This paper proposes a federated cloud framework for secure machine learning in research collaborations. It supports confidential data handling with encryption, isolated pipelines, and inter-cloud orchestration for data sharing without exposing sensitive attributes across institutions.

Dominic Isaac Prescott, Chen Rui Fang, Rithika Mahesh Gopal, Isabel Fiona Morton, Andre Filipe Torres

This work presents a latency-aware routing algorithm for microservice communication in distributed cloud architectures. Reinforcement learning enables adaptive routing based on live latency metrics, improving performance in real-time service-oriented systems.

Finley George Sutton, Li Hui Juan, Abhinav Sreekanth Murthy, Poppy Eleanor Clarke, Rodrigo Manuel Pacheco

This paper explores SLA prediction using regression tree models trained on historical cloud service logs. It supports proactive mitigation of SLA breaches in multi-tenant environments by estimating compliance likelihood across service metrics in advance.

Julian Tobias Kent, Yang Li Xuan, Sahana Raghunath Varma, Matilda Grace Bishop, Mateo Julian Fernandez

This paper introduces a containerless execution model for lightweight functions in the cloud. The framework eliminates cold start delays using pre-warmed stateless runtimes, offering rapid execution for ephemeral workloads and minimizing resource wastage.

Nathaniel Oliver Frost, Gao Xin Yue, Meenakshi Durai Kumar, Emily Kate Farrow, Luis Alejandro Sosa

This research proposes an encryption-integrated cloud analytics platform for IoT data. It applies homomorphic encryption and obfuscation to preserve user privacy during real-time processing, enabling insights without compromising data confidentiality or ownership.

Leonard Seth Brody, Liu Zhen Fang, Arjun Madhavan Pillai, Isla Harriet Sanderson, Bruno Rafael Delgado

This study introduces a cloud-hosted digital twin system to simulate and predict failures in cyber-physical machines. It integrates real-time sensor feeds and machine behavior models, enabling preventive diagnostics and reducing downtime in industrial ecosystems.

Cameron Tobias Wilkins, Zhang Yin Mei, Dinesh Anandarajan Kumar, Olivia Mae Hargrove, Rafael Estevez Molina