This paper introduces a delay-aware compression and caching layer for hybrid cloud data transfers. It reduces latency by dynamically adjusting compression based on congestion and enhances throughput during real-time data-intensive operations across multi-cloud infrastructures.

Anderson Kai Mitchell, Chen Xiu Fang, Vikram Shailesh Nambiar, Layla June Roberts, Rodrigo Felipe Morales

This research presents a blockchain framework for tracking data provenance across cloud-edge boundaries. It leverages multi-signature verification to ensure integrity, transparency, and non-repudiation, safeguarding collaborative AI pipelines and IoT data ingestion workflows.

Malcolm Isaiah Tate, Wu Yue Wen, Harshil Prakash Bhargava, Daisy Aurora Richardson, Emilio Santiago Vargas

This work introduces a graph neural model for task offloading in vehicular networks. The system dynamically selects edge or cloud targets based on connectivity graphs and latency thresholds, ensuring stable service quality in mobile environments.

Dominic Jalen Greene, Shen Ming Hui, Anirudh Gopal Tiwari, Mia Scarlett Lawrence, Fernando Javier Rivas

This study evaluates the application of lattice-based cryptographic schemes to protect cloud data workflows across international boundaries. It addresses regulatory compliance while resisting threats from future quantum adversaries.

Everett Miles Finley, Zhao Li Ning, Tejas Ramesh Bhosale, Paige Meredith Foster, Manuel Alberto Cruz

This paper presents a security system for containers in cloud-native environments. It uses runtime behavior profiling and adaptive feedback loops to detect anomalies, offering real-time mitigation for policy breaches without introducing overhead on orchestrated platforms.

Nelson Troy Blackburn, Wang Zhen Rui, Manan Prateek Khosla, Isabelle Noelle Simmons, Andres Emilio Pacheco

This study introduces an adaptive auto-scaling method tailored for ML services in global cloud environments. By incorporating latency patterns and regional demand fluctuations, it ensures seamless scaling while maintaining real-time responsiveness and system cost-efficiency.

Grayson Elijah Stone, Li Hao Feng, Rithvik Suresh Anand, Emily Jean Porter, Alejandro Tomas Rivera