Abstract
Situation Awareness in edge computing devices is necessary for detecting issues that may hinder their computation capacity and reliability. The Situation Detection Mechanism presented in this paper uses Complex Event Processing in order to detect situations where the edge infrastructure requires an adaptation. We designed the Situation Detection Mechanism so as it is modular and can be easily deployed as a Docker container or a set of Docker containers. Moreover, we designed it to be independent of Complex Event Processing libraries and we have shown that it can operate with both the Siddhi and Drools libraries. We evaluated our work with a real-world scenario indicative of the usage of our component, and its capabilities.
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Acknowledgments
This work is partly funded by the H2020 PrestoCloud project–Proactive Cloud Resources Management at the Edge for Efficient Real-Time Big Data Processing (732339).
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Papageorgiou, N., Apostolou, D., Verginadis, Y., Tsagkaropoulos, A., Mentzas, G. (2019). Situation Detection on the Edge. In: Barolli, L., Takizawa, M., Xhafa, F., Enokido, T. (eds) Web, Artificial Intelligence and Network Applications. WAINA 2019. Advances in Intelligent Systems and Computing, vol 927. Springer, Cham. https://doi.org/10.1007/978-3-030-15035-8_97
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DOI: https://doi.org/10.1007/978-3-030-15035-8_97
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