This study introduces a reinforcement learning-based approach for ensuring fair resource isolation in multi-tenant cloud environments. It dynamically tunes policy parameters in response to workload variation, improving tenant satisfaction and resource utilization in scalable cloud clusters.

Kyle Nathaniel Brooks, Li Sheng Xiu, Ananya Ramesh Mehta, Frances Mae Callahan, Bruno Eduardo Marques

This research explores a dynamic service mesh strategy to enable traffic re-routing and failover during microservice disruptions. The model improves application resilience and responsiveness using policy-driven mesh updates and context-aware monitoring data.

Felix Andrew Newton, Chen Jia Long, Rakesh Vijay Nambiar, Isabella June Rowan, Eduardo Pablo Cruz

This paper presents a prediction-based approach for optimizing serverless function placement. It forecasts execution durations and cost overheads across cloud regions, dynamically selecting deployment strategies that reduce cloud billing without sacrificing performance.

Caleb Emerson Wells, Wang Liu Qiang, Pranav Sachin Khurana, Harper Elise Monroe, Alejandro Miguel Ruiz

This work proposes a smart contract-based marketplace for scheduling workflows in federated clouds. It ensures transparency, fair resource trading, and verifiable SLA compliance using blockchain protocols to coordinate across autonomous cloud operators.

Miles Orion Tate, Zhuo Liang Hui, Akshara Kishore Iyer, Vivian Grace Peterson, Thiago Mario Delgado

This paper introduces a compliance monitoring system using policy-as-code integrated into CI/CD workflows. The framework identifies misconfigurations and security violations in real time, automatically flagging anomalies and enforcing regulatory alignment throughout cloud-native delivery pipelines.

Isaiah Marcus Flynn, Li An Rong, Sanya Dev Patel, Lily Rebecca Vaughn, Rafael Andres Mendez