This paper explores the application of reinforcement learning algorithms for optimizing cloud resource allocation. The approach minimizes resource wastage and ensures efficient distribution of computational resources, improving overall performance and cost-effectiveness in cloud computing environments.

Alice Harper Thompson, John Carter McDonald, Emily Charlotte Robinson, Thomas James Harris, Sophia Claire Lewis

This paper investigates quantum computing methods for improving the security of cloud-based Internet of Things (IoT) systems. By leveraging quantum cryptography and encryption algorithms, the system provides a robust defense against cyber threats, ensuring secure data transmission and processing in IoT networks.

Noah Samuel Anderson, Grace Olivia Martin, Lucas Benjamin Clark, Lily Alexander Parker, Jack Edward Lee

This research focuses on the use of blockchain technology to enhance the security and transparency of cloud storage solutions. By employing decentralized ledgers and smart contracts, the proposed system ensures data integrity and reduces the risks associated with centralized cloud storage services.

Megan Victoria Adams, Daniel Luke Evans, Olivia Chloe Davis, Samuel Harry White, Emily Ruby Scott

This paper proposes an adaptive edge computing framework for real-time data processing in cloud-based IoT networks. The model dynamically allocates computing resources at the edge to reduce latency and bandwidth usage, improving the performance of IoT applications in cloud environments.

James David Harris, Isabella Sophia Hall, William Alexander Young, Emily Charlotte King, Benjamin Michael Johnson

This paper investigates the use of AI-powered data analytics for predictive maintenance in cloud-connected industrial systems. The approach integrates machine learning algorithms to predict equipment failures and optimize maintenance schedules, reducing downtime and improving operational efficiency in manufacturing environments.

Jacob Matthew Thompson, Ella Grace Evans, Alexander Daniel King, Charlotte Hannah Lewis, Oliver Joshua Walker

This paper explores a hybrid framework combining blockchain and cloud storage to ensure enhanced security and data integrity. By integrating decentralized blockchain technology with cloud-based services, the system improves data management, reduces risks, and guarantees transparency in cloud storage environments.

Samuel George Walker, Emma Lucy Evans, Charlotte Kate Harrison, John Philip Martin, Olivia Grace Carter

This paper proposes a distributed edge computing framework for real-time analytics in smart cities. By integrating edge computing with cloud services, the system facilitates fast processing of IoT data, enabling cities to optimize resources, reduce congestion, and enhance citizen services with real-time insights.

Aiden Lucas Scott, Isabella Mia Wright, Benjamin John Turner, Harper Olivia Ross, Daniel Emily Green

This paper discusses the use of AI-powered cloud-based systems for efficient healthcare management. The proposed system focuses on secure storage and real-time analysis of patient data, improving treatment accuracy, operational efficiency, and ensuring the privacy and integrity of medical records.

Alexander Julian Moore, Olivia Charlotte Anderson, Noah James Mitchell, Emily Sarah King, Lucas Gabriel Smith