This paper introduces a reinforcement learning framework for orchestrating serverless functions across cloud regions. The model adapts to dynamic pricing and execution delays, optimizing cost and latency trade-offs for globally distributed event-driven applications in real time.

Amira Louise Bennett, Dev Mehul Srinath, Zhang Wei Tong, Olivia Marie Keating, Rafael Tomas Navarro

This research proposes a lightweight virtualization architecture combining encrypted containers and stateless microservices to optimize cloud-IoT integration. The model improves security, reduces memory overhead, and enhances scalability for sensor-driven services in industrial and smart city deployments.

Nathaniel Curtis Shaw, Wen Qiang Lu, Saanvi Raghavi Menon, Helena Kate Douglas, Francesco Luca Ferrara

This paper presents a cloud-native resource scheduler optimized for distributed quantum simulations. By leveraging GPU-awareness and workload profiling, the system efficiently allocates compute tasks, minimizing latency and maximizing throughput for simulation-intensive cloud workflows.

Isabelle May Norton, Liang Zhi Wen, Arnav Surya Chandrasekar, Julian Oscar Grant, Chloe Adriana Wolfe

This paper proposes a secure communication framework for cross-border cloud services. It integrates quantum key distribution with blockchain smart contracts to establish trust and encryption integrity, enhancing data sovereignty compliance across international hybrid cloud deployments.

Vincent James Hall, Meilin Zhao Chen, Dhruv Ramesh Subramaniam, Amelia Scarlett Webb, Leonardo Alberto Castillo

This work presents a context-aware mechanism to reduce energy consumption during AI inference across cloud-edge architectures. It dynamically adjusts precision levels and workload offloading based on contextual inputs, achieving significant energy savings without compromising output fidelity.

Lila Florence Sanders, Wang Lei Jun, Nirav Jitesh Bhagat, Emily Grace Carter, Pablo Javier Ruiz

This study presents a self-healing architecture for cloud platforms. It uses AI-driven policy adaptation and feedback loops to detect SLA violations in real time and trigger automated recovery actions, enhancing system resilience and uptime.

Samuel Leon Rivers, Jia Ming Zhang, Anjali Neeraj Iyer, Olivia Rose Blackwood, Matteo Lorenzo Esposito

This paper introduces an AI-powered orchestration framework that ensures multicloud service continuity during regional outages. It monitors latency trends, predicts partition risks, and automatically migrates services to alternate regions, maintaining SLA and operational integrity.

Grace Eleanor Wilkinson, Hao Liang Wei, Raghav Nitin Kapoor, Marcus Edward Shaw, Beatriz Lucia Delgado