Meckel, Simon Julius
[VerfasserIn]
;
Obermaisser, Roman
[MitwirkendeR]
Time-triggered architecture for online diagnosis in resource-constrained systems with compressed data streams ; Zeitgesteuerte Architektur für Online-Diagnose in ressourcenbeschränkten Systemen mit komprimierten Datenströmen
Titel:
Time-triggered architecture for online diagnosis in resource-constrained systems with compressed data streams ; Zeitgesteuerte Architektur für Online-Diagnose in ressourcenbeschränkten Systemen mit komprimierten Datenströmen
Beteiligte:
Meckel, Simon Julius
[VerfasserIn]
Erschienen:
Universität Siegen; Department Elektrotechnik - Informatik, 2021-01-01
Anmerkungen:
Diese Datenquelle enthält auch Bestandsnachweise, die nicht zu einem Volltext führen.
Beschreibung:
Coping with limited communication resources in distributed real-time systems is a major challenge nowadays. With regard to high-dependable and safety-critical systems (e.g., flight control systems and advanced driver assistance systems) the use of a time-triggered architecture is advantageous, since the periodic task executions and message exchanges according to a static schedule maximize the predictability compared to event-triggered systems. These systems efficiently realize fault tolerance by means of online and active fault diagnosis that enables redundancy-based fault-specific recovery or degradation strategies, e.g., system reconfigurations. In this way, they are able to overcome a failure or malfunction of some of their constituent components and continue to operate. As many systems are becoming more and more complex, there is an ever-growing amount of network traffic for monitoring and diagnostic purposes. In many cases, this causes the communication network to become the limiting resource, which can negatively impact the lengths of schedules, i.e., lead to longer overall service times, and reduce the maximum level of integration of different services in one system. The use of data compression can help to reduce network traffic. However, due to the specific requirements and constraints of both time-triggered systems and diagnostic applications, some of which are contradictory, classical data compression algorithms cannot be straightforwardly applied. The difficulty lies in reconciling the needs for guaranteed data quality as well as temporal guarantees regarding information delivery. Lossless data compression does not support a certain worst-case compression ratio on short input sequences, but produces variable-length outputs. Therefore, it is difficult to guarantee the amount of information that will be encoded into a time-triggered message or, in turn, to guarantee the number of messages needed to transmit a certain amount of information. In lossy data compression, fixed-length outputs can be produced, ...