article

Prioritizing the solution of cloud service selection using integrated MCDM methods under Fuzzy environment

Authors:

Rakesh Ranjan Kumar,

Chiranjeev KumarAuthors Info & Claims

The Journal of Supercomputing, Volume 73, Issue 11

Pages 4652 - 4682

https://doi.org/10.1007/s11227-017-2039-1

Published: 01 November 2017 Publication History

Abstract

Cloud service selection plays a crucial role in terms of on-demand service selection on a subscription basis. As a result of wide-range availability of cloud services with similar functionalities, it is very crucial to determine which service best addresses the user's desires and objectives. This paper aims to design a new cloud service selection model under the fuzzy environment by utilizing the analytical hierarchy process (AHP) and fuzzy technique for order preference by similarity to ideal solution (TOPSIS). The AHP method is enforced to configure the structure of cloud service selection problem and to impel the criteria weight using the pairwise comparisons, and the TOPSIS method utilizes the final ranking of the solution. In our proposed model, the non-functional quality of service requirements is taken into consideration for selecting appropriate service. Furthermore, the proposed model exploits a set of pre-defined linguistic variables, parameterized by triangular fuzzy numbers for evaluating each criteria weights. The experimental results obtained using the real-time cloud service domains prove the efficacy of our proposed model and demonstrate the effectiveness by inducing better performance, when compared against other available cloud service selection algorithms. Finally, the sensitivity analysis is persuaded to confirm the robustness of our proposed model.

References

[1]

Albayrak E, Erensal YC (2004) Using analytic hierarchy process (ahp) to improve human performance: an application of multiple criteria decision making problem. J Intell Manuf 15(4):491---503

[2]

Alhamad M, Dillon T, Chang E (2011) A trust-evaluation metric for cloud applications. Int J Mach Learn Comput 1(4):416---421

[3]

Amiri MP (2010) Project selection for oil-fields development by using the AHP and fuzzy TOPSIS methods. Expert Syst Appl 37(9):6218---6224

[4]

Ardagna D, Casale G, Ciavotta M, Pérez JF, Wang W (2014) Quality-of-service in cloud computing: modeling techniques and their applications. J Internet Serv Appl 5(1):1---17

[5]

Ballı S, Korukoğlu S (2009) Operating system selection using fuzzy ahp and topsis methods. Math Comput Appl 14(2):119---130

[6]

Buckley JJ (1985) Fuzzy hierarchical analysis. Fuzzy Sets Syst 17(3):233---247

[7]

Buyya R, Yeo CS, Venugopal S, Broberg J, Brandic I (2009) Cloud computing and emerging IT platforms: vision, hype, and reality for delivering computing as the 5th utility. Future Gener Comput Syst 25(6):599---616

Digital Library

[8]

Chahal RK, Singh S (2016) Fuzzy logic and ahp-based ranking of cloud service providers. Comput Intell Data Min 1:337---346

[9]

Chan FT, Kumar N (2007a) Global supplier development considering risk factors using fuzzy extended ahp-based approach. Omega 35(4):417---431

[10]

Chan FT, Kumar N (2007b) Global supplier development considering risk factors using fuzzy extended ahp-based approach. Omega 35(4):417---431

[11]

Chen CT, Lin CT, Huang SF (2006) A fuzzy approach for supplier evaluation and selection in supply chain management. Int J Prod Econ 102(2):289---301

[12]

Chen CT, Hung WZ, Zhang WY (2013) Using interval valued fuzzy vikor for cloud service provider evaluation and selection. In: Proceedings of the International Conference on Business and Information (BAI'13)

[13]

Chen F, Dou R, Li M, Wu H (2015) A flexible QoS-aware web service composition method by multi-objective optimization in cloud manufacturing. Comput Indus Eng 99:423---431

Digital Library

[14]

Christopher Frey H, Patil SR (2002) Identification and review of sensitivity analysis methods. Risk Anal 22(3):553---578

[15]

Dağdeviren M, Yavuz S, Kılınç N (2009) Weapon selection using the AHP and TOPSIS methods under fuzzy environment. Expert Syst Appl 36(4):8143---8151

Digital Library

[16]

