Abstract
This work will focus on the problems of creating a safe distributed laboratory. We explicitly will not discuss how to make individual elements of an experiment safe, as this is highly application-dependent. Instead, the goal is to find and evaluate different methods to detect and respond to fault conditions that an individual laboratory device might detect. Specifically, the methods should differentiate between user-based faults and those introduced through network communications. We develop a mathematical model to simulate distributed laboratories. We will introduce (time-dependent) network latency and jitter between all elements. Based on the model, a discrete event simulation is created. This simulation environment simulates three different fault detecting methods: the token method, the timestamp method, and the full-state-transfer method. We will compare detection ratios, bandwidth usage, and memory usage between the three methods based on the simulation.
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Notes
- 1.
It is noteworthy that even at this stage, we can see a considerable difference between the methods resource usage. The parameters were chosen because of the full-state-transfer method. The Timestamp method could handle simulations with at least 20 variables in the same runtime, and the token method could easily handle well over 40 variables.
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Acknowledgements
This work is funded by the Stiftung Innovation in der Hochschullehre, Treuhandstiftung in Trägerschaft der Toepfer Stiftung gGmbH in the project CrossLab [4] (project number FBM2020-VA-182-3-00590).
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Nau, J., Helbing, P., Henke, K., Streitferdt, D. (2023). Latency Resistant Safety in Distributed Remote Laboratories. In: Auer, M.E., El-Seoud, S.A., Karam, O.H. (eds) Artificial Intelligence and Online Engineering. REV 2022. Lecture Notes in Networks and Systems, vol 524. Springer, Cham. https://doi.org/10.1007/978-3-031-17091-1_12
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