This research proposes a resource allocation model to optimize cloud computing resources for AI-powered applications. It focuses on dynamic resource allocation techniques, ensuring efficient utilization of computational power, memory, and storage, while maintaining the performance of AI algorithms in real-time applications.

Benjamin Scott Taylor, Sophie Claire Morgan, Nicholas Allen Walker, Lucas David Hunter, Abigail Emily Davis

This paper investigates decentralized data privacy solutions in cloud computing using blockchain technology. It discusses the potential of blockchain in ensuring secure data transactions, enhancing privacy, and providing transparency in cloud environments, especially for sensitive data storage and access management.

William James Green, Olivia Emily Carter, Thomas Andrew Hughes, Mia Catherine Harris, Joseph Samuel Turner

This study explores cloud-based edge computing for real-time data processing in autonomous vehicles. It highlights the integration of edge computing with cloud infrastructure to process data on the edge, reducing latency and enabling real-time decision-making for autonomous driving systems.

Oliver Thomas Mitchell, Ethan James Wilson, Sophie Victoria Clarke, Matthew Daniel Johnson, Amelia Grace Lee

This paper presents a multi-agent system for efficient resource management in cloud datacenters. The proposed system dynamically allocates resources, enhances load balancing, and optimizes energy consumption, thereby improving operational efficiency and reducing operational costs for cloud service providers.

Lucas Benjamin Scott, Charlotte Amelia Nelson, Henry Samuel Brown, Grace Eleanor Evans, James Frederick Stewart

This paper proposes a blockchain-enabled cloud security framework to ensure data integrity and privacy in healthcare systems. The framework utilizes blockchain's decentralized nature for secure data storage and transmission, while ensuring compliance with privacy regulations and preventing data tampering.

Michael David Harris, Olivia Sophia Martinez, Isabella Grace Cooper, Ethan Alexander Morris, Harper Amelia Thompson

This research investigates the use of artificial intelligence (AI) for predictive maintenance in cloud-based Internet of Things (IoT) networks. The study focuses on AI algorithms that predict potential failures, optimize maintenance schedules, and improve the overall performance and longevity of IoT devices.

Alexander Charles Green, Scarlett Emily Carter, James William Lewis, Victoria Grace Moore, Benjamin James Evans