiratta, A. (1986). Piecewise Loglinear Estimation of Efficient Production Surfaces. Manage. Sci., 32(1), 126–135.

https://doi.org/10.1287/mnsc.32.1.126

Banker, R. D., & Morey, R. C. (1986). Efficiency Analysis for Exogenously Fixed Inputs and Outputs. Oper. Res., 34(4), 513–521. https://doi.org/10.1287/opre.34.4.513 Barat Zadeh Joveini, M., Sadri, J., & Alavi Khoushhal, H. (2018). Fractal Modeling of Big

Data Networks.

Bez, N., & Bertrand, S. (2011). The duality of fractals: Roughness and self-similarity. Theoretical Ecology, 4(3), 371–383. https://doi.org/10.1007/s12080-010-0084-y Bui, T. (2015). Analysis of Docker Security. Computing Research Repository,

abs/1501.0, 7. Retrieved from http://arxiv.org/abs/1501.02967

Campbell, P., & Abhyankar, S. (1978). Fractals, form, chance and dimension. The Mathematical Intelligencer, 1(1), 35–37. https://doi.org/10.1007/BF03023043 Casado, M., Koponen, T., Ramanathan, R., & Shenker, S. (2010). Virtualizing the

Network Forwarding Plane. In Proceedings of the Workshop on Programmable Routers for Extensible Services of Tomorrow (p. 8:1--8:6). New York, NY, USA: ACM. https://doi.org/10.1145/1921151.1921162

Chakraborty, D., Ashir, A., Suganuma, T., Mansfield Keeni, G., Roy, T. K., & Shiratori, N. (2004). Self-similar and fractal nature of Internet traffic. International Journal of Network Management, 14(2), 119–129. https://doi.org/10.1002/nem.512

Charnes, A., Clark, C. T., Cooper, W. W., & Golany, B. (1984). A developmental study of data envelopment analysis in measuring the efficiency of maintenance units in the U.S. air forces. Annals of Operations Research, 2(1), 95–112.

Charnes, A., Cooper, W. W., & Rhodes, E. (1978). Measuring the efficiency of decision making units. European Journal of Operational Research, 2(6), 429–444.

https://doi.org/10.1016/0377-2217(78)90138-8

Charnes, A., Gallegos, A., & Li, H. (1996). Robustly efficient parametric frontiers via Multiplicative DEA for domestic and international operations of the Latin American airline industry. European Journal of Operational Research, 88(3), 525–536. https://doi.org/https://doi.org/10.1016/0377-2217(94)00216-9

Chowdhury, N. M. M. K., & Boutaba, R. (2010). A survey of network virtualization. Computer Networks, 54(5), 862–876. https://doi.org/10.1016/j.comnet.2009.10.017 Cook, W. D., & Zhu, J. (2014). DEA Cobb–Douglas frontier and cross-efficiency. Journal

of the Operational Research Society, 65(2), 265–268. https://doi.org/10.1057/jors.2013.13

Cook, W. D., & Zhu, J. (2015). DEA cross efficiency. In International Series in Operations Research and Management Science (Vol. 221, pp. 23–43). https://doi.org/10.1007/978-1-4899-7553-9_2

Cooper, W. W., Seiford, L. M., & Tone, K. (2007). Data envelopment analysis: A

comprehensive text with models, applications, references and DEA-solver software: Second edition. Data Envelopment Analysis: A Comprehensive Text with Models, Applications, References and DEA-Solver Software: Second Edition.

https://doi.org/10.1007/978-0-387-45283-8

Cronkite-Ratcliff, B., Bergman, A., Vargaftik, S., Ravi, M., McKeown, N., Abraham, I., & Keslassy, I. (2016). Virtualized Congestion Control. In Proceedings of the 2016

ACM SIGCOMM Conference (pp. 230–243). New York, NY, USA: ACM.

https://doi.org/10.1145/2934872.2934889

Crovella, M. E., & Bestavros, A. (1997). Self-similarity in World Wide Web traffic: evidence and possible causes. IEEE/ACM Transactions on Networking, 5(6), 835– 846. https://doi.org/10.1109/90.650143

