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Saad Abdullah AlAhmadi | سعد عبدالله الأحمدي

Professor

Professor in Computer Science - Specialty: Artificial Intelligence (AI), Cybersecurity, and the Internet of Things (IoT)

علوم الحاسب والمعلومات
Building 31 (CCIS Building) - 2nd Floor - Room 2179
المنشورات
مقال فى مجلة
2023

PF-EdgeCache: Popularity and freshness aware edge caching scheme for NDN/IoT networks, Pervasive and Mobile Computing

Named Data Networking (NDN) is considered an appropriate architecture for IoT as it naturally supports consumer mobility and provides in-network caching capabilities as leverage to meet IoT requirements. Some caching techniques have been introduced to meet IoT application requirements and enforce the caching at the network edge. However, it remains challenging to design a popularity and freshness aware caching technique that places cached contents at the edge of the network as close to consumers as possible in a natural and simple manner without resorting to cumbersome networking mechanisms and hard-to-insure assumptions. In this paper, we propose PF-EdgeCache, an efficient popularity and freshness aware caching technique that naturally brings requested popular contents to the edge of the network in a manner fully compliant with the NDN standard. Simulations performed using the ndnSIM simulator and a large transit stub topology clearly show the competitiveness of PF-EdgeCache in terms of server hit reduction, eviction rate, and retrieval time compared to some representative work proposed in the literature.

نوع عمل المنشور
Research
اسم الناشر
Pervasive and Mobile Computing, Elsevier
رقم المجلد
91
الصفحات
101782
مزيد من المنشورات
publications

Internet of Things (IoT) networks’ wide range and heterogeneity make them prone to cyberattacks. Most IoT devices have limited resource capabilities (e.g., memory capacity, processing power, and…

2025
تم النشر فى:
Sensors
publications

Machine Learning (ML) has been exploited across diverse fields with significant success. However, the deployment of ML models on resource-constrained devices, such as edge devices, has remained…

2025
تم النشر فى:
IEEE Access
publications

One of the most promising applications for electroencephalogram (EEG)-based brain–computer interfaces (BCIs) is motor rehabilitation through motor imagery (MI) tasks. However, current MI training…

2024
تم النشر فى:
Sensors