Serverless Architecture for Real-Time Data Processing in Smart Applications


EOI: 10.11242/viva-tech.01.09.27

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Citation

Dr.Pradnya Mhatre,Ajay Bhivsane,Sumit Kadam,"Serverless Architecture for Real-Time Data Processing in Smart Applications" VIVA-IJRI Volume 1, Issue 9, Article 27, pp. 1-3, 2026. Published by MCA Department, VIVA Institute of Technology, Virar, India.

Abstract

The rapid growth of smart applications such as Internet of Things (IoT), smart cities, healthcare monitoring, and real-time analytics systems has significantly increased the demand for scalable and low-latency data processing architectures. Traditional server-based systems often struggle to meet these requirements due to infrastructure management overhead and limited scalability. Serverless architecture has emerged as a promising solution by enabling event-driven, on-demand execution of computing resources without server management. This paper explores the role of serverless architecture in real-time data processing for smart applications. It discusses core components, system architecture, advantages, challenges, and practical use cases. The study demonstrates how serverless platforms enhance scalability, reduce operational costs, and improve responsiveness in real-time smart systems.

Keywords

Event-driven computing, Internet of Things, Real-time data processing, Scalability, Serverless architecture

References

  1. [1] Amazon Web Services, Serverless Computing – Overview, AWS Documentation, 2024.
  2. [2] Google Cloud, Cloud Functions: Event- Driven Serverless Compute Platform, Google Cloud Docs, 2024.
  3. [3] J. Spillner, T. Mateos, and D. Bermbach, “Faaster, better, cheaper: The rise of serverless computing,” IEEE Internet Computing, vol. 21, no. 4, pp. 20–28, 2017.
  4. [4] E. Jonas et al., “Occupy the cloud: Distributed computing for the 99%,” Proceedings of the ACM Symposium on Cloud Computing, pp. 445–451, 2017./li>
  5. [5] W. Shi et al., “Edge computing: Vision and challenges,” IEEE Internet of Things Journal, vol. 3, no. 5, pp. 637–646, 2016.
  6. [6] M. Chen, Y. Zhang, Y. Li, S. Mao, and V. C. M. Leung, “Big data analytics for IoT and smart cities,” IEEE Communications Magazine, vol. 56, no. 2, pp. 128–136, 2018.
  7. [7] I. Baldini et al., “Serverless computing: Current trends and open problems,” Research Advances in Cloud Computing, Springer, pp. 1–20, 2017.
  8. [8] L. Wang et al., “Peeking behind the curtains of serverless platforms,” USENIX Annual Technical Conference, pp. 133–145, 2018.
  9. [9] A. Singh and M. M. Singh, “Real-time data processing using cloud-based serverless architecture,” International Journal of Computer Applications, vol. 182, no. 44, pp. 1–6, 2019.
  10. [10] T. Lynn, P. Rosati, A. Lejeune, and V. Emeakaroha, “A preliminary review of enterprise serverless cloud computing,” Journal of Cloud Computing, vol. 6, no. 1, pp. 1–14, 2017.
  11. [11] Z. Zhang et al., “6G wireless networks: Vision, requirements, architecture, and key technologies,” IEEE Vehicular Technology Magazine, vol. 14, no. 3, pp. 28–41, 2019.
  12. [12] M. Adzic and V. Chatley, “Serverless computing: Economic and architectural impact,” Proceedings of the 11th Joint Meeting on Foundations of Software Engineering, pp. 884–889, 2017.
  13. [13] Apache Software Foundation, Apache Kafka Documentation, 2024.
  14. [14] S. Hendrickson et al., “Serverless computation with open Lambda,” Proceedings of the 8th USENIX Workshop on Hot Topics in Cloud Computing, 2016.