Daqing, L., Kosmidis, K., Bunde, A., & Havlin, S. (2011). Dimension of spatially embedded networks. Nature Physics, 7, 481. Retrieved from

https://doi.org/10.1038/nphys1932

Dauphiné, A. (2013). A Fractal World. In Fractal Geography (pp. 1–19). John Wiley & Sons, Inc. https://doi.org/10.1002/9781118603178.ch1

de Carvalho Ferreira, C. M., & Provezano Gomes. (2009). Introdução à Análise Envoltória de Dados (1st ed.). Editora UFV. Retrieved from

https://editoraufv.com.br/produto/1591265/introducao-a-analise-envoltoria-de- dados

de Lima, A. B., & de Almeida Amazonas, J. R. (2013). Internet Teletraffic Modeling and Estimation. Wharton, TX, USA: River Publishers.

Dua, R., Raja, A. R., & Kakadia, D. (2014). Virtualization vs containerization to support PaaS. In Proceedings - 2014 IEEE International Conference on Cloud Engineering, IC2E 2014 (pp. 610–614). https://doi.org/10.1109/IC2E.2014.41

Emrouznejad, A., & Amin, G. R. (2009). DEA models for ratio data: Convexity consideration. Applied Mathematical Modelling, 33(1), 486–498.

https://doi.org/https://doi.org/10.1016/j.apm.2007.11.018

Emrouznejad, A., & Cabanda, E. (2010). An aggregate measure of financial ratios using a multiplicative DEA model. International Journal of Financial Services

Management, 4(2), 114–126. Retrieved from

https://econpapers.repec.org/RePEc:ids:ijfsmg:v:4:y:2010:i:2:p:114-126

Emrouznejad, A., Cabanda, E., & Gholami, R. (2010). An alternative measure of the ICT-Opportunity Index. Information & Management, 47(4), 246–254.

https://doi.org/https://doi.org/10.1016/j.im.2010.04.002

Emrouznejad, A., Rostami-Tabar, B., & Petridis, K. (2016). A novel ranking procedure for forecasting approaches using Data Envelopment Analysis. Technological Forecasting and Social Change, 111(Supplement C), 235–243.

https://doi.org/https://doi.org/10.1016/j.techfore.2016.07.004

Emrouznejad, A., Rostamy-Malkhalifeh, M., Hatami-Marbini, A., & Tavana, M. (2012). General and multiplicative non-parametric corporate performance models with interval ratio data. Applied Mathematical Modelling, 36(11), 5506–5514. https://doi.org/https://doi.org/10.1016/j.apm.2011.12.040

Emrouznejad, A., & Witte, K. De. (2010). COOPER-framework: A unified process for non-parametric projects. European Journal of Operational Research, 207(3), 1573– 1586. https://doi.org/https://doi.org/10.1016/j.ejor.2010.07.025

Emrouznejad, A., & Yang, G. liang. (2017). A survey and analysis of the first 40 years of scholarly literature in DEA: 1978-2016. Socio-Economic Planning Sciences.

https://doi.org/10.1016/j.seps.2017.01.008

Fernandes, N. C., Moreira, M. D. D., Moraes, I. M., Ferraz, L. H. G., Couto, R. S., Carvalho, H. E. T., … Duarte, O. C. M. B. (2011). Virtual networks: Isolation, performance, and trends. Annales Des Telecommunications/Annals of

Telecommunications, 66(5–6), 339–355. https://doi.org/10.1007/s12243-010-0208- 9

Fernandez-Palacin, F., Lopez-Sanchez, M. A., & Munoz-Márques, M. (2018). STEPWISE SELECTION OF VARIABLES IN DEA USING CONTRIBUTION LOADS. Pesquisa Operacional, 38, 31–52. Retrieved from

http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0101- 74382018000100031&nrm=iso

Florindo, J. B., & Bruno, O. M. (2013). Texture analysis by multi-resolution fractal descriptors. Expert Systems with Applications, 40(10), 4022–4028.

