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Experiences in Architectural Design and Deployment of eHealth and Environmental Applications for Cloud-Edge Continuum

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Advanced Information Networking and Applications (AINA 2023)

Abstract

The Cloud-Edge continuum has lately exponentially grown, thanks to the increase in the availability of computational power in Edge Devices, and the better capabilities of communication networks. In this paper, two use cases, in eHealth and environmental domain, are presented in order to provide an application context to exemplify the approaches driving the analysis and selection of Cloud-Edge architectural solutions and patterns, the structural design, the allocation and deployment of distributed applications targeted to the Cloud Continuum. The main focus of this paper is the comparison of the architectural choices made for the two use cases, and how they have been driven by typical non-functional requirements, guiding the adoption of a Cloud Continuum solution.

A. Aral and A. Esposito—Contributed equally to this work as the first authors.

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References

  1. Satyanarayanan, M.: The emergence of edge computing. Computer 50(1), 30–39 (2017)

    Article  Google Scholar 

  2. Baresi, L., Mendonça, D.F., Garriga, M., Guinea, S., Quattrocchi, G.: A unified model for the mobile-edge-cloud continuum. ACM Trans. Internet Technol. (TOIT) 19(2), 1–21 (2019)

    Article  Google Scholar 

  3. Zheng, T., Wan, J., Zhang, J., Jiang, C.: Deep reinforcement learning-based workload scheduling for edge computing. J. Cloud Comput. 11(1), 1–13 (2022). https://doi.org/10.1186/s13677-021-00276-0

    Article  Google Scholar 

  4. Koloth, A.: Data patterns for the edge: data localization, privacy laws, and performance (2022). https://www.infoq.com/articles/data-patterns-edge/. Accessed 25 Nov 2022

  5. Xu, J., Glicksberg, B.S., Su, C., Walker, P., Bian, J., Wang, F.: Federated learning for healthcare informatics. J. Healthc. Inform. Res. 5(1), 1–19 (2021). https://doi.org/10.1007/s41666-020-00082-4

    Article  Google Scholar 

  6. Rieke, N., et al.: The future of digital health with federated learning. NPJ Digit. Med. 3(1), 1–7 (2020)

    Article  Google Scholar 

  7. Shyu, C.-R., et al.: A systematic review of federated learning in the healthcare area: from the perspective of data properties and applications. Appl. Sci. 11(23), 11191 (2021)

    Article  Google Scholar 

  8. Lo, S.K., Lu, Q., Zhu, L., Paik, H.-Y., Xu, X., Wang, C.: Architectural patterns for the design of federated learning systems. J. Syst. Softw. 191, 111357 (2022)

    Article  Google Scholar 

  9. Lo, S.K., Lu, Q., Paik, H.-Y., Zhu, L.: FLRA: a reference architecture for federated learning systems. In: Biffl, S., Navarro, E., Löwe, W., Sirjani, M., Mirandola, R., Weyns, D. (eds.) ECSA 2021. LNCS, vol. 12857, pp. 83–98. Springer, Cham (2021). https://doi.org/10.1007/978-3-030-86044-8_6

    Chapter  Google Scholar 

  10. Di Martino, B., Graziano, M., Colucci Cante, L., Cascone, D.: Analysis of techniques for mapping convolutional neural networks onto cloud edge architectures using SplitFed learning method. In: Barolli, L., Hussain, F., Enokido, T. (eds.) AINA 2022. LNNS, vol. 451, pp. 163–172. Springer, Cham (2022). https://doi.org/10.1007/978-3-030-99619-2_16

    Chapter  Google Scholar 

  11. Bellemare, A.: Building Event-Driven Microservices. O’Reilly Media Inc. (2020)

    Google Scholar 

  12. Shapira, G., Palino, T., Sivaram, R., Petty, K.: Kafka: The Definitive Guide: Real-Time Data and Stream Processing at Scale. O’Reilly Media Inc. (2020)

    Google Scholar 

  13. Martín, C., Langendoerfer, P., Zarrin, P.S., Díaz, M., Rubio, B.: Kafka-ML: connecting the data stream with ML/AI frameworks. Future Gener. Comput. Syst. 126, 15–33 (2022)

    Article  Google Scholar 

  14. Mohebbian, M.R., Vedaei, S.S., Wahid, K.A., Dinh, A., Marateb, H.R., Tavakolian, K.: Fetal ECG extraction from maternal ECG using attention-based CycleGAN. IEEE J. Biomed. Health Inform. 26(2), 515–526 (2021)

    Article  Google Scholar 

  15. Ajdaraga, E., Gusev, M.: Analysis of sampling frequency and resolution in ECG signals. In: 2017 25th Telecommunication Forum (TELFOR), pp. 1–4 (2017)

    Google Scholar 

  16. De Maio, V., Aral, A., Brandic, I.: A roadmap to post-moore era for distributed systems. In: Proceedings of the 2022 Workshop on Advanced Tools, Programming Languages, and PLatforms for Implementing and Evaluating Algorithms for Distributed Systems, pp. 30–34 (2022)

    Google Scholar 

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Acknowledgement

This work was partially funded by the Digital Europe Programme, Project DANTE EDIH, ID: 101083913, as within the activities conducted by the “CINI - Consorzio Interuniversitario Nazionale per l’Informatica”.

A. Aral was supported by the CHIST-ERA grant CHIST-ERA-19-CES-005 and by the Austrian Science Fund (FWF): I 5201-N.

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Correspondence to Mario A. Bochicchio .

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Aral, A., Esposito, A., Nagiyev, A., Benkner, S., Di Martino, B., Bochicchio, M.A. (2023). Experiences in Architectural Design and Deployment of eHealth and Environmental Applications for Cloud-Edge Continuum. In: Barolli, L. (eds) Advanced Information Networking and Applications. AINA 2023. Lecture Notes in Networks and Systems, vol 655. Springer, Cham. https://doi.org/10.1007/978-3-031-28694-0_13

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