Research on Low-Latency TTP–TSN Cross-Domain Network Planning Problem
Abstract
:1. Introduction and Motivation
Motivation
2. Literature Review
3. System Model
3.1. Time-Triggered Protocol
3.2. Time-Sensitive Network
3.3. TTP–TSN Gateway
3.4. TTP–TSN Network Model
3.4.1. Base Model
3.4.2. Low-Latency TTP–TSN Scheduling Model
3.4.3. Model Consistency Analysis
4. Research on Low-Latency TTP–TSN Network Planning
4.1. Engineered Time-Synchronization Algorithm
4.2. TTP–TSN Low-Latency Planning Algorithm
4.2.1. Routing Algorithm
4.2.2. Scheduling Algorithm
Algorithm 1: searchSuitablePit Algorithm |
4.2.3. TTP–TSN Gateway-Allocation Method
4.3. Algorithm Analysis
4.3.1. Schedulability Analysis
4.3.2. Approximation Ratio Analysis
4.3.3. Algorithm Complexity Analysis
5. Experiment
5.1. Experimental Environment and Test Stimuli
5.2. Simulation Verification
5.2.1. TTP–TSN Routing Verification
5.2.2. TTP–TSN Scheduling Verification
5.2.3. Schedulability Verification
5.2.4. TTP–TSN End-to-End Delay Simulation
5.3. TestBed
5.3.1. Time Synchronization Verification
5.3.2. TTP–TSN End-to-End Delay Comparison
6. Conclusions
Author Contributions
Funding
Data Availability Statement
Conflicts of Interest
References
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Symbol | Description |
---|---|
Flow object, which contains flow attributes, including Period, Path, and length. | |
Greatest common divisor of flow periods. | |
Least common multiple of all flow periods. | |
Feasibility result. True means the current flow can be successfully assigned to Time Slots; False indicates no slots are available for the current flow. | |
Round-robin point, indicating the current location on the GCD cycle. | |
Current active time window. | |
If the current slot is not valid, the offset gives the adjustment from the starting time. | |
Switch delay. | |
P | Flow length level. |
Flow length interval. | |
Maximum duration for flow length level P. | |
Total number of frames in S with period and length level j. | |
Maximum hop count in the flow set . | |
Slot length corresponding to flow set . | |
Probability that m selected flows from flow set have no intersecting paths; this probability can be estimated using the Monte Carlo method. | |
Probability that m selected flows from flow set have no intersecting paths, but selecting flows results in at least two intersecting paths. | |
Expected number of flows in the Time Slot with non-intersecting paths. | |
Maximum duration required by the flow set . | |
Maximum duration required by the flow set . |
Experimental Case | Platform | Method Description |
---|---|---|
Planning Algorithm | Python | We compared our algorithm with two others. Firstly, ref. [19] (2022), which used BFS for routing and ILP for scheduling, referred to as ; secondly, ref. [27] (2022), which used a limited KSP algorithm for routing and ILP for scheduling, referred to as . |
Schedulability Theory | Python | Evaluation of actual scheduling results of Theorem 1, Corollary 1, and the fast algorithm through random experiments. |
Time Synchronization | FPGA | We used an oscilloscope to verify the time synchronization. |
End-to-End Delay (comprehensive experiment) | Python and FPGA | We generated 10 flows each for TTP->TSN, TSN->TTP, and TSN->TSN, with flow periods of {1 ms, 2 ms, 4 ms}, and a message length of 20 bytes to simplify the experiment. |
Parameter | Range |
---|---|
Network Scale | {Set1: [8 sw, 16 es], Set2: [16 sw, 32 es]} |
Flow Period Range | Set1: {100 µs, 200 µs, 400 µs, 500 µs} Set2: {1000 µs, 2000 µs, 4000 µs, 5000 µs} |
Packet Length Range | {100 bytes, 1500 bytes} |
ILP Solving Time | 600 s |
(a) Non-Sched TTP–TSN Communication Delay | |||
Direction | T = 100 s | T = 200 s | T = 400 s |
TTP→TSN | 49.928 s | 99.769 s | 199.817 s |
TSN→TTP | 70.005 s | 140.155 s | 280.097 s |
Direction | T = 1 ms | T = 2 ms | T = 4 ms |
TTP→TSN | 500.766 s | 1000.18 s | 1993.69 s |
TSN→TTP | 699.488 s | 1400.13 s | 2799.85 s |
(b) Sched TTP–TSN Communication Delay | |||
Direction | T = 100 s | T = 200 s | T = 400 s |
TTP→TSN | 0.0 µs | 0.0 µs | 0.0 µs |
TSN→TTP | 31.599 µs | 71.599 µs | 111.6 µs |
Direction | T = 1 ms | T = 2 ms | T = 4 ms |
TTP→TSN | 0.0 s | 0.0 s | 0.0 s |
TSN→TTP | 301.599 s | 701.599 s | 1101.6 s |
(a) Non-Sched TTP–TSN Communication Delay | |||
Direction | T = 1 ms | T = 2 ms | T = 4 ms |
TTP→TSN | 161.568 µs | 261.288 µs | 461.224 µs |
TSN→TTP | 765.416 µs | 1465.42 µs | 2865.42 µs |
(b) Sched TTP–TSN Communication Delay | |||
Direction | T = 1 ms | T = 2 ms | T = 4 ms |
TTP→TSN | 67.08 µs | 67.08 µs | 67.08 µs |
TSN→TTP | 217.92 µs | 413.520 µs | 812.62 µs |
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Peng, Y.; Jiang, T.; Tu, X.; Huang, B.; Guo, Z.; Xu, D. Research on Low-Latency TTP–TSN Cross-Domain Network Planning Problem. Electronics 2025, 14, 203. https://doi.org/10.3390/electronics14010203
Peng Y, Jiang T, Tu X, Huang B, Guo Z, Xu D. Research on Low-Latency TTP–TSN Cross-Domain Network Planning Problem. Electronics. 2025; 14(1):203. https://doi.org/10.3390/electronics14010203
Chicago/Turabian StylePeng, Yifei, Tigang Jiang, Xiaodong Tu, Bolin Huang, Zheng Guo, and Du Xu. 2025. "Research on Low-Latency TTP–TSN Cross-Domain Network Planning Problem" Electronics 14, no. 1: 203. https://doi.org/10.3390/electronics14010203
APA StylePeng, Y., Jiang, T., Tu, X., Huang, B., Guo, Z., & Xu, D. (2025). Research on Low-Latency TTP–TSN Cross-Domain Network Planning Problem. Electronics, 14(1), 203. https://doi.org/10.3390/electronics14010203