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  4. Verification of network end-to-end latencies for adaptive ethernet-based cyber-physical systems
 
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2018
Journal Article
Title

Verification of network end-to-end latencies for adaptive ethernet-based cyber-physical systems

Abstract
As Cyber-Physical Systems (CPS) are evolving towards flexible and smart systems, their dependable communication becomes a decisive factor. In order to still guarantee a predictive and real-time behavior, verifying the network performance of such adaptive systems is vital. Therefore, the performance-verification has to consider the runtime variability while scaling for larger number of applications and networks in CPS. We introduce a novel performance-verification approach with integrated variability enabling the analysis of adaptive Ethernet-based CPS. It incorporates a formal model capturing all relevant characteristics for deriving safe communication bounds. Its soundness has been evaluated in an extensive automotive case study and several changing test setups targeting scalability. The results show that this integrated variability approach is superior to a common static analysis and previously utilized heuristic. In direct comparison it outperforms static analysis by up to 95 percent within the evaluated automotive system. Moreover, the results show that it scales well and provides a profound basis for analyzing larger adaptive networked systems.
Author(s)
Manderscheid, Martin
Fraunhofer-Institut für Eingebettete Systeme und Kommunikationstechnik ESK  
Weiß, Gereon  
Fraunhofer-Institut für Eingebettete Systeme und Kommunikationstechnik ESK  
Knorr, Rudi
Fraunhofer-Institut für Eingebettete Systeme und Kommunikationstechnik ESK  
Journal
Journal of systems architecture  
Open Access
File(s)
Download (714.02 KB)
DOI
10.24406/publica-r-254382
10.1016/j.sysarc.2018.05.004
Language
English
ESK  
Keyword(s)
  • Cyber-physical Systems

  • CPS

  • embedded systems

  • network performance analysis

  • network performance verification

  • real time system architecture

  • runtime variability

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