Abstract
This paper presents the real implementation of a fog computing environment for the execution of color tracking applications by using FogBus2 framework and an artificial intelligence based docker container scheduling. To be precise, an edge computing network has been developed by using a personal computer and several small computing devices such as Raspberry Pi and Nvidia Jetson Nano. Related to the scheduling policy, besides the existing policies in Fogbus2 framework, another one based on fuzzy rules-based system has been designed. Results demonstrate the proposed policy outperforms classical approaches, even when using, pavin the way to the use of knowledge acquisition techniques in order to improve the scheduling performance in terms of makespan and flowtime.
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Chrobak, R., Galán, S.G., Expósito, E.M., Ibanez, M.V., Marciniak, T., Marchewka, A. (2023). Color Tracking Application Using AI-Based Docker Container Scheduling in Fog Computing. In: Burduk, R., Choraś, M., Kozik, R., Ksieniewicz, P., Marciniak, T., Trajdos, P. (eds) Progress on Pattern Classification, Image Processing and Communications. CORES IP&C 2023 2023. Lecture Notes in Networks and Systems, vol 766. Springer, Cham. https://doi.org/10.1007/978-3-031-41630-9_17
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