Skip to main content

Advertisement

SpringerLink
Log in

Trust level estimation for cloud service composition with inter-service constraints

  • Original Research
  • Published:
Journal of Ambient Intelligence and Humanized Computing Aims and scope Submit manuscript

Abstract

Many cloud services with similar functionalities but different quality of service (QoS) have emerged in the past few years. Thus, the composition of a set of services in order to perform a particular functionality becomes a challenge. Organizations are more and more interested in moving their information systems (IS) with their various components (data, services, business processes, etc.) to the cloud. The composition of services in a similar case is more difficult since the components of the IS have different levels of complexity. This process should not be based only on the QoS, but other factors must be considered, such as the constraints that may exist between services as well as the trustworthiness of the providers. In this paper, we introduce an approach for the composition of cloud services to deal with the above issues. We compared our approach with other algorithms that treat the same problem, in order to evaluate it. The evaluation results show that our approach returns better results that meet the non-functional requirements and respect the constraints between services while maximizing the trust level of service providers.

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

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11

Similar content being viewed by others

References

  • Ai L, Tang M (2008) A penalty-based genetic algorithm for QoS-aware web service composition with inter-service dependencies and conflicts. In: 2008 international conference on computational intelligence for modelling control and automation, CIMCA 2008. pp 738–743

  • AICPA (2017) Trust services criteria. https://www.aicpa.org/content/dam/aicpa/interestareas/frc/assuranceadvisoryservices/downloadabledocuments/trust-services-criteria.pdf. Accessed 12 Jan 2019

  • Almanea MI (2015) The role of transparency and trust in the selection of cloud service providers. Newcastle University, Newcastle upon Tyne

    Google Scholar 

  • Alrifai M, Risse T, Nejdl W (2011) A hybrid approach for efficient Web service composition with end-to-end QoS constraints. ACM Trans Web. https://doi.org/10.1145/2180861.2180864

    Article  Google Scholar 

  • Avizienis A, Laprie J-C, Randell B, Landwehr C (2004) Basic concepts and taxonomy of dependable and secure computing. IEEE Trans Dependable Secur Comput 1:11–33. https://doi.org/10.1109/TDSC.2004.2

    Article  Google Scholar 

  • Bouanaka MA, Zarour N (2013) An approach for an optimized web service selection based on skyline. Int J Comput Sci Issues 10:412–418

    Google Scholar 

  • Cao Y, Guo Z, Zhang J (2017) Weight calculation for cases generated by tacit knowledge explicit based on RS-FAHP. MATEC Web Conf. https://doi.org/10.1051/matecconf/201710005029

    Article  Google Scholar 

  • Chakraborty S, Roy K (2012) An SLA-based framework for estimating trustworthiness of a cloud. In: Proceeding of the 11th IEEE international conference on trust, security and privacy in computing and communications trust—11th IEEE international conference on ubiquitous computing and communications IUCC-2012, pp 937–942. https://doi.org/10.1109/TrustCom.2012.84

  • Chhetri MB, Goh S, Lin J et al (2007) Agent-based negotiation of service level agreements for web service compositions. In: Proceedings of the joint conference on the INFORMS section on group decision and negotiation. pp 81–93

  • Chiregi M, Navimipour NJ (2016) A new method for trust and reputation evaluation in the cloud environments using the recommendations of opinion leader’s entities and removing the effect of troll entities. Comput Human Behav. https://doi.org/10.1016/j.chb.2016.02.029

    Article  Google Scholar 

  • Cloud Security Alliance (2013) The notorious nine cloud computing top threats in 2013. https://downloads.cloudsecurityalliance.org/initiatives/top_threats/The_Notorious_Nine_Cloud_Computing_Top_Threats_in_2013.pdf. Accessed 12 Jan 2019

  • Cloud Security Alliance (2016) The treacherous 12: cloud computing top threats in 2016. https://downloads.cloudsecurityalliance.org/assets/research/top-threats/Treacherous-12_Cloud-Computing_Top-Threats.pdf. Accessed 19 Sept 2018

  • Faratin P, Sierra C, Jennings NR (2000) Using similarity criteria to make negotiation trade-offs. In: Proceedings—4th international conference on MultiAgent systems, ICMAS 2000. pp 119–126

  • Farokhi S, Jrad F, Brandic I, Streit A (2014) HS4MC: hierarchical SLA-based service selection for multi-cloud environments. In: Proceedings of the 4th international conference on cloud computing and services science (CLOSER 2014). Barcelona, Spain, pp 722–734

  • Fdhila W, Dumas M, Godart C (2010) Optimized decentralization of composite web services. In: Conference on collaborative computing: networking, applications and worksharing. pp 1–10

  • Goettelmann E, Dahman K, Gateau B et al (2014) A broker framework for secure and cost-effective business process deployment on multiple clouds. In: CAiSE 2014 Forum/Doctoral Consortium. Lecture notes in business information processing 204

  • Hajizadeh R, Jafari Navimipour N (2017) A method for trust evaluation in the cloud environments using a behavior graph and services grouping. Kybernetes. https://doi.org/10.1108/K-02-2017-0070

    Article  Google Scholar 

  • Kanpariyasoontorn J, Senivongse T (2017) Cloud service trustworthiness assessment based on cloud controls matrix. In: International conference on advanced communication technology, ICACT. pp 291–297

  • Klein A, Ishikawa F, Honiden S (2011) Efficient heuristic approach with improved time complexity for QoS-aware service composition. In: Proceedings—2011 IEEE 9th international conference on web services, ICWS 2011. pp 436–443