Dastjerdi AV, Buyya R (2011) A taxonomy of QoS management and service selection methodologies for cloud computing. In: Wang L, Ranjan R, Chen J, Benatallah B (eds) Cloud computing: methodology, systems, and applications, vol 15. CRC Press, Boca Raton, pp 16---76

[17]

Daug deviren M, Yuksel I (2008) Developing a fuzzy analytic hierarchy process (ahp) model for behavior-based safety management. Inf Sci 178(6):1717---1733

[18]

Ertuugrul I, Karaka csouglu N (2008) Comparison of fuzzy ahp and fuzzy topsis methods for facility location selection. Int J Adv Manuf Technol 39(7):783---795

[19]

Garg SK, Versteeg S, Buyya R (2013) A framework for ranking of cloud computing services. Future Gener Comput Syst 29(4):1012---1023

Digital Library

[20]

Godse M, Mulik S (2009) An approach for selecting software-as-a-service (saas) product. In: IEEE International Conference on Cloud Computing, pp 155---158

Digital Library

[21]

Gumus AT (2009) Evaluation of hazardous waste transportation firms by using a two step fuzzy-ahp and TOPSIS methodology. Expert Syst Appl 36(2, Part 2):4067---4074

[22]

Heilig L, Lalla-Ruiz E, Voß S (2016) A cloud brokerage approach for solving the resource management problem in multi-cloud environments. Comput Indus Eng 95:16---26

Digital Library

[23]

Hwang CL, Yoon K (2012) Multiple attribute decision making: methods and applications a state-of-the-art survey, vol 186. Springer, Berlin

[24]

Hwang CL, Lai YJ, Liu TY (1993) A new approach for multiple objective decision making. Comput Oper Res 20(8):889---899

Digital Library

[25]

Jahani A, Khanli LM (2016) Cloud service ranking as a multi objective optimization problem. J Supercomput 72(5):1897---1926

Digital Library

[26]

Jatoth C, Gangadharan G, Fiore U (2016) Evaluating the efficiency of cloud services using modified data envelopment analysis and modified super-efficiency data envelopment analysis. Soft Comput.

[27]

Junior FRL, Osiro L, Carpinetti LCR (2014) A comparison between fuzzy ahp and fuzzy topsis methods to supplier selection. Appl Soft Comput 21:194---209

[28]

Karami A, Guo Z (2012) A fuzzy logic multi-criteria decision framework for selecting it service providers. In: Proceedings of the 45th Annual Hawaii International Conference on System Sciences HICSS 2012, Maui, Hawaii, 4---7 Jan 2012. IEEE Computer Society, Los Alamitos, pp 1118---1127.

[29]

Karim R, Ding C, Miri A (2013) An end-to-end QoS mapping approach for cloud service selection. In: Ninth IEEE World Congress on Services, pp 341---348

[30]

Kulak O, Kahraman C (2005) Fuzzy multi-attribute selection among transportation companies using axiomatic design and analytic hierarchy process. Inf Sci 170(2):191---210

Digital Library

[31]

Le S, Dong H, Hussain FK, Hussain OK, Ma J, Zhang Y (2014) Multicriteria decision making with fuzziness and criteria interdependence in cloud service selection. In: IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), pp 1929---1936

[32]

Lee S, Seo KK (2016) A hybrid multi-criteria decision-making model for a cloud service selection problem using bsc, fuzzy delphi method and fuzzy ahp. Wirel Pers Commun 86(1):57---75

Digital Library

[33]

Lin SY, Lai CH, Wu CH, Lo CC (2014) A trustworthy QoS-based collaborative filtering approach for web service discovery. J Syst Softw 93:217---228

[34]

Liu S, Chan FT, Ran W (2016) Decision making for the selection of cloud vendor: an improved approach under group decision-making with integrated weights and objective/subjective attributes. Expert Syst Appl 55:37---47

Digital Library

[35]

McKendrick J (2006) Ten companies where SOA made a difference in 2006. http://www.zdnet.com/article/ten-companies-where-soa-made-a-difference-in-2006/

[36]

