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International Journal of Sensors, Wireless Communications and Control

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ISSN (Print): 2210-3279
ISSN (Online): 2210-3287

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Research Article

Intuitionistic Fuzzy Score Function Based Multi-Criteria Decision Making Method for Selection of Cloud Service Provider

Author(s): Sonal Agrawal* and Pradeep Tripathi

Volume 10, Issue 4, 2020

Page: [533 - 539] Pages: 7

DOI: 10.2174/2210327910666191220102849

Price: $65

Abstract

Aims & Background: Cloud Computing (CC) has received great attention from the scholarly researchers and IT companies. CC is a standard that offers services through the Internet. The standard has been manipulated by existing skills (such as collect, peer-to-peer and grid computing) and currently accepted by approximately all major associations. Various associations like as Microsoft and Facebook have revealed momentous investments in CC and currently offer services with top levels of reliability. The well-organized and precise evaluation of cloud-based communication network is an essential step in assurance both the business constancy and the continuous open services.

Objectives & Methods: To select and rank the CC service providers, we introduce an Improved Score Function (ISF) based Multi-Criteria Decision-Making (MCDM) approach. The proposed approach is developed to solve the MCDM problems with partly unknown weight. To do this, the criteria preferences are given in terms of Intuitionistic Fuzzy Sets (IFSs). Numerical example is illustrated to show the effectiveness of the proposed approach over the previous ones.

Results: A decision making problem of cloud computing service provider has been considered for signifying the developed technique and finishes with the outcomes coincide with the already developed methods which confirms the solidity of the developed method.

Conclusion: For future, we plan to implement the proposed technique on various decision making problems, clustering and multi-objective problems. Also, we plan to extend our method under different uncertain atmosphere by using other MCDM methods.

Keywords: Cloud computing, intuitionistic fuzzy sets, MCDM, score function, multi-criteria decision-making, multi-objective problems.

