Large-Scale Data Processing and System Architecture Evolution in Distributed Cloud Platforms

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Published: 2026-05-24
Keywords:
Distributed Cloud Platforms, System Architecture, Large-Scale Data Processing, Scalability, Resource Optimization

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Kevin Smith
School of Computing, Queen's University, Kingston, Canada

Abstract

This research article explores the evolution of system architecture and large-scale data processing in distributed cloud platforms. It delves into the challenges of scalability, fault tolerance, and resource optimization inherent in distributed systems. The study presents a systematic methodology for analyzing architectural paradigms, experimental setups, and performance metrics. Results demonstrate significant improvements in processing efficiency through optimized resource allocation and advanced data partitioning techniques. The discussion highlights the implications of these findings for future cloud-based systems, emphasizing the need for adaptive, modular architectures. The paper concludes by outlining potential directions for further research in distributed cloud platforms.

Article Details

Issue

Vol. 2 No. 1 (2026)

Section

Articles

How to Cite

Large-Scale Data Processing and System Architecture Evolution in Distributed Cloud Platforms. (2026). Hua Xia Xin Zhi, 2(1), 158-169. https://journals.hubblepress.com/index.php/HXXZ/article/view/37

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