This paper proposes a heuristic-driven model for cost-efficient storage tiering across distributed cloud data warehouses. The model classifies data by access patterns and compliance attributes to allocate storage optimally across hot, cold, and archival cloud tiers.

Harold Eugene Mortimer, Vivienne Charlotte Renwick, Martin Douglas Fairfax, Clara Roseleigh Templeton, Bernard Otto Kingsley

This study evaluates edge-aided cloud resilience using fault injection on distributed infrastructure monitoring systems. It quantifies failure propagation, detects response time degradations, and proposes mitigation strategies to enhance the robustness of cloud-dependent critical applications.

Gideon Clark Hayworth, Phoebe Louisa Waverly, Edmund Jasper Lockridge, Amelia Frances Montrose, Quentin Lawrence Brimley

This paper introduces a secure federated learning protocol for cloud-edge networks. It applies differential privacy mechanisms and encrypted gradient aggregation to protect user data while maintaining learning accuracy in multi-tenant intelligent applications.

Imogen Harriet Blackwood, Felix Gregory Stonewell, Cecilia Florence Whittingham, Malcolm Theodore Dunmore, Lydia Isabella Redgrave

This paper proposes a workload-aware virtual machine migration framework for reducing carbon emissions in cloud computing. It dynamically reallocates workloads to green-energy-powered data centers based on real-time grid carbon intensity metrics and service-level agreements.

Archibald Henry Wycliffe, Celeste Marianne Goodwin, Nigel Franklin Arbroath, Eloise Violet Channing, Rupert Wesley Penhaligon

This research presents an adaptive service mesh framework designed for multi-tenant microservice applications across cloud regions. The mesh dynamically configures traffic routing, observability, and access control, improving performance isolation and security for distributed tenants.

Julian Oscar Thornberry, Beatrice Evelyn Winscombe, Tobias Zachary Ashcombe, Meredith Iris Langston, Chester Alfred Ellington