This paper presents a reinforcement learning strategy for latency-aware task offloading in IoT systems using hybrid fog and cloud resources. The model balances network conditions, task urgency, and energy consumption to improve quality of service for edge-based applications.

Clifford Henry Breckridge, Fiona Juliet Marlborough, Nathaniel Louis Darlington, Daphne Elizabeth Tillingham, Edmund Percy Kinsley

This paper introduces a dynamic service composition framework for enterprise workflows requiring strict SLA compliance. It uses constraint satisfaction modeling and runtime adaptation to orchestrate microservices based on latency, throughput, and contractual requirements across hybrid cloud environments.

Victor Emmanuel Cranswick, Helena Ivy Prestwick, Arnold James Stockwell, Clarissa Winona Goldwyn, Tobias Edwin Merrifield

This research proposes a blockchain-integrated trust mechanism for creating immutable audit trails in decentralized cloud storage. It enables transparent file access history, tamper-proof logging, and decentralized identity verification while improving data traceability for compliance-intensive industries.

Gregory Sebastian Litchfield, Miranda Alice Harborough, Tristan Oliver Wickham, Penelope Aurora Hartley, Francis Quentin Deerfield

This paper develops an AI-powered orchestration system for federated Kubernetes clusters across multi-cloud infrastructures. The system enables real-time workload distribution and autonomous resource scaling based on predictive analytics and policy-driven triggers to optimize cost and performance.

Harrison Jacob Fleetwood, Eleanor Cecilia Wadsworth, Patrick Noel Stanmore, Juliette Matilda Edgeworth, Miles Benjamin Halton

This study introduces a federated analytics framework that utilizes homomorphic encryption to preserve data privacy across cloud platforms. It supports secure computation of aggregated insights while maintaining compliance with data localization and sovereignty laws in cross-border applications.

Oscar Maxwell Farnsworth, Annabelle Daphne Wetherby, Leonard Amos Grimshaw, Rosalind Victoria Pennington, Vincent Louis Calderwood

This paper proposes a multi-objective genetic algorithm for optimizing virtual machine placement in cloud data centers. It balances energy consumption and performance metrics, ensuring efficient server utilization and reduced operational costs while maintaining service-level objectives across heterogeneous environments.

Leonard Philip Thorne, Isabel Harriet Weatherstone, Felix Gregory Stannington, Margot Louise Elbridge, Julian Isaac Cresswell

This research develops a secure inter-cloud file synchronization protocol leveraging identity-based encryption and deduplication. The approach reduces storage redundancy and protects against data leaks, ensuring compliance with user privacy requirements during synchronization between distributed cloud systems.

Walter Eugene Kingsmill, Georgina Eleanor Bradwell, Rupert Francis Ellington, Victoria Isobel Gainsborough, Charles Stanley Merton