Skip to main content
SpringerLink
Log in

An Uncertainty-Aware Cloud Service Selection Model Using CRITIC and MAUT

  • Conference paper
  • First Online:
Advances in Distributed Computing and Machine Learning

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 427))

Abstract

Cloud computing technology is escalating day by day by delivering huge benefits to its customers in the form of services. Many cloud service providers (CSPs) are available in the market and offer similar services. Therefore, it is very much challenging to select one of them that can fulfill the customer requirements. This is referred to as a multi-criteria decision-making (MCDM) problem. Here, the decision-makers (DMs) express their opinion in the initialization phase and the rest of the data is collected from other sources. But, there may be uncertainty in the data in the form of ambiguity and partial information. In this paper, we propose a cloud service selection model, called uncertainty-aware cloud service selection (UACSS), to select the best CSP, which can deal with uncertainty in the data. For this, the proposed model uses CRiteria Importance Through Intercriteria Correlation (CRITIC) and Multi-Attribute Utility Theory (MAUT). CRITIC is used for criteria weighting by considering the conflict between the evaluation criteria and eliminating the influence of the DMs in the process of decision-making. On the other hand, MAUT is used to rank the alternative by dealing with uncertainty. A case study is used to show the working and efficacy of the proposed model.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 129.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 169.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Jatoth C, Gangadharan GR, Fiore U, Buyya R (2019) SELCLOUD: a hybrid multi-criteria decision-making model for selection of cloud services. Soft Comput 23(13):4701–4715

    Google Scholar 

  2. Pande SK, Panda SK, Das S, Alazab M, Sahoo KS, Luhach AK, Nayyar A (2020) A smart cloud service management algorithm for vehicular clouds. IEEE Trans Intell Transp Syst

    Google Scholar 

  3. Alabool HM, Mahmood AK (2013) Trust-based service selection in public cloud computing using fuzzy modified Vikor method. Aust J Basic Appl Sci 7(9):211–220

    Google Scholar 

  4. Pande SK, Panda SK, Das S (2021) Dynamic service migration and resource management for vehicular clouds. J Ambient Intell Humanized Comput 12(1):1227–1247

    Google Scholar 

  5. Liu S, Chan FTS, 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

    Google Scholar 

  6. Panda SK, Jana PK (2016) Uncertainty-based QoS min–min algorithm for heterogeneous multi-cloud environment. Arabian J Sci Eng 41(8):3003–3025

    Google Scholar 

  7. Panda SK, Jana PK (2017) SLA-based task scheduling algorithms for heterogeneous multi-cloud environment. J Supercomputing 73(6):2730–2762

    Google Scholar 

  8. Liu M, Shao Y, Yu C, Yu J (2020) A heterogeneous QoS-based cloud service selection approach using entropy weight and GRA-ELECTRE III. Math Prob Eng 2020

    Google Scholar 

  9. Hussain A, Chun J, Khan M (2020) A novel framework towards viable cloud service selection as a service (CSSaaS) under a fuzzy environment. Future Generation Comput Syst 104:74–91

    Article  Google Scholar 

  10. Khoda Parast F, Sindhav C, Nikam S, Yekta HI, Kent KB, Hakak S (2021) Cloud computing security: a survey of service-based models. Comput Secur 102580

    Google Scholar 

  11. Nawaz F, Asadabadi MR, Janjua NK, Hussain OK, Chang E, Saberi M (2018) An MCDM method for cloud service selection using a Markov chain and the best-worst method. Knowledge-Based Syst 159:120–131

    Google Scholar 

  12. Somu N, Kirthivasan K, Shankar Sriram VS (2017) A rough set-based hypergraph trust measure parameter selection technique for cloud service selection. J Supercomputing 73(10):4535–4559

    Google Scholar 

  13. Kumar RR, Mishra S, Kumar C (2017) Prioritizing the solution of cloud service selection using integrated MCDM methods under fuzzy environment. J Supercomputing 73(11):4652–4682

    Google Scholar 

  14. Saha M, Panda SK, Panigrahi S (2021) A hybrid multi-criteria decision making algorithm for cloud service selection. Int J Inf Technol 13(4):1417–1422

    Google Scholar 

  15. Triantaphyllou E (2000) Multi-criteria decision making methods. Multi-criteria Decis Making Methods Comparative Study 5–21 (Springer)

    Google Scholar 

  16. Campos ACSM, Mareschal B, de Almeida AT (2015) Fuzzy flowsort: an integration of the flowsort method and fuzzy set theory for decision making on the basis of inaccurate quantitative data. Inf Sci 293:115–124

    Google Scholar 

  17. Bañuelas R, Antony* J (2004) Modified analytic hierarchy process to incorporate uncertainty and managerial aspects. Int J Prod Res 42(18):3851–3872

    Google Scholar 

  18. Liu H-W, Wang G-J (2007) Multi-criteria decision-making methods based on intuitionistic Fuzzy sets. Eur J Oper Res 179(1):220–233

