This paper proposes a dynamic energy management system for hybrid clouds that integrates predictive workload analytics and carbon-awareness. The approach minimizes energy consumption and carbon emissions while maintaining service levels across distributed infrastructures using real-time optimization and load balancing techniques.

Edward Franklin Monroe, Isabel Helena Chambers, Gregory Samuel Fielding, Lucas Bernard Powell, Madeleine Alice Rhodes

This research introduces a secure container framework leveraging Trusted Execution Environments (TEE) for confidentiality in multi-tenant clouds. It ensures code and data isolation, supports compliance, and provides end-to-end protection throughout the container lifecycle without sacrificing scalability or performance.

Joanna Harriet McMillan, Benedict Arthur Russell, Sophia Mae Kendall, Oliver Grant Whitaker, Fiona Louise Beckett

This paper presents a scalable ML-driven storage tiering system for cloud-native workloads. By learning data access patterns, the system intelligently places files across SSD, HDD, and object storage, improving response time and reducing storage cost in large-scale cloud deployments.

Harrison Miles Pritchard, Natalie Claire Jennings, Arthur Lewis McGregor, Victoria Annabel Goodwin, Simon Andrew Fitzpatrick

This study demonstrates a federated learning framework hosted in the cloud that unites environmental data from heterogeneous edge sensors. The solution achieves high prediction accuracy with strong privacy guarantees, enabling climate-aware insights without centralized data collection across varying device capabilities.

Elijah Connor Morrison, Felicity Brooke Sanderson, Miles Adrian Foster, Harriet Rose Devereux, Callum George Huxley

This research proposes a green-aware workload placement strategy for containers deployed in geographically distributed cloud regions. The model considers renewable energy availability, carbon intensity, and latency sensitivity to reduce emissions while optimizing compute distribution in real-time cloud orchestration systems.

Maxwell Edward Thornton, Grace Alexandra Barnes, Owen Henry Caldwell, Alice Miriam Prescott, Zachary Louis Templeton