Abstract
Reliability is one of the major concerns of Time Sensitive Networking (TSN). Current systems mostly rely on static redundancy to protect functionality from permanent component failures. This greatly increases the cost of Time-Triggered (TT) flows. Instead, Software Defined Networking (SDN) enables dynamic redundancy. Disrupted traffic can be rerouted by a centralized controller to reduce the cost while maintaining reliability. This paper presents an approach to compute alternative paths at run-time and analyze their impact on reliability. We define a novel three-mode recovery scheme, which includes full functionality, reduced functionality, and emergency halt modes. Run-time recovery for TT flows is explored using Integer Linear Programming (ILP) and a heuristic algorithm. Then, a Markov chain-based design-time reliability analysis is developed to evaluate the Mean Time to Reduced Functionality Mode (MTTRF) and Mean Time to Failure (MTTF) of run-time recoverable systems. Our experiments show that run-time recovery provides better protection against multi-point failures than static redundancy. Compared with the state of the art, our proposed ILP has better routing efficiency. The proposed heuristic algorithm can perform routing and scheduling in polynomial time, but it tends to route multicast flows to longer paths than ILP. Furthermore, when applied to realistic recovery scenarios, our proposed ILP improves the MTTF by up to 2× and the average execution time by up to 20× than the raw ILP of the state of the art. Although less efficient with multicast flows, the heuristic algorithm achieves similar reliability as the ILP, and its worst-case recovery time is below 100ms on an embedded ARM processor.
Highlights
The communication bandwidth demand of the emerging autonomous driving technology has encouraged innovations in next-generation vehicle networks
Using additional 120 more realistic test cases, our experiment shows that the proposed recovery approaches can result up to twice the mean time to failure than the state of the art; the proposed Integer Linear Programming (ILP) by its average can setup flows within a second; and the heuristic algorithm meets the 100ms worst-case execution time requirement
To demonstrate that the proposed approaches are feasible in realistic network configurations, we perform a case study of an automotive Time Sensitive Networking (TSN) to show that the execution time of the proposed heuristic algorithm is well below the recovery deadline. (§7)
Summary
The communication bandwidth demand of the emerging autonomous driving technology has encouraged innovations in next-generation vehicle networks. While switched Ethernet is considered as a promising solution, it is not originally designed for real-time safety-critical systems and requires enhancements for bounded latency and reliability This results in a set of amendments of the Ethernet standard named Time Sensitive Networking (TSN) [1]. Using additional 120 more realistic test cases, our experiment shows that the proposed recovery approaches can result up to twice the mean time to failure than the state of the art; the proposed ILP by its average can setup flows within a second; and the heuristic algorithm meets the 100ms worst-case execution time requirement. To demonstrate that the proposed approaches are feasible in realistic network configurations, we perform a case study of an automotive TSN to show that the execution time of the proposed heuristic algorithm is well below the recovery deadline. To demonstrate that the proposed approaches are feasible in realistic network configurations, we perform a case study of an automotive TSN to show that the execution time of the proposed heuristic algorithm is well below the recovery deadline. (§7)
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