This study presents a dynamic resource scaling framework using predictive analytics to anticipate cloud workload variations. It adapts provisioning strategies in real time, enhancing system responsiveness and minimizing resource waste under fluctuating demand conditions in cloud-hosted environments.

Clinton George Ashbury, Madeleine Rosa Langford, Tobias Harold Whitmore, Helena Grace Redford, Miles Albert Cranston

This research proposes a blockchain-integrated cloud disaster recovery framework that ensures data integrity and authenticity. It uses distributed consensus to verify recovery transactions, enabling secure and transparent failover mechanisms during natural disasters or data center failures.

Frederick Owen Litchfield, Penelope Irene Aldridge, Quentin Douglas Heathridge, Sabrina Clarisse Bellamy, Gregory Vincent Thornhill

This study introduces a federation mechanism for cloud providers to collaboratively manage workload offloading across geographies. It prioritizes regions with renewable energy availability, reducing carbon footprint while maintaining workload balance and ensuring SLA compliance in multi-cloud deployments.

Douglas Irving Coleridge, Fiona Bethany Winslow, Jasper Lionel Renwick, Matilda Juliet Stonebridge, Simon Edgar Lockhart

This paper explores a privacy-preserving framework for federated learning across cloud domains. It employs encrypted model updates and secure aggregation techniques, enabling decentralized training without exposing raw data, ensuring compliance with data protection laws and ethical AI guidelines.

Henrietta Florence Withers, Malcolm Theodore Crenshaw, Clara Elise Pennington, Oliver Thaddeus Langham, Theresa June Lockridge

This research introduces a latency-optimized serverless architecture that dynamically migrates containers and adjusts event scheduling across the edge-cloud continuum. It reduces cold-start delays and optimizes execution times for distributed applications with strict latency constraints.

Alfred Montgomery Shields, Beatrice Eloise Radcliffe, Lionel Benedict Greyson, Francesca Imogen Cartwright, Hugo Barnaby Underhill

This paper proposes a secure multi-cloud storage system using encryption sharding and decentralized access control. It protects sensitive enterprise data against breaches while allowing seamless data sharing and access validation across heterogeneous cloud providers using zero-trust principles.

Margaret Elaine Stanford, Douglas Everett Kinsley, Charlotte Mae Langston, Franklin Lloyd Dorsey, Eleanor Beatrix Crowley

This study introduces a cost-optimized resource allocation strategy in multi-tenant cloud platforms. By analyzing tenant-specific usage patterns and SLA priorities, it dynamically reallocates virtual resources, enhancing performance while maintaining fairness and reducing operational costs.

Jeremy Nathaniel Blackwood, Amelia Rose Forsythe, Samuel Atticus Ellington, Victoria Noelle Chadwick, Benjamin Oliver Trenton