    Article  Google Scholar 

  19. Pelissari R, Oliveira MC, Abackerli AJ, Ben-Amor S, Assumpção MR (2021) Techniques to model uncertain input data of multi-criteria decision-making problems: a literature review. Int Trans Oper Res 28(2):523–559

    Google Scholar 

  20. Radulescu CZ, Radulescu M (2018) Group decision support approach for cloud quality of service criteria weighting. Stud Inform Control 27(3):275–284

    Article  Google Scholar 

  21. Al-Faifi AM, Song B, Alamri A, Alelaiwi A, Xiang Y (2017) A survey on multi-criteria decision making methods for evaluating cloud computing services. J Internet Technol 18(3):473–494

    Google Scholar 

  22. Liu Y, Esseghir M, Boulahia LM et al (2016) Evaluation of parameters importance in cloud service selection using rough sets. Appl Math 7(06):527

    Google Scholar 

  23. Liu Y, Esseghir M, Boulahia LM (2014) Cloud service selection based on rough set theory. In: 2014 International conference and workshop on the network of the future (NOF). IEEE, pp 1–6

    Google Scholar 

  24. Obulaporam G, Somu N, ManiIyer Ramani GR, Boopathy AK, Vathula Sankaran SS (2018) GCRITICPA: a critic and grey relational analysis based service ranking approach for cloud service selection. In: International conference on intelligent information technologies. Springer, pp 3–16

    Google Scholar 

  25. Diakoulaki D, Mavrotas G, Papayannakis L (1995) Determining objective weights in multiple criteria problems: the critic method. Comput Oper Res 22(7):763–770

    Article  Google Scholar 

  26. Yilmaz B, Harmancioglu N (2010) Multi-criteria decision making for water resource management: a case study of the Gediz river basin, Turkey. Water SA 36(5)

    Google Scholar 

  27. Madic M, Radovanović M (2015) Ranking of some most commonly used nontraditional machining processes using rov and critic methods. UPB Sci Bull Series D 77(2):193–204

    Google Scholar 

  28. Keeney RL, Sicherman A (1976) Assessing and analyzing preferences concerning multiple objectives: an interactive computer program. Behav Sci 21(3):173–182

    Google Scholar 

  29. Dyer JS (2016) Multiattribute utility theory (MAUT). In: Multiple criteria decision analysis. Springer, pp 285–314

    Google Scholar 

  30. Zietsman J, Rilett LR, Kim S-J (2006) Transportation corridor decision-making with multi-attribute utility theory. Int J Manage Decis making 7(2–3):254–266

    Google Scholar 

  31. Wang M, Lin S-J, Lo Y-C (2010) The comparison between MAUT and promethee. In: 2010 IEEE International conference on industrial engineering and engineering management. IEEE, pp 753–757

    Google Scholar 

  32. Adali EA, Isik AT (2017) Critic and MAUT methods for the contract manufacturer selection problem. Eur J Multidisc Stud 2(5):93–101

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Veer Surendra Sai University of Technology Burla, Burla, Odisha, 768018, India

    Munmun Saha & Suvasini Panigrahi

  2. National Institute of Technology Warangal, Warangal, Telangana, 506004, India

    Sanjaya Kumar Panda

Authors
  1. Munmun Saha
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Sanjaya Kumar Panda
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Suvasini Panigrahi
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Sanjaya Kumar Panda .

Editor information

Editors and Affiliations

  1. Department of Computer Science and Engineering, National Institute of Technology, Warangal, India

    Rashmi Ranjan Rout

  2. Department of Computer Science and Engineering, Indian Institute of Technology, Kharagpur, India

    Soumya Kanti Ghosh

  3. Department of Computer Science and Engineering, Indian Institute of Technology (ISM) Dhanbad, Dhanbad, India

    Prasanta K. Jana

  4. School of IT and Engineering (SITE), Vellore Institute of Technology, Vellore, India

    Asis Kumar Tripathy

  5. Department of Computer Science and Information Technology, Institute of Technical Education and Research (ITER), Siksha ‘O’ Anusandhan Deemed to be University, Bhubaneswar, India

    Jyoti Prakash Sahoo

  6. Department of Computer Science and Information Engineering (CSIE), Providence University, Taichung, Taiwan

    Kuan-Ching Li

Rights and permissions

Reprints and permissions

Copyright information

© 2022 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Saha, M., Panda, S.K., Panigrahi, S. (2022). An Uncertainty-Aware Cloud Service Selection Model Using CRITIC and MAUT. In: Rout, R.R., Ghosh, S.K., Jana, P.K., Tripathy, A.K., Sahoo, J.P., Li, KC. (eds) Advances in Distributed Computing and Machine Learning. Lecture Notes in Networks and Systems, vol 427. Springer, Singapore. https://doi.org/10.1007/978-981-19-1018-0_21

Download citation

Publish with us

Policies and ethics

Search

Navigation