Programmable Networks are of great importance. It is the starting point for making computer networks open for innovation, and enables the rapid introduction of new functionalities that make our networks more scalable, reliable and effective. Especially the data plane is important because it determines the speed, capacity and latency that distributed applications and services will experience. At Karlstad University, we have developed advanced level academic courses on how to make the network data plane more flexible and programmable.
About the course
Traditionally, network equipment has been seen as a closed box with little opportunity to invent. With the recent support of new programming languages such as P4, compiler and runtime support, the next generation of network equipment will be programmable, enabling new use cases. The course is divided into three modules. In the first module, we will introduce the concept of programmable data planes, including P4. In the second part, we will look into how we can use programmable data planes for data-center loadbalancing. Finally, part three covers techniques that enable network monitoring, in-network caching and facilitate simple computing operations with programmable data planes.
For students and researchers in the area of computer networking as well as networking designers, engineers or telecommunication specialists with interests for data plane programming.
The course is online-based, and its optional to go through it as credit bearing (4,5 ECTS) or as an open network course. For credit bearing there are special demands. The course is divided into three modules. Module two and three are independent from each other but both of them depend on module one.
Find out more about the different modules via the links below!
Module 1 - Introduction to dataplane programming
Module 2 - Load balancing for data-center networks
Module 3 - Network monitoring with programmable dataplanes
The course is part of WISR17 project, a collaboration between CTF, Computer Science, Karlstad Business School, and CMM at Karlstad University and companies from different business areas as external partners. The project is funded by KK-stiftelsen (The Knowledge Foundation) between 2018-2020.
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