This paper explores the application of distributed algorithms to optimize the performance of wireless sensor networks. By utilizing real-time data processing and efficient resource allocation, it ensures high throughput and energy-efficient communication in large-scale networks for environmental monitoring and smart agriculture applications.

John William Smith, Sarah Emma Thompson, Michael David Clark, Hannah Elizabeth White, Richard James Lee

This survey paper reviews cloud-based data storage and security solutions for IoT networks. By focusing on scalable storage techniques and encryption protocols, it highlights the advancements made in ensuring the confidentiality and integrity of data transmitted between IoT devices and the cloud.

Isabella Rose Green, Samuel Joseph Miller, Ethan William Johnson, Oliver Benjamin Davis, Liam Alexander Taylor

This paper introduces a blockchain-based consensus protocol for ensuring secure communication in ad-hoc sensor networks. By leveraging the immutability and decentralized nature of blockchain, the protocol ensures secure data transmission and reduces the vulnerability of sensor nodes to malicious attacks in critical infrastructure networks.

Cheng Wei Zhang, Li Xiaohui Wang, Chen Yu Li, Hua Mei Wang, Zhi Rong Li

This study focuses on designing low-cost sensor networks tailored for environmental monitoring in developing countries. The proposed system utilizes energy-efficient protocols and low-cost sensors to provide real-time environmental data, making it accessible to local authorities for better disaster management and sustainable development.

Emily Olivia Harris, Thomas Alexander Roberts, Ava Isabella Wright, Benjamin Michael Harris, Sophia Charlotte Evans

This research investigates the use of homomorphic encryption for enhancing data privacy in cloud-based IoT systems. The paper explores how this encryption technique enables computations on encrypted data, ensuring the confidentiality of sensitive information while allowing real-time processing in IoT applications across various domains.

David Richard Brown, George Alexander Walker, Charlotte Elizabeth Turner, Henry William Scott, Emily Anne Mitchell

This paper proposes a novel distributed machine learning algorithm designed to optimize resource allocation in IoT networks. By leveraging real-time data analysis, the algorithm improves network performance and ensures efficient resource utilization, providing a scalable solution for smart cities and industrial IoT applications.

James Henry Adams, Patricia Rose Clark, William Daniel Moore, Jessica Sarah Martin, Thomas Edward Johnson

This research introduces a blockchain-based authentication system to enhance security in cloud-based IoT networks. By integrating blockchain's decentralization and immutability features, the system ensures secure and tamper-proof authentication of devices and data transmission, preventing unauthorized access in critical infrastructure applications.

Alice Maria Davies, Benjamin Mark Robinson, Charlotte Elizabeth Lewis, David John Wilson, George Andrew Brown