AI for IoT-NDN: Enhancing IoT with Named Data Networking and Artificial Intelligence
Mohamed Ahmed M. Hail, Ali Abdulqader Bin-Salem, Waddah Munassar · 2024
This paper presents a comprehensive study on the integration of Artificial Intelligence (AI) methodologies within the rapidly evolving Internet of Things (IoT) landscape, particularly focusing on Named Data Networking (NDN). As IoT permeates various sectors like Smart Homes, Cities, Grids, and Health, NDN emerges as a robust solution for managing the extensive data flow, addressing key aspects such as naming, mobility, data aggregation, and security. Despite NDN's efficacy, its implementation confronts challenges related to high operational costs, influenced by bandwidth usage and network popularity. Our research investigates how AI can enhance NDN's functionality in IoT contexts, aiming to optimize data dissemination and network efficiency. The study explores AI's potential in bolstering IoT capabilities within the NDN framework, offering insights into future directions for IoT-based NDN networks.