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Author

Praveen Kumar Donta

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Review Oct 2026

Agentic AI in Healthcare 5.0: Reference Architecture, Applications, and Challenges

Healthcare systems are increasingly data-rich but remain fragmented, reactive, and difficult to coordinate across institutions, devices, and clinical workflows. Healthcare 5.0 addresses these limitations through human-centricity, resilience, and symbiotic human-artificial intelligence (AI) collaboration. This survey po...

T. Gadekallu, Thien Huynh-The, A. Chehri et al. · 0 citations
Sep 2026

LLM4ETS: Self‐Evolving Algorithm Design for Edge Task Scheduling via Large Language Models

With the rapid proliferation of 5G and the Internet of Things, ensuring low latency in edge computing has become crucial for real‐time processing applications. However, existing task scheduling approaches often struggle to balance multiple optimization objectives effectively due to manual parameter tuning and slo...

Yu-Qi Zhao, Shen-Dong Gao, Ya-Tong Wang et al. · 0 citations
Jul 2026

A Taxonomy of Performance Metrics for the Distributed Computing Continuum

Performance evaluation is essential for understanding, comparing, and improving computing systems, including Distributed Computing Continuum Systems (DCCS). In recent years, computational requirements have changed substantially with the growth of artificial intelligence and large-scale data-driven applications. These a...

Praveen Kumar Donta, Boris Sedlak, Alfreds Lapkovskis et al. · 0 citations
Jul 2026

ADORN: Adaptive Drift handling for Open RAN using Reinforcement Learning

Experimental results show that the proposed Q-learning-based adaptive retraining approach effectively reduces retraining overhead compared to greedy and random baselines, while maintaining system performance within predefined limits.

A. Subudhi, Bhargav Chirumamilla, Shubham Vaishnav et al. · 0 citations

Adaptive AI Task Partitioning and Safe Offloading in Heterogeneous Edge-Cloud Continuum

A framework that dynamically splits neural network layers across the heterogeneous continuum and achieves reductions in energy and end-to-end latency is proposed, confirming the superiority of adaptive to static partitioning.

Akuen Akoi Deng, Eimantas Butkus, Alfreds Lapkovskis et al. · 0 citations

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