A survey on in-network computing: Programmable data plane and technology specific applications
In comparison with cloud computing, edge computing offers processing at locations closer to
end devices and reduces the user experienced latency. The new recent paradigm of in …
end devices and reduces the user experienced latency. The new recent paradigm of in …
In-network machine learning using programmable network devices: A survey
Machine learning is widely used to solve networking challenges, ranging from traffic
classification and anomaly detection to network configuration. However, machine learning …
classification and anomaly detection to network configuration. However, machine learning …
An exhaustive survey on p4 programmable data plane switches: Taxonomy, applications, challenges, and future trends
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 …
a small set of protocols. This closed-design paradigm has limited the capability of the …
{ATP}: In-network aggregation for multi-tenant learning
Distributed deep neural network training (DT) systems are widely deployed in clusters where
the network is shared across multiple tenants, ie, multiple DT jobs. Each DT job computes …
the network is shared across multiple tenants, ie, multiple DT jobs. Each DT job computes …
Do switches dream of machine learning? toward in-network classification
Z **ong, N Zilberman - Proceedings of the 18th ACM workshop on hot …, 2019 - dl.acm.org
Machine learning is currently driving a technological and societal revolution. While
programmable switches have been proven to be useful for in-network computing, machine …
programmable switches have been proven to be useful for in-network computing, machine …
The programmable data plane: Abstractions, architectures, algorithms, and applications
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 …
level processing steps applied to network packets and are key drivers toward realizing the …
Automating in-network machine learning
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 …
focus of significant research. However, most of the research was of a limited scope …
IIsy: Practical in-network classification
C Zheng, Z **ong, TT Bui, S Kaupmees… - arxiv preprint arxiv …, 2022 - arxiv.org
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 …
data. The increased use of machine learning leads to further increase in processing …
Reducing latency in virtual machines: Enabling tactile Internet for human-machine co-working
Software-defined networking (SDN) and network function virtualization (NFV) processed in
multi-access edge computing (MEC) cloud systems have been proposed as critical …
multi-access edge computing (MEC) cloud systems have been proposed as critical …
Programmable switches for in-networking classification
Deploying accurate machine learning algorithms into a high-throughput networking
environment is a challenging task. On the one hand, machine learning has proved itself …
environment is a challenging task. On the one hand, machine learning has proved itself …