OPTIMIZING COMPUTING IN DISTRIBUTED AI SYSTEMS USING EDGE COMPUTING

Authors

  • Aram Andreasyan IT Specialist, Los Angeles, USA Author

Keywords:

Edge Computing, distributed AI, optimization computing, federated learning, model compression, IoT, latency.

Abstract

This article discusses approaches to optimizing computational processes in distributed artificial intelligence systems based on the Edge concept. Computing. This article analyzes architectural models, load balancing methods, model compression algorithms, and computation orchestration mechanisms between the cloud and edge nodes. Particular attention is paid to reducing latency, conserving network resources, and improving the energy efficiency of AI infrastructures.

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Published

2025-04-21

Issue

Vol. 1 No. 1 (2025)

Section

Articles

License

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

OPTIMIZING COMPUTING IN DISTRIBUTED AI SYSTEMS USING EDGE COMPUTING. (2025). Modern American Journal of Engineering, Technology, and Innovation, 1(1), 84-91. https://usajournals.org/index.php/2/article/view/1868