2 research outputs found
Towards Executing Computer Vision Functionality on Programmable Network Devices
By offering the possibility to already perform processing as packets traverse the network, programmable data planes open up new perspectives for applications suffering from strict latency and high bandwidth requirements. Real-time Computer Vision (CV), with its high data rates and often mission- and safety-critical roles in the control of autonomous vehicles and industrial machinery, could particularly benefit from executing parts of its logic within network elements. In this paper, we thus explore what it takes to bring CV to the network. We present our work-in-progress efforts of implementing a line-following algorithm based on convolution filters on a P4-programmable NIC. We find that by appropriately identifying regions of interest in the image data and by diligently distributing the necessary calculations among the various match/action stages of the ingress- and egress pipelines of the NIC, our prototypical implementation can achieve over 19 decisions per second on 640x480 px grayscale images with filters large enough to guide a small autonomous car through various courses
A Survey on Data Plane Programming with P4: Fundamentals, Advances, and Applied Research
With traditional networking, users can configure control plane protocols to
match the specific network configuration, but without the ability to
fundamentally change the underlying algorithms. With SDN, the users may provide
their own control plane, that can control network devices through their data
plane APIs. Programmable data planes allow users to define their own data plane
algorithms for network devices including appropriate data plane APIs which may
be leveraged by user-defined SDN control. Thus, programmable data planes and
SDN offer great flexibility for network customization, be it for specialized,
commercial appliances, e.g., in 5G or data center networks, or for rapid
prototyping in industrial and academic research. Programming
protocol-independent packet processors (P4) has emerged as the currently most
widespread abstraction, programming language, and concept for data plane
programming. It is developed and standardized by an open community and it is
supported by various software and hardware platforms. In this paper, we survey
the literature from 2015 to 2020 on data plane programming with P4. Our survey
covers 497 references of which 367 are scientific publications. We organize our
work into two parts. In the first part, we give an overview of data plane
programming models, the programming language, architectures, compilers,
targets, and data plane APIs. We also consider research efforts to advance P4
technology. In the second part, we analyze a large body of literature
considering P4-based applied research. We categorize 241 research papers into
different application domains, summarize their contributions, and extract
prototypes, target platforms, and source code availability.Comment: Submitted to IEEE Communications Surveys and Tutorials (COMS) on
2021-01-2