Önüt S, Soner S (2008) Transshipment site selection using the ahp and topsis approaches under fuzzy environment. Waste Manag 28(9):1552---1559

[37]

Roy B (1991) The outranking approach and the foundations of electre methods. Theory Decis 31(1):49---73

[38]

Saltelli A, Chan K, Scott EM (2000) Sensitivity analysis, vol 1. Wiley, New York

[39]

Satty TL (1980) The analytic hierarchy process. McGraw-Hill, New York

[40]

Shiraz M, Gani A, Khokhar RH, Buyya R (2013) A review on distributed application processing frameworks in smart mobile devices for mobile cloud computing. IEEE Commun Surv Tutor 15(3):1294---1313

[41]

Shyur HJ, Shih HS (2006) A hybrid MCDM model for strategic vendor selection. Math Comput Modell 44(7):749---761

Digital Library

[42]

Sidhu J, Singh S (2017) Improved TOPSIS method based trust evaluation framework for determining trustworthiness of cloud service providers. J Grid Comput 15:81---105.

Digital Library

[43]

Sodhi B, Prabhakar TV (2012) A simplified description of Fuzzy TOPSIS. arXiv preprint arXiv:1205.5098

[44]

Sun L, Dong H, Hussain FK, Hussain OK, Chang E (2014) Cloud service selection: state-of-the-art and future research directions. J Netw Comput Appl 45:134---150

Digital Library

[45]

Sun L, Ma J, Zhang Y, Dong H, Hussain FK (2016) Cloud-FuSeR: fuzzy ontology and MCDM based cloud service selection. Future Gener Comput Syst 57:42---55

Digital Library

[46]

Supriya M, Sangeeta K, Patra G (2016) Trustworthy cloud service provider selection using multi criteria decision making methods. Eng Lett 24(1):1---10

[47]

Tran VX, Tsuji H, Masuda R (2009) A new qos ontology and its QoS-based ranking algorithm for web services. Simul Model Pract Theory 17(8):1378---1398

[48]

ur Rehman Z, Hussain OK, Hussain FK (2012) IaaS cloud selection using MCDM methods. In: Ninth IEEE International Conference on e-Business Engineering (ICEBE), pp 246---251

[49]

ur Rehman Z, Hussain OK, Hussain FK (2014) Parallel cloud service selection and ranking based on QoS history. Int J Parallel Progr 42(5):820---852

Digital Library

[50]

Wang E (2015) Benchmarking whole-building energy performance with multi-criteria technique for order preference by similarity to ideal solution using a selective objective-weighting approach. Appl Energy 146:92---103

[51]

Wang JJ, Yang DL (2007) Using a hybrid multi-criteria decision aid method for information systems outsourcing. Comput Oper Res 34(12):3691---3700

Digital Library

[52]

Wang P (2009) QoS-aware web services selection with intuitionistic fuzzy set under consumer's vague perception. Expert Syst Appl 36(3):4460---4466

Digital Library

[53]

Whaiduzzaman M, Gani A, Anuar NB, Shiraz M, Haque MN, Haque IT (2014) Cloud service selection using multicriteria decision analysis. Sci World J 2014.

[54]

Yang T, Hung CC (2007) Multiple-attribute decision making methods for plant layout design problem. Robot Comput Integr Manuf 23(1):126---137

Digital Library

[55]

Yu X, Guo S, Guo J, Huang X (2011) Rank B2C e-commerce websites in e-alliance based on AHP and fuzzy TOPSIS. Expert Syst Appl 38(4):3550---3557

Digital Library

[56]

Zadeh LA (1965) Fuzzy sets. Inf Control 8(3):338---353

[57]

Zeleny M, Cochrane JL (1973) Multiple criteria decision making. University of South Carolina Press, Columbia

[58]

(2014) Selecting a Cloud Provider. http://spark.adobe.com/page/PN39b/

[59]

(2016) Cloud Harmony Reports. http://static.lindsberget.se/state-of-the-cloud-compute-0714.pdf. Online, Accessed 12 May 2016

