This study implements a predictive auto-scaling system for cloud infrastructure using multi-seasonal ARIMA models. By learning workload fluctuations over time, the model improves cost-efficiency and responsiveness in dynamically varying compute demand environments.

Dorian Maxwell Fox, Bai Mei Chen, Gaurav Ramesh Iyer, Isla Katherine Banks, Tomas Alejandro Ruiz

This research introduces a federated data governance approach ensuring regulatory compliance across multi-cloud analytics platforms. It manages data residency, encryption, and access policies using a decentralized rules engine supporting global collaboration in regulated industries.

Quentin Elias Rhodes, Zhou Ling Xia, Sandeep Anil Varma, Eliza Charlotte Morton, Bruno Ricardo Fonseca

This paper proposes a state preservation framework for serverless workflows that ensures continuity after interruptions. By capturing execution context based on data dependencies, it enables real-time recovery and resilience in critical cloud functions.

Harrison Eli Cartwright, Lin Fei Yan, Rajeev Prakash Nair, Amber Josephine Wilkes, Rodrigo Luis Ferreira

This study explores post-quantum cryptography solutions for secure communication across cloud regions. It proposes a scalable hybrid key exchange protocol using lattice-based cryptographic primitives, ensuring resilience against future quantum decryption capabilities.

Ruben George Ellis, Yang Xiu Fang, Rituja Mahesh Jadhav, Florence Daisy Newton, Andres Felipe Cardenas

This paper introduces a reinforcement learning model for dynamic pricing in cloud service marketplaces. It adjusts resource costs based on real-time demand elasticity and historical patterns, optimizing provider revenue while maintaining user satisfaction.

Carter William James, Li Wei Xun, Nishant Raghavan Shetty, Lucy Evelyn Harper, Joao Marcos Almeida

This paper presents a GNN-based intrusion detection system for microservices. It models container interactions as graphs and identifies anomalies in communication behavior to protect cloud-native architectures from evolving threats and zero-day exploits.

Julian Francis Kemp, Wu Xian Tong, Raghavendra Sitaram Joshi, Lydia Anne Maxwell, Diego Santiago Herrera

This paper introduces a smart data replication framework for scientific cloud environments. It optimizes storage across tiers by analyzing dataset access frequency, latency sensitivity, and compliance needs, enhancing availability while minimizing redundant resource consumption.

Xander Tobias Graham, Gao Xiang Min, Arjun Mahesh Batra, Sophia Eleanor Hayes, Rafael Alberto Castillo

This study presents an energy-aware scheduling algorithm for Kubernetes that factors workload thermal signatures and cloud carbon indices. It dynamically allocates containers to minimize heat generation and carbon footprint without impacting service performance.

Declan Oliver Wade, Chen Jia Wei, Mehul Dinesh Solanki, Ava Lorraine Mitchell, Bruno Santiago Mendes