https://doi.org/https://doi.org/10.1016/j.eswa.2013.01.007

Førsund, F. R. (1996). On the calculation of the scale elasticity in DEA models. Journal of Productivity Analysis, 7(2), 283–302. https://doi.org/10.1007/BF00157045 Gilbert, E. N. (1960). Capacity of a burst-noise channel. The Bell System Technical

Journal, 39(5), 1253–1265. https://doi.org/10.1002/j.1538-7305.1960.tb03959.x Gneiting, T., Sevčíková, H., & Percival, D. B. (2012). Estimators of Fractal Dimension:

Assessing the Roughness of Time Series and Spatial Data. Statistical Science Donald B. Percival Is Principal Mathematician Applied Physics Laboratory, 27(2), 247–277. https://doi.org/10.1214/11-STS370

Ha, S., Lopez-Pacheco, D., & Urvoy-Keller, G. (2013). Networking in a virtualized environment: The TCP case. In 2013 IEEE 2nd International Conference on Cloud Networking (CloudNet) (pp. 50–57).

https://doi.org/10.1109/CloudNet.2013.6710557

Hall, P., & Roy, R. (1994). On the Relationship Between Fractal Dimension and Fractal Index for Stationary Stochastic Processes. The Annals of Applied Probability, 4(1), 241–253. Retrieved from http://www.jstor.org/stable/2245054

He, Y. M., Wang, B. M., & Qiao, D. J. (2012). Application in Anomaly Detection of Network Traffic Based on Fractal Technology. Applied Mechanics and Materials, 195–196, 987–991. https://doi.org/10.4028/www.scientific.net/AMM.195-196.987 Hill, B. M. (1975). A Simple General Approach to Inference About the Tail of a

Distribution. Ann. Statist., 3(5), 1163–1174. https://doi.org/10.1214/aos/1176343247

HURST, H. E. (1951). LONG-TERM STORAGE CAPACITY OF RESERVOIRS. TRANSACTIONS OF THE AMERICAN SOCIETY OF CIVIL ENGINEERS, 116, 770–799. https://doi.org/10.1119/1.18629

Iqbal, M., Naeem, M., Anpalagan, A., Qadri, N. N., & Imran, M. (2016). Multi-objective optimization in sensor networks: Optimization classification, applications and solution approaches. Computer Networks, 99, 134–161.

https://doi.org/https://doi.org/10.1016/j.comnet.2016.01.015

Jain, R. (1991). The art of computer systems performance analysis - techniques for experimental design, measurement, simulation, and modeling. Wiley.

Jenkins, L., & Anderson, M. (2003). A multivariate statistical approach to reducing the number of variables in data envelopment analysis. European Journal of Operational Research, 147(1), 51–61. https://doi.org/https://doi.org/10.1016/S0377-

2217(02)00243-6

Kaklauskas, L., & Sakalauskas, L. (2009). Application of Chaos Theory to Analysis of Computer Network Traffic.

Kang, H., Le, M., & Tao, S. (2016). Container and microservice driven design for cloud infrastructure DevOps. In Proceedings - 2016 IEEE International Conference on Cloud Engineering, IC2E 2016: Co-located with the 1st IEEE International Conference on Internet-of-Things Design and Implementation, IoTDI 2016 (pp. 202–211). https://doi.org/10.1109/IC2E.2016.26

Kantelhardt, J. W. (2008). Fractal and Multifractal Time Series. Encyclopedia of Complexity and Systems Science, 59.

https://doi.org/10.1007/SpringerReference_60393

Khan, A., Zugenmaier, A., Jurca, D., & Kellerer, W. (2012). Network virtualization: a hypervisor for the Internet? IEEE Communications Magazine, 50(1), 136–143. https://doi.org/10.1109/MCOM.2012.6122544

Leland, W. E., Taqqu, M. S., & Wilson, D. V. (1994). On the Self-Similar Nature of Ethernet Traffic (Extended Version). IEEE/ACM Transactions on Networking, 2(1), 1–15. https://doi.org/10.1109/90.282603