  • Klein A, Ishikawa F, Honiden S (2012) Towards network-aware service composition in the cloud. In: Proceedings of the 21st international conference on World Wide Web—WWW’12. pp 959–968

  • Liu B, Zhang Z (2016) QoS-aware service composition for cloud manufacturing based on the optimal construction of synergistic elementary service groups. Int J Adv Manuf Technol 88:2757–2771. https://doi.org/10.1007/s00170-016-8992-7

    Article  Google Scholar 

  • Liu Y, Esseghir M, Boulahia LM (2016) Evaluation of parameters importance in cloud service selection using rough sets. Appl Math 7:527–541

    Article  Google Scholar 

  • Lu W, Hu X, Wang S, Li X (2014) A multi-criteria QoS-aware trust service composition algorithm in cloud computing environments. Int J Grid Distrib Comput 7:77–88. https://doi.org/10.14257/ijgdc.2014.7.1.08

    Article  Google Scholar 

  • Malouche H, Ben Halima Y, Ben Ghezala H (2017) Enterprise preparation for cloud migration: assessment phase. In: 2017 IEEE/ACS 14th international conference on computer systems and applications (AICCSA). IEEE, pp 652–659

  • Nemhauser GL, Wolsey LA (1988) Integer and combinatorial optimization. Wiley-Interscience, New York

    Book  Google Scholar 

  • NIST (2013) Security and privacy controls for federal information systems and organizations. NIST Spec Publ. https://doi.org/10.6028/NIST.SP.800-53Ar4

    Article  Google Scholar 

  • Pavithra M, Mahalingam SK (2015) Trust driven workflow scheduling by composition of cloud services under fuzzy preferences of users. Int J Eng Technol Sci 2:45–50

    Google Scholar 

  • Pawlak Z (1982) Rough sets. Int J Comput Inf Sci 11:341–356. https://doi.org/10.1007/BF01001956

    Article  MATH  Google Scholar 

  • Ranbhise SM, Joshi KK (2014) Simulation and analysis of cloud environment. Int J Adv Res Comput Sci Technol 2:206–209

    Google Scholar 

  • Remli MA, Deris S, Jamous M et al (2015) Service composition optimization using differential evolution and opposition-based learning. Res J Appl Sci Eng Technol 11:229–234. https://doi.org/10.19026/rjaset.11.1711

    Article  Google Scholar 

  • Sasikaladevi N (2016) Trust based cloud service composition framework. Int J Grid Distrib Comput 9:99–104. https://doi.org/10.14257/ijgdc.2016.9.1.10

    Article  Google Scholar 

  • Shehu U, Safdar GA, Epiphaniou G (2015) Network-aware composition for Internet of thing services. Trans Netw Commun. https://doi.org/10.14738/tnc.31.961

    Article  Google Scholar 

  • Stegaru G, Danila C, Sacala IS et al (2012) Quality driven web service composition modeling framework. In: 13th working conference on virtual enterpries (PROVE), Oct 2012, Bournemouth, United Kingdom. Springer, IFIP advances in information and communication technology, AICT-380. pp 87–95

    Google Scholar 

  • Talbi J, Haqiq A (2017) A MAS-based cloud service brokering system to respond security needs of cloud customers. Int J Interact Multimed Artif Intell 4:65. https://doi.org/10.9781/ijimai.2017.4310

    Article  Google Scholar 

  • Wang S, Sun Q, Zou H, Yang F (2013) Particle swarm optimization with skyline operator for fast cloud-based web service composition. Mob Netw Appl 18:116–121. https://doi.org/10.1007/s11036-012-0373-3

    Article  Google Scholar 

  • Wang D, Yang Y, Mi Z (2014) A genetic-based approach to web service composition in geo-distributed cloud environment. Comput Electr Eng. https://doi.org/10.1016/j.compeleceng.2014.10.008

    Article  Google Scholar 

  • Wu Q, Zhang M, Zheng R et al (2013) A QoS-satisfied prediction model for cloud-service composition based on a hidden markov model. Math Probl Eng. https://doi.org/10.1155/2013/387083

    Article  Google Scholar 

  • Yacoab MYM, Alameen A, Sha MM (2018) A web service composition framework based on functional weight to reach maximum QoS. Int J Adv Comput Sci Appl 9:146–150

    Google Scholar 

  • Zeng L, Benatallah B, Dumas M et al (2003) Quality driven web services composition. In: Proceedings of the twelfth international conference on World Wide Web WWW 03. pp 411–421

  • Zheng X, Martin P, Brohman K (2012) Cloud service negotiation: concession vs. tradeoff approaches. In: Proceedings—12th IEEE/ACM international symposium on cluster, cloud and grid computing, CCGrid 2012. pp 515–522

Download references

Author information

Authors and Affiliations

  1. RIADI Labs, National School of Computer Science, Manouba University, Manouba, Tunisia

    Hela Malouche, Youssef Ben Halima & Henda Ben Ghezala

Authors
  1. Hela Malouche
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Youssef Ben Halima
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Henda Ben Ghezala
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Hela Malouche.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Malouche, H., Ben Halima, Y. & Ben Ghezala, H. Trust level estimation for cloud service composition with inter-service constraints. J Ambient Intell Human Comput 10, 4881–4899 (2019). https://doi.org/10.1007/s12652-019-01182-9

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12652-019-01182-9

Keyword

Search

Navigation