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Avoiding down times - monitoring, diagnostics and troubleshooting of industrial wireless systems

Paper presented at Wireless Congress: Systems & Applications; 15.-16. November 2017, Munich, Germany
 
: Frotzscher, Andreas; Wetzker, Ulf

:
Volltext urn:nbn:de:0011-n-4710487 (165 KByte PDF)
MD5 Fingerprint: 1710a0799fa427b27c44bda6e4e88f8a
Erstellt am: 8.11.2017


2017, 4 S.
Wireless Congress "Systems & Applications" <2017, Munich>
Bundesministerium für Bildung und Forschung BMBF
03ZZ0510A; fast automation
Echtzeitfähiges, drahtloses Kommunikationssystem in lizenzfreien Funkfrequenzbändern für Anwendungen in der Industrieautomation
Englisch
Konferenzbeitrag, Elektronische Publikation
Fraunhofer IIS, Institutsteil Entwurfsautomatisierung (EAS) ()

Abstract
The ever-growing proliferation of wireless devices and technologies used for Internet of Things (IoT) applications, such as patient monitoring, military surveillance, and industrial automation and control, has created an increasing need for methods and tools for connectivity prediction, information flow monitoring, and failure analysis to increase the dependability of the wireless network. Indeed, in a safety-critical Industrial IoT (IIoT) setting, such as a smart factory, harsh signal propagation conditions combined with interference from coexisting radio technologies operating in the same frequency band may lead to poor network performance or even application failures despite precautionary measures. Analyzing and troubleshooting such failures on a large scale is often difficult and time-consuming. In this paper, we share our experience in troubleshooting coexistence problems in operational IIoT networks, pointing out the need for a userfriendly, automated failure analysis system. Furthermore we present a new solution addressing this demand, developed for mobile and the permanent monitoring and troubleshooting scenarios.

: http://publica.fraunhofer.de/dokumente/N-471048.html