This paper explores a scalable cloud-integrated digital twin framework that enhances predictive maintenance for industrial IoT systems. Leveraging real-time sensor data, it models equipment behavior and proactively detects anomalies, minimizing downtime and improving operational efficiency in industrial cloud deployments.

Edward Nathaniel Blackwell, Charlotte Isabelle Pennington, Hugo Dominic Fairchild, Madeleine Beatrice Harwood, Jacob Franklin Rosewood

The study introduces a performance-aware autoscaling policy tailored for Kubernetes microservices operating across multi-region clouds. The framework dynamically adapts resource provisioning to latency thresholds, service dependencies, and traffic variations, optimizing global responsiveness and service availability under real-time demand conditions.

Theodore Marcus Lovell, Daisy Amelia Sutherland, Felix Edward Thorne, Lucy Victoria Goodwin, Oliver Sebastian Hargrave

This paper proposes a multi-objective genetic algorithm for scheduling containerized applications in cloud environments. The approach balances energy consumption and response time while maintaining service level agreements, offering a robust and adaptive solution for green and cost-efficient container orchestration.

Arthur Lionel Carver, Matilda Eve Bradbury, William Isaac Forsythe, Isabelle Grace Linton, Hugo George Carmichael

The study presents a federated identity system that enforces cross-domain access control across hybrid cloud environments. Leveraging role-based trust hierarchies, it ensures secure, scalable user access to distributed cloud resources while maintaining centralized policy administration across organizational boundaries.

Archibald Victor Langley, Evie Rose Tinsley, Sebastian Miles Rowntree, Chloe Eleanor Stratton, Thomas Julian Bradfield

This paper proposes a self-adaptive mechanism to distribute computational loads between edge and cloud resources in smart grids. It emphasizes reliability and fault-tolerance, using system monitoring data to dynamically reroute workloads based on node health and current latency thresholds.

Harrison Edward Pemberton, Florence Ivy Rowden, Leo Christopher Ainsworth, Sophie Beatrix Lawton, Henry Oscar Belgrave

This research introduces a secure data-sharing protocol tailored for confidential resource access in multi-tenant clouds. Utilizing attribute-based encryption and access delegation, the solution ensures data confidentiality and controlled resource access while preserving performance across distributed cloud infrastructure.

Louis Alexander Whitmore, Beatrice Alice Kershaw, Elliot Benjamin Radcliffe, Daisy Isabelle Crompton, Thomas Oliver Fenwick

This study focuses on real-time virtualization layer optimization to support latency-sensitive workloads across heterogeneous cloud environments. The architecture dynamically reconfigures compute and I/O paths, improving task execution efficiency for high-throughput applications without compromising isolation or security guarantees.

Frederick James Halberd, Olivia Margaret Lyndon, Benjamin Edward Whitaker, Phoebe Annette Gresham, Samuel Victor Norwood