Nature, 433(7023), 312–316. https://doi.org/10.1038/nature03204

Lilja, D. J. (2000). Measuring Computer Performance: A Practitioner’s Guide. Cambridge University Press. https://doi.org/10.1017/CBO9780511612398

Lins, M. P. E., & Calôba, G. M. (2006). Programação linear: com aplicações em teoria dos jogos e avaliação de desempenho (data envelopment analysis). Interci{ê}ncia. Retrieved from https://books.google.com.br/books?id=SFxSSAAACAAJ

Liu, J. (2019). Fractal Network Traffic Analysis with Applications.

Liu, W., Yan, Y., Tang, D., & Tang, R. (2012). Self-Similarity and Heavy-Tail of {ICMP} Traffic. JCP, 7(12), 2948–2954. https://doi.org/10.4304/jcp.7.12.2948-2954

Lloyd, C. D., Berberoglu, S., Curran, P. J., & Atkinson, P. M. (2004). A comparison of texture measures for the per-field classification of Mediterranean land cover. International Journal of Remote Sensing, 25(19), 3943–3965.

https://doi.org/10.1080/0143116042000192321

López-Ortega, O., & López-Popa, S. I. (2012). Fractals, fuzzy logic and expert systems to assist in the construction of musical pieces. Expert Systems with Applications, 39(15), 11911–11923. https://doi.org/https://doi.org/10.1016/j.eswa.2012.02.089 Mandelbrot, B. (1965). Self-Similar Error Clusters in Communication Systems and the

Concept of Conditional Stationarity. Communication Technology, IEEE

Transactions On, 13(1), 71–90. https://doi.org/10.1109/TCOM.1965.1089090 Mandelbrot, B. (1967). How Long Is the Coast of Britain? Statistical Self-Similarity and

Fractional Dimension. Science, 156(3775), 636–638. https://doi.org/10.1126/science.156.3775.636

Mandelbrot, B. B. (1975). Stochastic Models for the Earth’s Relief, the Shape and the Fractal Dimension of the Coastlines, and the Number-Area Rule for Islands.

Proceedings of the National Academy of Sciences of the United States of America, 72(10), 3825–3828. Retrieved from http://www.jstor.org/stable/65184

Mandelbrot, B. B. (1982). The Fractal Geometry of Nature. 1997. Retrieved from https://books.google.com.br/books?id=SWcPAQAAMAAJ

Mandelbrot, B. B., & Taleb, N. N. (2012). mild vs wild randomness focusing on those risks that matter. In the Known, the Unknown and the Unknowable in Financial Risk Management : Measurement and Theory Advancing Practice.

https://doi.org/10.1017/CBO9781107415324.004

Mandelbrot, B. B., & Wallis, J. R. (1969). Computer Experiments with Fractional Gaussian Noises: Part 2, Rescaled Ranges and Spectra. Water Resources Research, 5(1), 242–259. https://doi.org/10.1029/WR005i001p00242

Martín de Diego, I., Siordia, O. S., Fernández-Isabel, A., Conde, C., & Cabello, E. (2019). Subjective data arrangement using clustering techniques for training expert systems. Expert Systems with Applications, 115, 1–15.

https://doi.org/https://doi.org/10.1016/j.eswa.2018.07.058

Millan, G., Juan, E. S., & Jamett, M. (2014). A simple estimator of the Hurst exponent for self-similar traffic flows. IEEE Latin America Transactions, 12(8), 1349–1354. https://doi.org/10.1109/TLA.2014.7014500

Morabito, R., Kjällman, J., & Komu, M. (2015). Hypervisors vs. lightweight virtualization: A performance comparison. In Proceedings - 2015 IEEE International Conference on Cloud Engineering, IC2E 2015 (pp. 386–393).

https://doi.org/10.1109/IC2E.2015.74

Nakanishi, Y. J., & Falcocchio, J. C. (2004). PERFORMANCE ASSESSMENT OF INTELLIGENT TRANSPORTATION SYSTEMS USING DATA ENVELOPMENT ANALYSIS. Research in Transportation Economics, 8, 181–197.

