This work proposes a decentralized scheduling system for federated deep learning workloads within dynamic, cloud-connected healthcare infrastructure, emphasizing data privacy, computational efficiency, and adaptive optimization across diverse regional data centers.

Samantha Leigh Donovan, Ryuichi Takahiro Yamazaki, Antoine Luis Delgado, Kavya Rajendran Bhat, Omar Nasir Khaleel

This study introduces a self-adaptive resource allocation mechanism for microservices in multi-cloud container orchestration. It dynamically scales deployments based on usage patterns, improving cost-efficiency and reliability without human intervention under volatile traffic scenarios.

Chun Xiao Mei, Leonardo Vincenti, Julia Renée Monroe, Akash Prateek Sen, Matteo Jorge Cardona

This paper presents a redundancy mechanism for serverless functions, optimizing execution across green data centers and edge nodes. The method minimizes energy consumption while maintaining performance in latency-sensitive services like IoT monitoring and autonomous decision systems.

Lina Huang Xiang, Eryk Maximilian Dubois, Jonas Eric Holtz, Ananya Ghosh Iyer, Gabriel Alonso Ferreira

This work introduces a transformer-based detection pipeline tailored for decentralized cloud services. By leveraging multi-head attention across logs and metrics, the system accurately identifies anomalies, minimizes false alarms, and ensures robust cloud service integrity under real-world conditions.

William Zachary Grant, Xiang Zhen Shuai, Priyanka Mahesh Chandar, Larissa Monique Barbosa, Ahmed Abdallah Selim

This paper introduces latency-tolerant blockchain algorithms to manage data consensus across federated cloud and edge networks. The proposed model enhances real-time performance while maintaining transparency and trust among multiple data providers and consumers in dynamic environments.

Marco Daniel Tonelli, Tao Xue Jin, Isabella Charlotte Jensen, Yusuf Shahrukh Khan, Lucas Ren Minghao

The paper proposes a novel quantum-enhanced compression approach aimed at reducing data footprint and latency in cloud storage. It also facilitates efficient inter-region data migration while ensuring end-to-end security in cross-continental deployments.

Zhou Wei Liang, Ryan Dominic Bergstrom, Anshul Devendra Sharma, Mariana Lucille Arguello, Felix Marius Trinh

This study presents a multi-cloud deployment technique incorporating software-defined networking for traffic steering and policy-driven replication strategies. It ensures service continuity, regulatory compliance, and operational efficiency during system outages or regional infrastructure disruptions.

Helena Margaret Voss, Qian Feng Zhuo, Martin Pablo Sterling, Divya Rajan Deepak, Omar Luis Franco