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RETRACTED ARTICLE: Meta heuristic QoS based service composition for service computing

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This article was retracted on 23 May 2022

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Abstract

In Service Computing, Service selection plays a vital role in delivering an appropriate service to the end user based on the request. Service composition methodology is the major factor affecting the appropriate need for the user or the consumer. The proposed technique involve the use of hybrid meta heuristics genetic algorithm with tabu search to retrieve the best suitable web service to the end user based on the Quality of service parameters. The existing techniques use the parameters response time, cost and reliability. The technique used in hybrid algorithm is used computes the availability of service, response time, throughput and interoperability between the services. Hence the result of service composition gives high reliable service to the end user with maximum throughput and interoperability. The location based service selection mechanism is considered for service composition as almost 90% of the services are available in cloud.

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References

  • Bahadori S (2009) Optimal web service composition using hybrid GA-TABU search. J Theor Appl Inf Technol 9(1):10–15

    Google Scholar 

  • Chandrasekar J, Member S, Gangadharan F, Buyya R (2017) Computational intelligence based QoS-aware web service composition: a systematic literature review. IEEE Trans Serv Comput 10(3):475–493

    Article  Google Scholar 

  • Chattopadhyay S, Banerjee A (2016) QSCAS: QoS aware web service Composition Algorithms with Stochastic parameters. InWeb Services (ICWS), 2016 IEEE International Conference on 2016 Jun 27. IEEE, (pp 388–395)

  • Chifu VR, Salomie I (2014) Hybridization of cuckoo search and firefly algorithms for selecting the optimal solution in semantic web service composition, in cuckoo search and firefly algorithm. Springer, Berlin p 217–243

  • Cremene M (2016) Comparative analysis of multi-objective evolutionary algorithms for QoS-aware web service composition. Appl Soft Comput 39:124–139

    Article  Google Scholar 

  • Cremene M, Pallez D, Suciu M, Dumitrescu D (2016) Comparative analysis of multi-objective evolutionary algorithms for QoS-aware web service composition. Appl Soft Comput 29:124–139

    Article  Google Scholar 

  • da Silva AS, Ma H, Zhang M (2016) Genetic programming for QoS-aware web service composition and selection. Soft Comput 20(10):3851–67

    Article  Google Scholar 

  • Deng D, Liu F (2016) QoS-aware service composition with user preferences and multiple constraints. J High Speed Netw 22(3):193–204

  • Derhami V, Ghasemzadeh M, Amiri A (2013) QoS-based web service composition based on genetic algorithm. JAI Data Min 1(2):63–73

    Google Scholar 

  • Gaur VD, Rishi A (2015) GA-Tabu based user centric approach for discovering optimal Qos composition. Int J Modern Educ Comput Sci 7(2):56

    Article  Google Scholar 

  • Fdhila W (2014) Heuristics for composite web service decentralization. Softw Syst Model 13(2):599–619

    Article  Google Scholar 

  • Jatoth C, Buyya G (2015) Computational intelligence based QoS-aware web service composition: a systematic literature review

  • Jin T, Tan W, Zhao Y (2017) QoS-aware web service composition considering the Constraints between Services. InProceedings of the 12th Chinese Conference on Computer Supported Cooperative Work and Social Computing. ACM, pp 229–232

  • Jyoti A, Shrimali M, Tiwari S et al (2020) Cloud computing using load balancing and service broker policy for IT service: a taxonomy and survey. J Ambient Intell Human Comput. https://doi.org/10.1007/s12652-020-01747-z

    Article  Google Scholar 

  • Nasr ES, Elsayed DH, Alaa El Din M, Gheith MH (2017) A new hybrid approach using genetic algorithm and Q-learning for QoS-aware web service composition. InInternational Conference on Advanced Intelligent Systems and Informatics (pp. 537–546). Springer, Cham

  • Pejman E (2012) Web service composition methods: a survey. Proceedings of the International MultiConference of Engineers and Computer Scientists

  • Ramrez A, Romero JR, Parejo JA, Ruiz-Corts SS (2017) Evolutionary composition of QoS-aware web services. Exp Syst Appl 72:357–70

    Article  Google Scholar 

  • Safi-Esfahani F, Shahrokh P (2016) QoS-based web service composition applying an improved genetic algorithm (IGA) method. Int J Enterp Inf Syst 12(3):60–77

    Article  Google Scholar 

  • Sallehuddin R, Kaewpruksapimon C, Mohamad R (2014) A review on service selection for web service composition

  • Sun Y, Ding Z, Liu J, Liu J, Pan M (2017) A genetic algorithm based approach to transactional and QoS-aware service selection. Enterprise Inf Syst 16(3):339–358

    Google Scholar 

  • Xu X, Sheng QZ, Wang X, Wang Z, Yao L (2016) Novel artificial bee colony algorithms for QoS-aware service selection. IEEE Trans Serv Comput 22

  • Yang Y, He Q, Wang Y (2017) Service selection based on correlated QoS requirements. InServices computing (SCC). IEEE International Conference on IEEE, pp 241–248

  • Yuan Y (2013) Optimal web service composition based on context-awareness and genetic algorithm. Information Science and Cloud Computing Companion (ISCC-C), International Conference on IEEE

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Correspondence to P. Thangaraj.

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This article has been retracted. Please see the retraction notice for more detail:https://doi.org/10.1007/s12652-022-03932-8

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Thangaraj, P., Balasubramanie, P. RETRACTED ARTICLE: Meta heuristic QoS based service composition for service computing. J Ambient Intell Human Comput 12, 5619–5625 (2021). https://doi.org/10.1007/s12652-020-02083-y

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  • DOI: https://doi.org/10.1007/s12652-020-02083-y

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