Root Cause Analysis for TSN
network monitoring, root cause analysis, Linux, P4, TAS, TSN
Time Sensitive Networks aim to provide for mechanisms and methods for deterministic delay and jitter in industrial networks. Sources of delay and jitter in a TSN can be numerous, e.g., misconfigured or incorrectly dimensioned TAS schedules, congested egress ports, large clock jitter in distributed time synchronization, congestion at egress / ingress ports of the end-stations, variable switch backplane delays etc. are all possible causes of poor end-to-end performance.
In this work, an existing approach to end-to-end monitoring of transmission delay and jitter will be extended to support for quick identification of source of the anomaly in a TSN scenario (i.e., the root cause). Two or more approaches will be proposed to cater for end-to-end monitoring of TSN streams, relying on:
1) intermediate, pre-placed network TAPs;
2) hardware / software data plane agents capable of telemetry and dynamic re-programming to support the quick identification of anomaly sources for individual streams.
Any resulting overhead of the intermediary monitoring solution will be quantified for consideration in the TSN stream planning. The work will hence implement and validate the monitoring mechanisms in an existing TSN testbed that relies on a Linux-based control plane, and will optionally involve P4-based middlebox devices to serve as intermediate monitoring entities.
 802.1Qbv - Enhancements for Scheduled Traffic - http://www.ieee802.org/1/pages/802.1bv.html
 Improving Network Monitoring and Management with Programmable Data Planes - https://p4.org/p4/inband-network-telemetry/
- Good knowledge of networking concepts and architectures
- Good knowledge and practical experiences with Linux networking
- Good knowledge of Python, C or Rust
- Any prior experience with TSN, P4, SDN is a plus but not mandatory
Safe Runtime Reconfiguration of TAS-based TSN schedules
optimization, metaheuristics, reconfiguration, TAS, TSN, simulation
Industry 4.0 scenarios have introduced the novel requirements for dynamic device-to-device interaction without strict plan-ahead interactions (typical of Industrial Ethernet of the last two decades). For example, the use cases of work piece de-attachment and interacting Automated Guided Vehicles (AGVs) in factory automation impose the need for dynamic inter-connection of distributed industrial applications at runtime  without a plan-ahead schedule.
Dynamic TSN stream establishment has been proposed by IEEE802.1 to address scenarios of applications requesting real-time communication services at runtime [2, 3]. TSN schedulers capable of computing the transmission schedules with guaranteed real-time properties (upper-bound constraints on latency, jitter, and guaranteed bandwidth) have accordingly been proposed in the past, however, they have traditionally focused on one-time / offline execution .
Combined with the requirement for dynamic and efficient resource (de-)allocation, transmission schedules must generally be adaptable at runtime in order to provide for maximum efficiency in network resource utilization. This work will investigate the runtime adaptation of TSN control and data plane to support for the dynamic stream allocation. Algorithms for adaptation of existing TAS-based schedules with minimal impact on availability (packet loss) and QoS guarantees for running TSN streams will be proposed, implemented, and validated. Novel metrics for stream consistency conservation may need to be proposed by the approach. The resulting approach will eventually be evaluated in NeSTiNg (OMNeT++/INET) simulator and/or a small-scale physical testbed comprising multiple TSN switches and end-stations.
 IEC/IEEE 60802 TSN Profile for Industrial Automation - https://1.ieee802.org/tsn/iec-ieee-60802/
 P802.1Qdd – Resource Allocation Protocol - https://1.ieee802.org/tsn/802-1qdd/
 802.1Qat - Stream Reservation Protocol -/ http://www.ieee802.org/1/pages/802.1at.html
 Dürr et al., No-wait Packet Scheduling for IEEE Time-sensitive Networks (TSN) - https://dl.acm.org/doi/abs/10.1145/2997465.2997494
- Very good knowledge of networking concepts and architectures
- Very good knowledge and practical experiences with Linux networking
- Good knowledge of Python, C, C++ or Rust
- Any prior experience with optimization methods and and tools and OMNeT++ is a plus
- Any prior experience with TSN is a plus
- Any prior experience with SDN is a plus
- Proficient English and/or German communication skills
- Ability to work and pursue solutions under limited supervision