This study introduces an orchestration model that optimizes energy consumption during service deployment across hybrid cloud-edge infrastructures. It leverages predictive analytics and adaptive policies to dynamically manage resources while ensuring SLA compliance and minimizing environmental impact across heterogeneous computing layers.

Karthik Venu Gopal, Alice Morgan Bennett, Huang Yao Jie, Thomas Quentin Bradley, Emilio Santiago Alvarez, Zoey Faye Richmond

This paper proposes a blockchain-based framework for secure identity and access control across multi-vendor cloud systems. It enables trust, interoperability, and decentralized enforcement of access policies, promoting secure collaboration in distributed digital ecosystems without dependency on centralized authentication providers.

Yin Mei Qian, Benjamin Scott Mercer, Pranav Deepak Kumar, Valentina Grace Chapman, Jacob Elliott Knowles

This research introduces a graph-based AI framework for workload distribution in HPC environments. It dynamically maps resource availability to job priority using cost-efficiency models, reducing execution time and cloud overhead for compute-intensive tasks in multi-cloud scientific research workloads.

Wei Zhong Lin, Olivia Margaret Knight, Rajeev Narayan Subbiah, Ethan Charles Morley, Gabriella Ruth Mendoza

The study presents an AutoML pipeline for predicting resource demand in cloud-native applications. It leverages time-series telemetry data to train scalable models that forecast usage spikes and adjust compute allocations in microservice architectures to maintain performance and cost efficiency.

Aarav Deepan Raghunathan, Lily Rebecca Walsh, Daniel Kieran O’Donnell, Ming Cheng Hao, Isabella Marie Thornton

This paper introduces a deep graph neural model for autonomous resource balancing in multi-tier clouds. It enables real-time analytics by forecasting inter-node traffic, proactively redistributing load across edge, fog, and core layers to reduce latency and optimize throughput.

Feng Yu Hao, Isabella Jane Matthews, Nikhil Abhinav Patil, Alexander Rhys Holland, Sophia Grace Blackwell

This work introduces a policy-aware data tagging protocol for healthcare clouds. It ensures secure data handling from ingestion to archiving by tagging records with compliance attributes, allowing real-time auditability, automated retention, and role-based access enforcement across hybrid cloud deployments.

Jiang Hao Ren, Chloe Danielle Norton, Aditya Suresh Iyer, Leo Matthew Warner, Martina Isabel Alvarez

This study presents an AI-powered intrusion detection mechanism for securing containers in zero-trust cloud environments. It leverages behavioral profiling and anomaly detection to monitor runtime activity, automatically isolating compromised services and supporting policy-driven remediation at scale.

Sai Kiran Ramaswamy, Ava Harper Langston, Zhi Liang Xu, Henry Callum Brookes, Olivia Catherine Steele, Manuela Teresa Dominguez