Machine learning is widely used to solve networking challenges, ranging from traffic
classification and anomaly detection to network configuration. However, machine learning …

Programmable data plane technologies enable the systematic reconfiguration of the low-
level processing steps applied to network packets and are key drivers toward realizing the …

Traditionally, the data plane has been designed with fixed functions to forward packets using
a small set of protocols. This closed-design paradigm has limited the capability of the …

Machine learning is currently driving a technological and societal revolution. While
programmable switches have been proven to be useful for in-network computing, machine …

User-plane machine learning facilitates low-latency, high-throughput inference at line rate.
Yet, user planes are highly constrained environments, and restrictions are especially …

Using programmable network devices to aid in-network machine learning has been the
focus of significant research. However, most of the research was of a limited scope …

Cervical cancer causes the fourth most cancer-related deaths of women worldwide. Early
detection of cervical intraepithelial neoplasia (CIN) can significantly increase the survival …

The demand for machine learning (ML) has increased significantly in recent decades,
enabling several applications, such as speech recognition, computer vision, and …

The rat race between user-generated data and data-processing systems is currently won by
data. The increased use of machine learning leads to further increase in processing …

Intrusion detection through classifying incoming packets is a crucial functionality at the
network edge, requiring accuracy, efficiency and scalability at the same time, introducing a …