Schedulability analysis and efficient scheduling of rate constrained messages in the TTEthernet protocol

Kermia, Omar

doi:10.1002/spe.2480

Cited by 4 publications

(2 citation statements)

References 20 publications

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“…The delay caused by low priority traffic is determined by the traffic integration strategy of TT and ET traffic (primarily referring to RC traffic). The integrated transmission modes of TT and RC traffic are divided into three types: preemption, timely-block and shuffling [16], as shown in Figure 2. Preemption indicates a RC frame can be preempted and relayed after the transmission of a TT frame.…”

Section: Time-triggered Ethernetmentioning

confidence: 99%

A Performance Analysis Framework of Time-Triggered Ethernet Using Real-Time Calculus

et al. 2020

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With increasing demands of deterministic and real-time communication, network performance analysis is becoming an increasingly important research topic in safety-critical areas, such as aerospace, automotive electronics and so on. Time-triggered Ethernet (TTEthernet) is a novel hybrid network protocol based on the Ethernet standard; it is deterministic, synchronized and congestion-free. TTEthernet with a time-triggered mechanism meets the real-time and reliability requirements of safety-critical applications. Time-triggered (TT) messages perform strict periodic scheduling following the offline schedule tables. Different scheduling strategies have an effect on the performance of TTEthernet. In this paper, a performance analysis framework is designed to analyze the end-to-end delay, backlog bounds and resource utilization of network by real-time calculus. This method can be used as a base for the performance evaluation of TTEthernet scheduling. In addition, this study discusses the impacts of clock synchronization and traffic integration strategies on TT traffic in the network. Finally, a case study is presented to prove the feasibility of the performance analysis framework.

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Section: Time-triggered Ethernetmentioning

confidence: 99%

A Performance Analysis Framework of Time-Triggered Ethernet Using Real-Time Calculus

et al. 2020

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“…Cyber‐physical systems (CPSs) are integrations of network, computation, and physical processes 1 . As the infrastructure of CPS, network connects the subsystems of CPS and transmits various information.…”

Section: Introductionmentioning

confidence: 99%

Network traffic prediction method based on echo state network with adaptive reservoir

et al. 2020

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Network traffic prediction is of great significance to resource management in cyber‐physical systems (CPSs). In particular, network traffic is a nonlinear time series. Echo state network (ESN) is a new neural network with strong nonlinear processing capacity and short‐term memory capacity, and thus can achieve good performance in predicting nonlinear time series. However, network traffic has various characteristics such as self‐similarity, chaos, mutability. As the core of ESN, the reservoir will be fixed rather than adjustable once it is generated, which limits the prediction performance of ESN in different network traffic. To achieve universal excellent prediction performance, this paper proposes a new network traffic prediction method based on ESN with adaptive reservoir (ESN‐AR). First, the framework of ESN‐AR is constructed for network traffic prediction, in which the idea of generative adversarial network (GAN) is incorporated into ESN to adaptively adjust the reservoir. Specifically, ESN is used as the generative model to predict network traffic and feedforward neural network (FNN) is used as the discriminative model to distinguish between the real network traffic and the predicted network traffic. Second, the adversarial training algorithm of ESN‐AR is proposed to obtain the appropriate reservoir depending on the network traffic characteristics. Finally, ESN‐AR is applied to the prediction of three actual network traffic with different characteristics. Simulation results show that compared with the state‐of‐the‐art models, the proposed method achieves more accurate and stable prediction performance.

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A Flow-Grained End-to-End Delay Analysis for RC Traffic in TTEthernet

Guo¹,

Wan²,

Li³

et al. 2018

2018 IEEE 42nd Annual Computer Software and Applications Conference (COMPSAC)

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Schedulability analysis and efficient scheduling of rate constrained messages in the TTEthernet protocol

Cited by 4 publications

References 20 publications

A Performance Analysis Framework of Time-Triggered Ethernet Using Real-Time Calculus

A Performance Analysis Framework of Time-Triggered Ethernet Using Real-Time Calculus

Network traffic prediction method based on echo state network with adaptive reservoir

A Flow-Grained End-to-End Delay Analysis for RC Traffic in TTEthernet

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