Failure Resiliency With Only a Few Tunnels – Enabling Segment Routing for Traffic Engineering

Schüller, Timmy; Aschenbruck, Nils; Chimani, Markus; Horneffer, Martin

doi:10.1109/tnet.2020.3030543

Cited by 17 publications

(11 citation statements)

References 20 publications

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“…The most professional practice, must first read the data stream, read the data stream, found that the car intake pressure sensor than other engines of the same model to a larger point, in addition to no other phenomenon. However, the intake pressure is associated with the exhaust system, according to which it is believed that the exhaust system is not smooth, and the successful handling of this fault [13][14].…”

Section: Methods Of Df Analysis In the Diagnosis Of Faults In The Ele...mentioning

confidence: 99%

Data flow analysis in automotive engine underpower fault detection

liu

Ming

2023

Third International Conference on Artificial Intelligence and Computer Engineering (ICAICE 2022)

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Due to the relative maturity of data flow(DF) analysis and research technology as well as the increasing number and development of diagnostic instruments, the automotive engine fault detection and diagnosis system is developing in the direction of precision, intelligence and multi-module diagnosis. In this paper, the fault detection system is designed for the problem of insufficient power of automobile engine. The ECU of automobile engine has the function of collecting the engine DF under various conditions in real time, and then reading out the relevant data during the driving process with the automobile fault diagnostic instrument, and the maintenance personnel combine them according to different requirements to form different data sets. The fault detection system also has the function of fault identification and prediction, and the best result of PSO-ELM algorithm is found by comparing the prediction accuracy of different algorithms. Here, it is hoped that the research in this paper will provide a reliable basis for analyzing and researching automotive engine faults.

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Section: Methods Of Df Analysis In the Diagnosis Of Faults In The Ele...mentioning

confidence: 99%

Data flow analysis in automotive engine underpower fault detection

liu

Ming

2023

Third International Conference on Artificial Intelligence and Computer Engineering (ICAICE 2022)

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“…Moreover, the researchers of Ref. [33] presented an effective failure resiliency framework and controlled the number of tunnels for TE in SR. These articles reflect the potential to improve network performance for TE in SR.…”

Section: Segment Routingmentioning

confidence: 99%

Intelligent Segment Routing: Toward Load Balancing with Limited Control Overheads

Yang

Chen

Cui

et al. 2023

Big Data Min. Anal.

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Segment routing has been a novel architecture for traffic engineering in recent years. However, segment routing brings control overheads, i.e., additional packets headers should be inserted. The overheads can greatly reduce the forwarding efficiency for a large network, when segment headers become too long. To achieve the best of two targets, we propose the intelligent routing scheme for traffic engineering (IRTE), which can achieve load balancing with limited control overheads. To achieve optimal performance, we first formulate the problem as a mapping problem that maps different flows to key diversion points. Second, we prove the problem is nondeterministic polynomial (NP)-hard by reducing it to a k-dense subgraph problem. To solve this problem, we develop an ant colony optimization algorithm as improved ant colony optimization (IACO), which is widely used in network optimization problems. We also design the load balancing algorithm with diversion routing (LBA-DR), and analyze its theoretical performance. Finally, we evaluate the IRTE in different real-world topologies, and the results show that the IRTE outperforms traditional algorithms, e.g., the maximum bandwidth is 24.6% lower than that of traditional algorithms when evaluating on BellCanada topology.

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“…They provide examples where ECMP can decrease the quality of SR by creating congestion when combined with SR. In [17], Schüller et al propose an exact failure resilient MILP model that minimizes MLU based on the model from [2], but this model has very high computational costs. The only study combining jointly the optimization of segment paths and SPR weights is the work of Parham et al [15].…”

Section: Literature Reviewmentioning

confidence: 99%

Preprocessing for segment routing optimization

2023

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In this article we introduce a preprocessing technique to solve the Segment Routing Traffic Engineering Problem optimally using significantly fewer computational resources than previously introduced methods. Segment routing is a recently developed interior gateway routing protocol to be used on top of existing protocols that introduces more flexibility in traffic engineering. In practice, segment routing allows to deviate traffic from its original path by specifying a list of intermediate nodes or links, called segments, to visit before going to its destination. The issue we tackle in this article is that the number of segment paths scales exponentially with the maximum number of segments allowed leading to scalability issues in mathematical formulations. This article introduces the notion of dominated segment paths, these are paths that can be eliminated from the solution space when searching for an optimal solution. We propose a dynamic programming algorithm eliminating dominated paths for any number of segments. Numerical results show that respectively 50%, 90%, and 97% of paths are dominated when considering up to 2, 3, and 4 segments on benchmark network topologies.

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Failure Resiliency With Only a Few Tunnels – Enabling Segment Routing for Traffic Engineering

Cited by 17 publications

References 20 publications

Data flow analysis in automotive engine underpower fault detection

Data flow analysis in automotive engine underpower fault detection

Intelligent Segment Routing: Toward Load Balancing with Limited Control Overheads

Preprocessing for segment routing optimization

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