Abstract
The world is facing a complicated moment in which social isolation is necessary. Therefore, to minimize the problems of companies, remote work is being widely adopted, which is only possible because of existing technologies, including cloud computing. Choosing the providers to host the business applications is a complex task, as there are many providers and most of them offer various services with the same functionality and different capabilities. Thus, in this paper, we propose an approach, called \(PUM^2Q\), for selecting providers to host a distributed application based on microservices that have little communication between them. \(PUM^2Q\) is a provider selection approach based on multi-criteria, and it copes with the needs of microservices individually and in parallel. The proposed approach extends our previous one, \(UM^2Q\), and should be incorporated by PacificClouds. Besides, we carry out a performance evaluation by varying the number of requirements, microservices, and providers. We also compare \(PUM^2Q\) and \(UM^2Q\). The results presented by \(PUM^2Q\) are better than those given by \(UM^2Q\), showing not only its viability but also expanding the number of approaches adopted by PacificClouds. As a result, \(PUM^2Q\) making the tasks of the software architect, who is the user of PacificClouds, more flexible.
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References
Bhushan, S.B., Reddy, C.H.P.: A QoS aware cloud service composition algorithm for geo-distributed multi cloud domain. Int. J. Intell. Eng. Syst. 9(4), 147–156 (2016). https://doi.org/10.22266/ijies2016.1231.16
Carvalho, J., Vieira, D., Trinta, F.: Dynamic selecting approach for multi-cloud providers. In: Luo, M., Zhang, L.-J. (eds.) CLOUD 2018. LNCS, vol. 10967, pp. 37–51. Springer, Cham (2018). https://doi.org/10.1007/978-3-319-94295-7_3
Carvalho, J., Vieira, D., Trinta, F.: Greedy multi-cloud selection approach to deploy an application based on microservices. In: PDP 2019 (2019). https://doi.org/10.1109/PDP.2019.00021
Carvalho, J., Vieira, D., Trinta, F.: UM2Q: multi-cloud selection model based on multi-criteria to deploy a distributed microservice-based application, pp. 56–68 (2020). https://doi.org/10.5220/0009338200560068
de Carvalho, J.O., Trinta, F., Vieira, D.: PacificClouds: a flexible MicroServices based architecture for interoperability in multi-cloud environments. In: CLOSER 2018 (2018)
Chen, Y., Huang, J., Lin, C., Shen, X.: Multi-objective service composition with QoS dependencies. IEEE Trans. Cloud Comput. 7(2), 537–552 (2016). https://doi.org/10.1109/TCC.2016.2607750. http://ieeexplore.ieee.org/document/7563862/
Ding, S., Wang, Z., Wu, D., Olson, D.L.: Utilizing customer satisfaction in ranking prediction for personalized cloud service selection. Decis. Support Syst. 93, 1–10 (2017). https://doi.org/10.1016/j.dss.2016.09.001
Hayyolalam, V., Kazem, A.A.P.: A systematic literature review on QoS-aware service composition and selection in cloud environment. J. Netw. Comput. Appl. 110, 52–74 (2018). https://doi.org/10.1016/j.jnca.2018.03.003
Fischer, H.: A History of the Central Limit Theorem: From Classical to Modern Probability Theory. Sources and Studies in the History of Mathematics and Physical Sciences. Springer, New York (2011). https://doi.org/10.1007/978-0-387-87857-7
Hongzhen, X., Limin, L., Dehua, X., Yanqin, L.: Evolution of service composition based on QoS under the cloud computing environment. In: Proceedings of ICOACS 2016, pp. 66–69 (2016)
Jatoth, C., Gangadharan, G.R., Fiore, U., Buyya, R.: SELCLOUD: a hybrid multi-criteria decision-making model for selection of cloud services. Soft. Comput. 23(13), 4701–4715 (2018). https://doi.org/10.1007/s00500-018-3120-2
Jian, L., Youling, C., Long, W., Lidan, Z., Yufei, N.: An approach for service composition optimisation considering service correlation via a parallel max-min ant system based on the case library. Int. J. Comput. Integr. Manuf. 31(12), 1174–1188 (2018). https://doi.org/10.1080/0951192X.2018.1529435
Liu, Z.Z., Chu, D.H., Song, C., Xue, X., Lu, B.Y.: Social learning optimization (SLO) algorithm paradigm and its application in QoS-aware cloud service composition. Inf. Sci. 326, 315–333 (2016). https://doi.org/10.1016/j.ins.2015.08.004
Mezni, H., Sellami, M.: Multi-cloud service composition using formal concept analysis. J. Syst. Softw. 134, 138–152 (2017). https://doi.org/10.1016/j.jss.2017.08.016
Panda, S.K., Pande, S.K., Das, S.: Task partitioning scheduling algorithms for heterogeneous multi-cloud environment. Arab. J. Sci. Eng. 43(2), 913–933 (2017). https://doi.org/10.1007/s13369-017-2798-2
Seghir, F., Khababa, A.: A hybrid approach using genetic and fruit fly optimization algorithms for QoS-aware cloud service composition. J. Intell. Manuf. 29(8), 1773–1792 (2016). https://doi.org/10.1007/s10845-016-1215-0
Sousa, G., Rudametkin, W., Duchien, L.: Automated setup of multi-cloud environments for microservices-based applications. In: 9th IEEE International Conference on Cloud Computing (2016). https://doi.org/10.1109/CLOUD.2016.49
Thomas, M.V., Chandrasekaran, K.: Dynamic partner selection in Cloud Federation for ensuring the quality of service for cloud consumers. Int. J. Model. Simul. Sci. Comput. 08(03), 1750036 (2017). https://doi.org/10.1142/S1793962317500362. http://www.worldscientific.com/doi/abs/10.1142/S1793962317500362
Yimin, Z., Guojun, S., Xiaoguang, Y.: Cloud service selection optimization method based on parallel discrete particle swarm optimization. In: Proceedings of the 30th Chinese Control and Decision Conference, CCDC 2018, pp. 2103–2107 (2018). https://doi.org/10.1109/CCDC.2018.8407473
Zhou, J., Yao, X.: Multi-population parallel self-adaptive differential artificial bee colony algorithm with application in large-scale service composition for cloud manufacturing. Appl. Soft Comput. J. 56, 379–397 (2017). https://doi.org/10.1016/j.asoc.2017.03.017
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Carvalho, J., Trinta, F., Vieira, D. (2021). A Multi-cloud Parallel Selection Approach for Unlinked Microservice Mapped to Budget’s Quota: The \(PUM^2Q\). In: Ferguson, D., Pahl, C., Helfert, M. (eds) Cloud Computing and Services Science. CLOSER 2020. Communications in Computer and Information Science, vol 1399. Springer, Cham. https://doi.org/10.1007/978-3-030-72369-9_5
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