Cited By

Alshahrani RYenugula MAlgethami HAlharbi FShubhra Goswami SNoorulhasan Naveed QLasisi AIslam SKhan NZahmatkesh S(2024)Establishing the fuzzy integrated hybrid MCDM framework to identify the key barriers to implementing artificial intelligence-enabled sustainable cloud system in an IT industryExpert Systems with Applications: An International Journal10.1016/j.eswa.2023.121732238:PAOnline publication date: 15-Mar-2024
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Nabli HBen Djemaa RAmous Ben Amor I(2024)Improved clustering-based hybrid recommendation system to offer personalized cloud servicesCluster Computing10.1007/s10586-023-04119-227:3(2845-2874)Online publication date: 1-Jun-2024
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cover image The Journal of Supercomputing

The Journal of Supercomputing Volume 73, Issue 11

November 2017

469 pages

ISSN:0920-8542

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Copyright © Copyright © 2017 Springer Science+Business Media, LLC.

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Kluwer Academic Publishers

United States

Publication History

Published: 01 November 2017

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Cited By

Alshahrani RYenugula MAlgethami HAlharbi FShubhra Goswami SNoorulhasan Naveed QLasisi AIslam SKhan NZahmatkesh S(2024)Establishing the fuzzy integrated hybrid MCDM framework to identify the key barriers to implementing artificial intelligence-enabled sustainable cloud system in an IT industryExpert Systems with Applications: An International Journal10.1016/j.eswa.2023.121732238:PAOnline publication date: 15-Mar-2024
https://dl.acm.org/doi/10.1016/j.eswa.2023.121732
Nabli HBen Djemaa RAmous Ben Amor I(2024)Improved clustering-based hybrid recommendation system to offer personalized cloud servicesCluster Computing10.1007/s10586-023-04119-227:3(2845-2874)Online publication date: 1-Jun-2024
https://dl.acm.org/doi/10.1007/s10586-023-04119-2
Krisnawijaya NTekinerdogan BCatal Cvan der Tol R(2023)Multi-Criteria decision analysis approach for selecting feasible data analytics platforms for precision farmingComputers and Electronics in Agriculture10.1016/j.compag.2023.107869209:COnline publication date: 1-Jun-2023
https://dl.acm.org/doi/10.1016/j.compag.2023.107869
Zayat WKilic HYalcin AZaim SDelen D(2023)Application of MADM methods in Industry 4.0Computers and Industrial Engineering10.1016/j.cie.2023.109075177:COnline publication date: 1-Mar-2023
https://dl.acm.org/doi/10.1016/j.cie.2023.109075
Ghorui NMondal SChatterjee BGhosh APal ADe DGiri B(2023)Selection of cloud service providers using MCDM methodology under intuitionistic fuzzy uncertaintySoft Computing - A Fusion of Foundations, Methodologies and Applications10.1007/s00500-022-07772-827:5(2403-2423)Online publication date: 17-Jan-2023
https://dl.acm.org/doi/10.1007/s00500-022-07772-8
Seh AAhmad MNadeem MPandey AAgrawal AKumar RKhan R(2022)Usable-Security Assessment of Healthcare Software System Through Fuzzy ANP-TOPSIS MethodInternational Journal of System Dynamics Applications10.4018/IJSDA.30444410:4(1-24)Online publication date: 24-Jun-2022
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Neeraj Garg NNavadia NLakhanpal AGupta IIbrahim WRaj M(2022)CloudConsumerismMobile Information Systems10.1155/2022/59609762022Online publication date: 1-Jan-2022
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Hussain AChun J(2022)Cloud service scrutinization and selection framework (C3SF)Information Sciences: an International Journal10.1016/j.ins.2021.11.024586:C(155-175)Online publication date: 1-Mar-2022
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Hussain AChun JKhan M(2022)A novel customer-centric Methodology for Optimal Service Selection (MOSS) in a cloud environmentFuture Generation Computer Systems10.1016/j.future.2019.12.024105:C(562-580)Online publication date: 21-Apr-2022
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Gireesha OKamalesh AKrithivasan KShankar Sriram V(2022)A Fuzzy-Multi Attribute Decision Making approach for efficient service selection in cloud environmentsExpert Systems with Applications: An International Journal10.1016/j.eswa.2022.117526206:COnline publication date: 15-Nov-2022
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