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A Hybrid TLBO-TS Algorithm Based Mobile Service Selection for Composite Services

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Algorithms and Architectures for Parallel Processing (ICA3PP 2021)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 13155))

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Abstract

Service selection for composite service has been a hot research issue in service computing field. With the proliferation of mobile devices, service selection confronts new challenges in the mobile environment due to the mobility, unpredictability, and variation of signal strength of mobile networks, since quality of service (QoS) is closely related to these factors. In this work, we aim to address the problem of mobile service selection for composite service in terms of QoS. Specifically, based on the mobility model and mobility-aware QoS computation rule, we propose a hybrid service composition optimization algorithm, named TLBO-TS, by integrating Teaching-Learning-Based Optimization (TLBO) algorithm and Tabu Search (TS) algorithm. Through the optimization of service selection with TLBO-TS algorithm, the global QoS of the generated mobile service composition is approximately optimal. Extensive experiments are conducted and the experimental results show that the proposed approach can derive more optimized mobile service composition with acceptable scalability compared with the traditional approach and other baselines.

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References

  1. Kang, G., Liu, J., Cao, B., Cao, M.: NAFM: neural and attentional factorization machine for web API recommendation. In: 2020 IEEE International Conference on Web Services (ICWS), pp. 330–337. IEEE (2020)

    Google Scholar 

  2. Deng, S., et al.: Toward mobile service computing: opportunities and challenges. IEEE Cloud Comput. 3(4), 32–41 (2016)

    Article  Google Scholar 

  3. Deng, S., Wu, H., Yin, J.: Mobile Service Computing. ATSTC, vol. 58. Springer, Singapore (2020). https://doi.org/10.1007/978-981-15-5921-1

  4. Kang, G., Liu, J., Cao, B., Xiao, Y.: Diversified QoS-centric service recommendation for uncertain QoS preferences. In: IEEE International Conference on Services Computing, Beijing, China, pp. 288–295. IEEE (2020)

    Google Scholar 

  5. Kang, G., Liu, J., Tang, M., Xu, Y.: An effective dynamic web service selection strategy with global optimal QoS based on particle swarm optimization algorithm. Paper presented at the International Parallel and Distributed Processing Symposium, Shanghai, China (2012)

    Google Scholar 

  6. Deng, S., Huang, L., Hu, D., Zhao, J.L., Wu, Z.: Mobility-enabled service selection for composite services. IEEE Trans. Serv. Comput. 9(3), 394–407 (2014)

    Article  Google Scholar 

  7. Deng, S., Wu, H., Tan, W., Xiang, Z., Wu, Z.: Mobile service selection for composition: an energy consumption perspective. IEEE Trans. Autom. Sci. Eng. 14(3), 1478–1490 (2015)

    Article  Google Scholar 

  8. Gelenbe, E., Lent, R.: Energy–QoS trade-offs in mobile service selection. Future Internet 5(2), 128–139 (2013)

    Article  Google Scholar 

  9. Deng, S., Wu, H., Hu, D., Zhao, J.L.: Service selection for composition with QoS correlations. IEEE Trans. Serv. Comput. 9(2), 291–303 (2014)

    Article  Google Scholar 

  10. Rao, R.V.: Teaching Learning Based Optimization Algorithm. Springer, Cham (2016). https://doi.org/10.1007/978-3-319-22732-0

  11. Liu, Y., Ngu, A.H., Zeng, L.Z.: QoS computation and policing in dynamic web service selection. Paper presented at the Proceedings of the International World Wide Web Conference (2004)

    Google Scholar 

  12. Benatallah, B., Dumas, M., Sheng, Q.Z., Ngu, A.H.H.: Declarative composition and peer-to-peer provisioning of dynamic web services. Paper presented at the Proceedings of the 18th International Conference on Data Engineering (2002)

    Google Scholar 

  13. Zeng, L., Benatallah, B., Dumas, M., Kalagnanam, J., Sheng, Q.Z.: Quality driven web services composition. Paper presented at the International World Wide Web Conference (2003)

    Google Scholar 

  14. Yu, T., Zhang, Y., Lin, K.: Efficient algorithms for web services selection with end-to-end QoS constraints. ACM Trans. Web (TWEB) 1(1), 6–32 (2007)

    Article  Google Scholar 

  15. Alrifai, M., Risse, T.: Combining global optimization with local selection for efficient QoS-aware service composition. Paper presented at the 18th International Conference on World Wide Web, Madrid, Spain (2009)

    Google Scholar 

  16. Kashyap, N., Kumari, A.C., Chhikara, R.: Service composition in IoT using genetic algorithm and particle swarm optimization. Open Comput. Sci. 10(1), 56–64 (2020)

