This paper presents a deep contextual bandit algorithm for energy-efficient container placement in green cloud data centers. It dynamically adjusts scheduling strategies based on contextual energy metrics, reducing operational costs while maintaining compute performance and workload SLAs.

Julian Marcus Davenport, Li Qiao Nan, Neha Parthiban Reddy, Isla Grace Morrison, Sergio Ramon Fuentes

This research proposes a blockchain-supported audit mechanism for verifying workflow integrity in distributed cloud systems. Immutable transaction logs and real-time anomaly detection increase trust and accountability across multi-enterprise cloud collaborations.

Theodore Lucas Boyle, Zhang Rui Ling, Akshaya Mahesh Narayanan, Freya Madeline Hutton, Henri Claude Lafleur

This study develops predictive models for optimizing resource utilization in smart buildings using cloud-based analytics. Real-time data from IoT sensors is leveraged to forecast compute load patterns and reduce idle consumption across connected systems.

Declan Tobias Ford, Liu Yan Lin, Harini Venkata Subramaniam, Megan Isabel Thornton, Pablo Ernesto Aguilar

This paper presents a cloud-based framework for multilingual voice analysis using neural speech-to-text engines. It supports real-time transcription and sentiment detection across languages, facilitating seamless communication analytics for global organizations in distributed computing environments.

Samuel Pierre Thornton, Mei Lin Jia, Sandeep Rajendran Kumar, Olivia Grace Bennett, Hugo Marcel Delacroix

This study introduces a reinforcement learning approach to manage service mesh traffic across multi-cloud setups. The model dynamically routes API calls to reduce latency and improve reliability based on adaptive performance insights and real-time traffic behavior.

Cameron Elijah Whittaker, Zhang Hui Zhen, Vikas Chandra Sekhar, Sophie Amelia Lennox, Nicolas José Santiago