https://doi.org/https://doi.org/10.1016/S0739-8859(04)08009-6

Ni, L.-P., Ni, Z.-W., & Gao, Y.-Z. (2011). Stock trend prediction based on fractal feature selection and support vector machine. Expert Systems with Applications, 38(5), 5569–5576. https://doi.org/https://doi.org/10.1016/j.eswa.2010.10.079

Olesen, O. B., Petersen, N. C., & Podinovski, V. V. (2015). Efficiency analysis with ratio measures. European Journal of Operational Research, 245(2), 446–462.

https://doi.org/https://doi.org/10.1016/j.ejor.2015.03.013

Olesen, O. B., Petersen, N. C., & Podinovski, V. V. (2017). Efficiency measures and computational approaches for data envelopment analysis models with ratio inputs and outputs. European Journal of Operational Research, 261(2), 640–655.

https://doi.org/https://doi.org/10.1016/j.ejor.2017.02.021

Oliveira, C., Kim, J. B., & Suda, T. (2003). Long-range dependence in IEEE 802.11b wireless LAN traffic: an empirical study. In 2002 14th International Conference on Ion Implantation Technology Proceedings (IEEE Cat. No.02EX505) (pp. 17–23). https://doi.org/10.1109/CCW.2003.1240784

Paxson, V., & Floyd, S. (1995). Wide Area Traffic: The Failure of Poisson Modeling. IEEE/ACM Transactions on Networking, 3(3), 226–244.

https://doi.org/10.1109/90.392383

Popek, G. J., & Goldberg, R. P. (1974). Formal Requirements for Virtualizable Third Generation Architectures. Commun. ACM, 17(7), 412–421.

https://doi.org/10.1145/361011.361073

Przystalski, K., & Ogorzałek, M. J. (2017). Multispectral skin patterns analysis using fractal methods. Expert Systems with Applications, 88, 318–326.

https://doi.org/https://doi.org/10.1016/j.eswa.2017.07.011

Rastogi, V., Niddodi, C., Mohan, S., & Jha, S. (2017). New Directions for Container Debloating. In Proceedings of the 2017 Workshop on Forming an Ecosystem Around Software Transformation (pp. 51–56). New York, NY, USA: ACM. https://doi.org/10.1145/3141235.3141241

Rathore, M. (2013). KVM vs. LXC: Comparing Performance and Isolation of Hardware- assisted Virtual Routers. American Journal of Networks and Communications, 2, 88.

Rathore, M. S., Hidell, M., & Sjödin, P. (2011). Data plane optimization in open virtual routers. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6640 LNCS, pp. 379–392). https://doi.org/10.1007/978-3-642-20757-0_30

Rizo, L., Torres, D., Dehesa, J., & Munoz, D. (2008). Cauchy Distribution for Jitter in IP Networks. https://doi.org/10.1109/CONIELECOMP.2008.39

Rosenblum, M., & Garfinkel, T. (2005). Virtual machine monitors: current technology and future trends. Computer, 38(5), 39–47. https://doi.org/10.1109/MC.2005.176 Sahoo, J., Mohapatra, S., & Lath, R. (2010). Virtualization: A survey on concepts,

taxonomy and associated security issues. In 2nd International Conference on Computer and Network Technology, ICCNT 2010 (pp. 222–226).

https://doi.org/10.1109/ICCNT.2010.49

Seiford, L., Charnes, A., W. Cooper, W., & A. Stutz, J. (1982). A Multiplicative Model for Efficiency Analysis. Socio-Economic Planning Sciences, 16, 223–224.