    Article  Google Scholar 

  17. Li, C., Li, J., Chen, H.: A meta-heuristic-based approach for Qos-aware service composition. IEEE Access 8, 69579–69592 (2020)

    Article  Google Scholar 

  18. Liu, S., Liu, Y., Jing, N., Tang, G., Tang, Y.A.: Dynamic web service selection strategy with QoS global optimization based on multi-objective genetic algorithm. In: Zhuge, H., Fox, G.C. (eds.) GCC 2005. LNCS, vol. 3795, pp. 84–89. Springer, Heidelberg (2005). https://doi.org/10.1007/11590354_10

    Google Scholar 

  19. Wang, Z., Cheng, B., Zhang, W., Chen, J.: QoS-aware automatic service composition based on service execution timeline with multi-objective optimization. In: 2020 IEEE International Conference on Services Computing (SCC), pp. 296–303. IEEE (2020)

    Google Scholar 

  20. Kang, G., Liu, J., Tang, M., Liu, X.F., Fletcher, K.F.: Web service selection for resolving conflicting service requests. Paper presented at the International Conference on Web Services, Washington, DC, USA (2011)

    Google Scholar 

  21. Somu, N., Gauthama Raman, M.R., Kirthivasan, K., Shankar Sriram, V.S.: A trust centric optimal service ranking approach for cloud service selection. Future Gener. Comput. Syst. 86, 234–252 (2018)

    Article  Google Scholar 

  22. Deng, S., Huang, L., Taheri, J., Yin, J., Zhou, M., Zomaya, A.Y.: Mobility-aware service composition in mobile communities. IEEE Trans. Syst. Man Cybern. Syst. 47(3), 555–568 (2016)

    Article  Google Scholar 

  23. Yavaş, G., Katsaros, D., Ulusoy, Ö., Manolopoulos, Y.: A data mining approach for location prediction in mobile environments. Data Knowl. Eng. 54(2), 121–146 (2005)

    Article  Google Scholar 

  24. Jain, C.C.R., van den Berg, E.: Location prediction algorithms for mobile wireless systems (2002)

    Google Scholar 

  25. Rao, R.V., Savsani, V.J., Vakharia, D.: Teaching–learning-based optimization: a novel method for constrained mechanical design optimization problems. Comput. Aided Des. 43(3), 303–315 (2011)

    Article  Google Scholar 

  26. Glover, F., Laguna, M.: Tabu search. In: Handbook of Combinatorial Optimization, pp. 2093–2229. Springer, Cham (1998)

    Google Scholar 

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Acknowledgment

This work was partially supported by National Key R&D Program of China under grant No: 2020YFB1707602, Educational Commission of Hunan Province of China under Grant No: 20B244, National Natural Science Foundation of China under grant No: 61872139 and 61572187.

Author information

Authors and Affiliations

  1. Hunan Provincial Key Lab. for Services Computing and Novel Software Technology, HNUST, Xiangtan, China

    Runbin Xie, Jianxun Liu, Guosheng Kang, Buqing Cao, Yiping Wen & Jiayan Xiang

  2. School of Computer Science and Engineering, Hunan University of Science and Technology, Xiangtan, China

    Runbin Xie, Jianxun Liu, Guosheng Kang, Buqing Cao, Yiping Wen & Jiayan Xiang

Authors
  1. Runbin Xie
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  2. Jianxun Liu
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  3. Guosheng Kang
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  4. Buqing Cao
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  5. Yiping Wen
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  6. Jiayan Xiang
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Editor information

Editors and Affiliations

  1. Xiamen University, Xiamen, China

    Yongxuan Lai

  2. Beijing Normal University, Zhuhai, China

    Tian Wang

  3. Xiamen University, Xiamen, China

    Min Jiang

  4. Tianjin University, Tianjin, China

    Guangquan Xu

  5. Hunan University, Changsha, China

    Wei Liang

  6. University of Naples Parthenope, Naples, Italy

    Aniello Castiglione

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Xie, R., Liu, J., Kang, G., Cao, B., Wen, Y., Xiang, J. (2022). A Hybrid TLBO-TS Algorithm Based Mobile Service Selection for Composite Services. In: Lai, Y., Wang, T., Jiang, M., Xu, G., Liang, W., Castiglione, A. (eds) Algorithms and Architectures for Parallel Processing. ICA3PP 2021. Lecture Notes in Computer Science(), vol 13155. Springer, Cham. https://doi.org/10.1007/978-3-030-95384-3_16

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  • DOI: https://doi.org/10.1007/978-3-030-95384-3_16

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-95383-6

  • Online ISBN: 978-3-030-95384-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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