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Performance Analysis of the Preemption Mechanism in TSNMurselović, Lejla January 2020 (has links)
Ethernet-based real-time network communication technologies are nowadays a promising communication technology for industrial applications. It offers high bandwidth, scalability and performance compared to the existing real-time networks. Time-Sensitive Networking is an enhancement for the existing Ethernet standards thus offers compatibility, cost efficiency and simplified infrastructure, like previous prioritization and bridging standards. Time-Sensitive Networking is suitable for networks with both time-critical and non-time-critical traffic. The timing requirements of time-critical traffic are undisturbed by the less-critical traffic due to TSN features like the Time-Aware Scheduler. It is a time-triggered scheduling mechanism that guarantees the fulfilment of temporal requirements of highly time-critical traffic. Features like the Credit-Based Shapers and preemption result in a more efficiently utilized network. This thesis focuses on the effects that the preemption mechanism has on network performance. Simulation-based performance analysis of a singe-node and singe-egress port model for different configuration patterns is conducted. The simulation tool used is a custom developed simulator called TSNS. The configuration patterns include having multiple express traffic classes. In a single-egress port model, the most significant performance contributor is the response time and this is one of the simulation measurements obtained from the TSNS network simulator. The comparison between the results of these different network configurations, using realistic traffic patterns, provides a quantitative evaluation of the network performance when the network is configured in various ways, including multiple preemption scenarios.
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Get In Sync With TSN : A Study of Partially Synchronized TSN NetworksJohansson, Andreas Johansson January 2022 (has links)
Automotive and industrial embedded systems are increasingly dependent on real-time capabilities. TSN aims to offer flexibility of the traffic by providing Ethernet with hard and soft real-time capabilities which allows for integration with other protocols in legacy systems. TSN requires the network to be fully synchronized to achieve high performance. However, there are cases where legacy systems are not able to synchronize with TSN. These systems might nonetheless be able to synchronize with each other through their legacy synchronization mechanisms. In this thesis, we have investigated effects in terms of jitter and clock drift in endpoints by synchronizing them with each other and passing communication through an unsynchronized intermediary TSN switch. Our results revealed that with the introduction of TSN, jitter was reduced, while clock drift between endpoints and the TSN switch was introduced. The results show that negative clock drift leads to packets missing their scheduled TSN windows and positive drift leads to packets being dropped in the switch buffer queues. We proposed two solutions in order to manage the experienced clock drift. In one solution we statically changed the switch cycle, and in the other, we let the receiver node dynamically update the sending period in the sender node. In the static solution, the clock drift was reduced from negative eight microseconds per second to two nanoseconds per second. In the dynamic solution, a packet error rate of one per 100 seconds was reduced to zero errors in 19 hours.
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Implementation and evaluation of TSN scheduling algorithms / Implementation och bedömning av TSN-schemaläggningsalgoritmerSvensson, Emanuel January 2023 (has links)
Time Sensitive Networking (TSN) is a standard that extends Ethernet, providing deterministic guarantees to internal communications. The standard is finding use in many different fields such as modern cars whose networks are getting increasingly complex. One problem with TSN is the NP-hard problem of scheduling network flows, the process in which schedules are made to ensure that network flows demanding real-time guarantees have their requirements met.The goal of thesis is to implement two different scheduling algorithms. The evaluation of the implementations measure how they perform in regards to finding possible schedules and for how much time they take with an increasing number of network flows to schedule. The algorithms approaches to scheduling are then discussed and judged in comparison with the results. This thesis implements two different algorithms, a fine-grained algorithm and a coarse-grained algorithm. The difference between the algorithms lie in how fine-grained their scheduling is. Where the fine-grained algorithm adopts the lowest resolution permissible, the coarse-grained algorithm achieves the highest resolution possible in the schedule. The results show that the coarse-grained algorithm becomes unacceptably slow because of its fine-grained scheduling. In a scenario where algorithms 1 and 2 work with the same flows, the coarse-grained algorithm is 42x slower than the fine-grained algorithm in the worst case.The conclusion is that the finest possible scheduling is not a feasible approach because of it taking too much time to execute for a very small amount of flows. / Time Sensitive Networking (TSN) är en standard som utökar Ethernet genom att lägga till deterministiska garantier till intern kommunikation. Standarden har börjat användas inom fält såsom moderna bilar vars nätverk blir allt mer komplexa. Ett problem med TSN är det NP-hard svåra problemet med att schemalägga nätverksflöden, processen i vilket scheman uträknas för att garantera att nätverksflöden som kräver realtidsgarantier får sina krav uppfyllda. Uppsatsens mål är att implementera två olika schemaläggningsalgoritmer. Evalueringstesterna mäter algoritmernas förmåga att finna möjliga scheman för olika mängder av nätverksflöden och hur lång tid det tar.Algoritmernas tillvägagångssätt för schemaläggning jämförs och bedöms därefter.Denna uppsats implementerar två olika algorithmer, en finkorning algorithm och en grovkornig algoritm. Namnen kommer från finkornigheten i algoritmernas schemaläggning. Den finkorniga algoritmen schemalägger med finkornighet och den grovkorniga algoritmen schemalägger med grovkornighet. Resultatet från testerna och evalueringen visar att när algoritmerna schemalägger samma flöden tar den grovkorniga algoritmen som värst 42 gånger mer tid att slutföra sina beräkningar. Slutsatsen är att finkorning schemaläggning är inte applicerbar då det tar för lång tid att utföra för en väldigt liten mängd flöden.
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