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[1]
Mell P, Grance T. The nist definition of cloud computing. Natl Inst Stand Technol 2009; 53(6): 50.
[2]
Murugesan S, Bojanova I. Cloud services and service providers. Wiley-IEEE Press 2016.
[3]
Sadiku M, Musa S, Momoh O. Cloud computing: Opportunities and challenges. IEEE Potentials 2014; 33(1): 34-6.
[http://dx.doi.org/10.1109/MPOT.2013.2279684]
[4]
Bauer E, Adams R. Reliability and availability of cloud computing. Wiley-IEEE Press 2012.
[http://dx.doi.org/10.1002/9781118393994]
[5]
Bosse S, Splieth M, Turowski K. Multi-objective optimization of IT service availability and costs. Reliab Eng Syst Saf 2016; 147: 142-55.
[http://dx.doi.org/10.1016/j.ress.2015.11.004]
[6]
Ding S, Xia C, Wang C, Wu D, Zhang Y. Multi-objective optimization based ranking prediction for cloud service recommendation. Decis Support Syst 2017; 101: 106-14.
[http://dx.doi.org/10.1016/j.dss.2017.06.005]
[7]
Kabir S. An overview of fault tree analysis and its application in model based dependability analysis. Expert Syst Appl 2017; 77: 114-35.
[http://dx.doi.org/10.1016/j.eswa.2017.01.058]
[8]
Maciel P. Modeling availability impact in cloud computing. Cham: Springer International Publishing 2016.
[9]
Bauer E, Adams R. Service availability measurement. Wiley-IEEE Press 2014.
[10]
Dai W, Qiu L, Wu A, Qiu M. Cloud infrastructure resource allocation for big data applications. IEEE Trans Big Data 2017; 99: 1-1.
[11]
Melo C, Matos R, Dantas J, Maciel P. Capacity-oriented availability model for resources estimation on private cloud infrastructure. IEEE 22nd Pacific Rim International Symposium on Dependable Computing (PRDC). Christchurch, New Zealand 2017.
[http://dx.doi.org/10.1109/PRDC.2017.49]
[12]
Upadhyay N. Managing cloud service evaluation and selection. Procedia Comput Sci 2017; 122: 1061-8.
[13]
Zadeh LA. Fuzzy sets. Inf Control 1965; 8: 338-53.
[http://dx.doi.org/10.1016/S0019-9958(65)90241-X]
[14]
Atanassov KT. Intuitionistic fuzzy sets. Fuzzy Sets Syst 1986; 20(1): 87-96.
[http://dx.doi.org/10.1016/S0165-0114(86)80034-3]
[15]
Li DF. Multi-attribute decision making models and methods using intuitionistic fuzzy sets. J Comput Syst Sci 2005; 70: 73-85.
[http://dx.doi.org/10.1016/j.jcss.2004.06.002]
[16]
Xu ZS, Yager RR. Some geometric aggregation operators based on intuitionistic fuzzy sets. Int J Gen Syst 2006; 35: 417-33.
[http://dx.doi.org/10.1080/03081070600574353]
[17]
Xu ZS. Intuitionistic fuzzy aggregation operators. IEEE Trans Fuzzy Syst 2007; 15: 1179-87.
[http://dx.doi.org/10.1109/TFUZZ.2006.890678]
[18]
Mishra AR. Intuitionistic fuzzy information with application in rating of township development. Iran J Fuzzy Syst 2016; 13: 49-70.
[19]
Mishra AR, Rani P, Jain D. Information measures based TOPSIS method for multicriteria decision making problem in intuitionistic fuzzy environment. Iran J Fuzzy Syst 2017; 14(6): 41-63.
[20]
Kumari R, Mishra AR, Sharma DK. Intuitionistic fuzzy Shapley-TOPSIS method for multi-criteria decision making problems based on information measures. Recent Pat Comput Sci 2019.
[http://dx.doi.org/10.2174/2213275912666190115162832]
[21]
Mishra AR, Singh RK, Motwani D. Intuitionistic fuzzy divergence measure-based ELECTRE method for performance of cellular mobile telephone service providers. Neural Comput Appl 2018; 2018: 1-21.
[22]
Mishra AR, Rani P. Biparametric information measures based TODIM technique for interval-valued intuitionistic fuzzy environment. Arab J Sci Eng 2018; 43(6): 3291-309.
[http://dx.doi.org/10.1007/s13369-018-3069-6]
[23]
Rani P, Jain D, Hooda DS. Extension of intuitionistic fuzzy TODIM technique for multi-criteria decision making method based on Shapley weighted divergence measure. Granul Comput 2018; 4: 407-20.
[24]
Mishra AR, Rani P. Shapley divergence measures with VIKOR method for multi-attribute decision making problems. Neural Comput Appl 2017; 31: 1299-316.
[25]
Rani P, Jain D, Hooda DS. Shapley function based interval valued intuitionistic fuzzy VIKOR technique for correlative multi-criteria decision making problems. Iran J Fuzzy Syst 2018; 15(1): 25-54.
[26]
Rani P, Jain D. Intuitionistic fuzzy PROMETHEE technique for multi-criteria decision making problems based on entropy measure 2017.
[http://dx.doi.org/10.1007/978-981-10-5427-3_31]
[27]
Mishra AR, Singh RK, Motwani D. Multi-criteria assessment of cellular mobile telephone service providers using intuitionistic fuzzy WASPAS method with similarity measures. Granul Comput 2018; 4: 511-29.
[28]
Mishra AR, Rani P. Interval-valued intuitionistic fuzzy WASPAS method: Application in reservoir flood control management policy. Group Decis Negot 2018; 27: 1047-78.
[http://dx.doi.org/10.1007/s10726-018-9593-7]
[29]
Mishra AR, Rani P, Pardasani KR. Multiple-criteria decision-making for service quality selection based on Shapley COPRAS method under hesitant fuzzy sets. Granul Comput 2018; 2018: 1-19.
[30]
Mishra AR, Chandel A, Motwani D. Extended MABAC method based on divergence measures for multi-criteria assessment of programming language with interval-valued intuitionistic fuzzy sets. Granul Comput 2020; 5: 97-117.
[31]
Mishra AR, Jain D, Hooda DS. On fuzzy distance and induced fuzzy information measures. J Inf Optim Sci 2016; 37: 193-211.
[http://dx.doi.org/10.1080/02522667.2015.1103034]
[32]
Mishra AR, Jain D, Hooda DS. On logarithmic fuzzy measures of information and discrimination. J Optim Inf Sci 2016; 37: 213-23.
[http://dx.doi.org/10.1080/02522667.2015.1103041]
[33]
Mishra AR, Jain D, Hooda DS. Exponential intuitionistic fuzzy information measure with assessment of service quality. Int J Fuzzy Syst 2017; 19: 788-98.
[http://dx.doi.org/10.1007/s40815-016-0278-6]
[34]
Mishra AR, Jain D, Hooda DS. Intuitionistic fuzzy similarity and information measures with physical education teaching quality assessment. Adv Intell Syst Comput 2016; 379: 387-99.
[http://dx.doi.org/10.1007/978-81-322-2517-1_38]
[35]
Mishra AR, Kumari R, Sharma DK. Intuitionistic fuzzy divergence measure-based multi-criteria decision-making method. Neural Comput Appl 2017; 2017: 1-16.
[36]
Ansari MD, Mishra AR, Ansari FT. New Divergence and entropy measures for intuitionistic fuzzy sets on edge detection. Int J Fuzzy Syst 2018; 20(2): 474-87.
[http://dx.doi.org/10.1007/s40815-017-0348-4]
[37]
Xu GL, Wan SP, Xie XL. A Selection method based on MAGDM with interval-valued intuitionistic fuzzy sets. Math Probl Eng 2015; 2015: 1-13.
[http://dx.doi.org/10.1155/2015/365049]
[38]
Xia MM, Xu ZS. Entropy/cross entropy-based group decision making under intuitionistic fuzzy environment. Inf Fusion 2012; 13(1): 31-47.
[http://dx.doi.org/10.1016/j.inffus.2010.12.001]

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