Seiford, L. M., & Zhu, J. (1999). Infeasibility of super-efficiency data envelopment analysis models. Infor, 37(2), 174–187.

https://doi.org/Http://Dx.Doi.Org/10.1080/03155986.1999.11732379

SMITH, R. D. (2011). THE DYNAMICS OF INTERNET TRAFFIC: SELF-SIMILARITY, SELF-ORGANIZATION, AND COMPLEX PHENOMENA. Advances in Complex Systems, 14(06), 905–949. https://doi.org/10.1142/S0219525911003451

Soltesz, S., Pötzl, H., Fiuczynski, M. E., Bavier, A., & Peterson, L. (2007). Container- based operating system virtualization: a scalable, high-performance alternative to hypervisors. ACM SIGOPS Operating Systems Review, 41(3), 275.

https://doi.org/10.1145/1272998.1273025

Stein, A., Shi, W., & Bijker, W. (2008). Quality Aspects in Spatial Data Mining (1st ed.). Boca Raton, FL, USA: CRC Press, Inc.

Thrall, R. M. (1996). Duality, classification and slacks in DEA. Annals of Operations Research, 66(2), 109–138. https://doi.org/10.1007/BF02187297

Valadkhani, A., Roshdi, I., & Smyth, R. (2016). A Multiplicative Environmental DEA approach to measure efficiency changes in the world’s major polluters. Energy Economics (Vol. 54). https://doi.org/10.1016/j.eneco.2015.12.018

Wang, D., Ren, C., Govindan, S., Sivasubramaniam, A., Urgaonkar, B., Kansal, A., & Vaid, K. (2013). ACE: Abstracting, characterizing and exploiting datacenter power demands. In 2013 IEEE International Symposium on Workload Characterization (IISWC) (pp. 44–55). https://doi.org/10.1109/IISWC.2013.6704669

Weron, R. (2002). Estimating long-range dependence: Finite sample properties and confidence intervals. Physica A: Statistical Mechanics and Its Applications, 312(1– 2), 285–299. https://doi.org/10.1016/S0378-4371(02)00961-5

Whaiduzzaman, M., Gani, A., Anuar, N. B., Shiraz, M., Haque, M. N., & Haque, I. T. (2014). Cloud service selection using multicriteria decision analysis. The Scientific World Journal. https://doi.org/10.1155/2014/459375

Williams, D. E. (2007). Virtualization with Xen(Tm): Including XenEnterprise, XenServer, and XenExpress: Including XenEnterprise, XenServer, and XenExpress. Syngress Publishing.

Wisitpongphan, N., & Peha, J. M. (2003). Effect of TCP on self-similarity of network traffic. In Proceedings. 12th International Conference on Computer

Communications and Networks (IEEE Cat. No.03EX712) (pp. 370–373). https://doi.org/10.1109/ICCCN.2003.1284196

Xue, M., & Harker, P. T. (2002). Note: Ranking DMUs with Infeasible Super-Efficiency DEA Models. Management Science, 48(5), 705–710.

https://doi.org/10.1287/mnsc.48.5.705.7805

Yan, W. (2005). Measuring the Histogram Feature Vector for Anomaly Network Traffic BT - Computational Intelligence and Security. In Y. Hao, J. Liu, Y.-P. Wang, Y. Cheung, H. Yin, L. Jiao, … Y.-C. Jiao (Eds.) (pp. 279–284). Berlin, Heidelberg: Springer Berlin Heidelberg.

Ye, L., Zhang, H., Shi, J., & Du, X. (2012). Verifying cloud Service Level Agreement. In

2012 IEEE Global Communications Conference (GLOBECOM) (pp. 777–782).

https://doi.org/10.1109/GLOCOM.2012.6503207

Zhao, X., Shen, L., Peng, X., & Zhao, W. (2015). Toward SLA-constrained service composition: An approach based on a fuzzy linguistic preference model and an evolutionary algorithm. Information Sciences, 316, 370–396.

https://doi.org/10.1016/J.INS.2014.11.016

Zhou, S., Han, J., & Tang, H. (2011). Fractal Traffic Analysis and Applications in Industrial Control Ethernet Network BT - Emerging Research in Artificial

Intelligence and Computational Intelligence. In H. Deng, D. Miao, F. L. Wang, & J. Lei (Eds.) (pp. 34–42). Berlin, Heidelberg: Springer Berlin Heidelberg.