This paper proposes a predictive scheduling model with reinforcement optimization to enable energy-conscious load balancing in hybrid cloud environments. It dynamically reallocates resources based on workload patterns, reducing operational costs while enhancing the sustainability and responsiveness of distributed cloud applications.

Adrian Blake Mortimer, Helena Ruth Sanderson, Marcus Elliot Fordham, Abigail Grace Redford, Douglas Finnian Knight

This study proposes a federated identity management framework for secure, interoperable access control across multi-cloud environments. It ensures privacy-preserving authentication, decentralizes identity provisioning, and enhances compliance with data sovereignty regulations, supporting scalable access models in enterprise cloud ecosystems.

Florence Ivy Holloway, Leonard Bryce Atkinson, Harriet Joy Thatcher, Oscar Douglas Hargreaves, Charlotte Elise Rowland

This paper introduces a context-aware auto-scaling algorithm for serverless cloud frameworks. By analyzing real-time application metrics, it scales containerized services proactively, balancing resource usage, cost, and latency, thereby ensuring continuous availability and performance in fluctuating demand environments.

Gregory Lucas Whittaker, Madeleine Sophie Carrington, Ethan Matthew Blackwood, Isabel Amelia Wilkins, Thomas Henry Pritchard

This paper investigates privacy-aware synchronization methods for distributed machine learning in multi-cloud federations. It introduces a secure aggregation protocol that reduces exposure risks during training, preserving data confidentiality while enabling collaborative model convergence across different service providers.

Juliet Faye Whitmore, Edward Samuel Lennox, Lucy Annabelle Godfrey, Henry George Redding, Olivia Beatrix Cullen

This research introduces a latency-aware orchestration strategy for microservices deployed across fog-cloud continua. Using genetic algorithms, it minimizes response times and communication overhead, offering a robust framework for optimizing service deployment and user experience in latency-sensitive applications.

Benedict Lewis Stafford, Isabelle Felicity Hammond, Owen Charles Belgrave, Daisy Alexandra Carr, Maxwell Hugo Beauchamp

This study introduces AI-based fault tolerance techniques for autonomous cloud systems supporting real-time industrial IoT applications. The architecture detects failures proactively, enabling continuous service delivery, reducing downtime, and optimizing recovery strategies across large-scale, latency-critical cloud-managed infrastructures.

Frederick Aaron Doyle, Claudia Maren Voss, Jeremy Nathanial Winters, Eloise Frances Lambert, Patrick Elliot Browning

This research presents a multi-criteria decision optimization framework for cost-aware resource allocation in virtualized cloud environments. The model integrates SLA requirements, real-time cost metrics, and service priorities, ensuring efficient budget adherence while maximizing utilization of compute resources.

Leonard Hugh Bradbury, Amelia June Forrester, Thomas Wilfred Green, Georgina Violet Lawson, Dominic Charles Sinclair