This paper explores a cost-aware strategy for storing redundant datasets across multi-tenant clouds. It proposes adaptive erasure coding and smart replication policies to reduce cost while ensuring fault tolerance and high availability.

Brayden Zane Mitchell, Mei Ling Zhao, Ramesh Abhinav Kumar, Natalie Brielle Sanders, Felix Alejandro Espinoza

This research presents a TCN-based framework with self-attention for detecting anomalies in cloud infrastructure. The model effectively captures temporal dependencies and identifies outliers across system logs, aiding proactive infrastructure monitoring and fault resolution.

Declan Rhys Patterson, Yang Qi Fang, Arjun Surya Menon, Olivia Mae Summers, Pedro Ignacio Velasquez

This study proposes a privacy-focused federated learning framework tailored for smart city systems. Leveraging encrypted aggregation and hierarchical training, the model ensures data locality while preserving performance across multiple cloud-edge environments.

Jaxon Cole Winters, Li Jia Ning, Vishal Kiran Reddy, Chloe Danielle Morgan, Marco Antonio Delgado

This paper presents a predictive scaling system for allocating cloud resources in video streaming platforms. It models user behavior patterns to anticipate demand fluctuations, dynamically adjusting resources for smooth delivery and minimal cost.

Sawyer Julian Grant, Zhang Min Xue, Aniket Mukesh Chavan, Grace Lily Armstrong, Thiago Rafael Torres

This research introduces a fault-tolerant system for robotics applications managed via the cloud. It uses redundant workflow replication at the edge to ensure reliability and consistent performance during cloud service disruptions or latency spikes.

Jude Camden Hayes, Yu Wei Xiang, Tanay Sudhir Joshi, Stella Ava Newton, Eduardo Manuel Cardoza

This paper introduces an intelligent load balancing framework for multi-cloud applications. It uses context-aware decision engines powered by AI to dynamically route workloads based on latency, bandwidth, and cost, optimizing system efficiency and user experience.

Tristan Leo Myers, Wu Jie Nan, Sandeep Rajan Pillai, Harper Elise Monroe, Esteban Roberto Fuentes

This paper proposes a blockchain-integrated cloud model for secure supply chain monitoring. It supports tamper-proof transaction logging from edge nodes and real-time verification through distributed consensus, ensuring transparency and trust across decentralized industrial systems.

Caleb Rowan Whitaker, Lin Wei Han, Anshul Tejas Pandit, Isla Madeleine Parker, Bruno Henrique Castaneda