Implementation and analysis of a priority-based content popularity-aware caching strategy in named data networking-based internet of things

• Main Author: Yahui, Meng
• Format: Thesis
• Language: English; English; English
• Published: 2025
• Subjects: TK5015.888 Web sites
• Online Access: https://etd.uum.edu.my/11936/1/depositpermission.pdf; https://etd.uum.edu.my/11936/2/s903348_01.pdf; https://etd.uum.edu.my/11936/3/s903348_02.pdf; https://etd.uum.edu.my/11936/

Named Data Networking (NDN) is a new Internet architecture that addresses location dependent issues in the Internet of Things (IoT). It helps to minimize global data traffic and enhances Internet services by integrating caching techniques. However, choosing the right node for content transmission is a challenge, as each node decides where to cache content, affecting network performance. This study examines the latest NDN-based IoT caching solutions, with a focus on enhancing the accessibility and visibility of cached content and presented a Priority-based Content Popularity-Aware Caching (PCPA). PCPA is a technique that needs the involvement of the Content Selection Mechanism (CSM), Content Caching Mechanism (CCM), and Backup Caching Mechanism (BCM) to perform the complete functionality. CSM identifies the higher-priority content via dynamic selection, whereas CCM calculates the ideal places for caching chosen information depending on user desire. However, the BCM provides the ideal cache location for the least frequently downloaded content to keep it alive and meet successive user needs. To analysis the performance of the PCPA caching approach, it is compared to three benchmark strategies: Cache Everything Everywhere, probabilistic Caching strategy for the internet of things, and Caching Fresh and Popular Content. This study did the comparison using the simulation software NDN-SIM. The PCPA outperforms the compared techniques in terms of content retrieval latency, average hop count, cache hit ratio, and energy usage. The approximate findings demonstrate that the PCPA works better when the cache hit ratio is enhanced by 19.15% and 30.7% decreases in hop count with various alpha values and constant cache sizes. Moreover, the latency is cut by 31.3%, and a 27.5% reduction in energy usage is documented with varied cache sizes and a constant alpha value. Therefore, in the future, PCPA will be useful for new NDN-based technologies like 5G/6G, computing platforms, and the IoT