Anomaly Detection-Based Resource Autoscaling Mechanism for Fog Computing
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Publisher
Springer Nature Singapore
Link
https://link.springer.com/content/pdf/10.1007/978-981-97-2614-1_9
Reference10 articles.
1. Chang Z, Liu L, Guo X, Sheng Q (2020) Dynamic resource allocation and computation offloading for IoT fog computing system. IEEE Trans Industr Inf 17(5):3348–3357
2. Erhan L, Ndubuaku M, Di Mauro M, Song W, Chen M, Fortino G, Bagdasar O, Liotta A (2021) Smart anomaly detection in sensor systems: a multi-perspective review. Inf Fusion 67:64–79
3. Sheela S, Chouhan D, Kumar SD (2022) Computational framework for node placement and bandwidth optimization in dynamic fog computing environments. In: 2022 IEEE 19th India council international conference (INDICON). IEEE, pp 1–6
4. Tseng FH, Tsai MS, Tseng CW, Yang YT, Liu CC, Chou LD (2018) A lightweight autoscaling mechanism for fog computing in industrial applications. IEEE Trans Industr Inf 14(10):4529–4537
5. Sami H, Mourad A, Otrok H, Bentahar J (2020) FScaler: automatic resource scaling of containers in fog clusters using reinforcement learning. In: 2020 international wireless communications and mobile computing (IWCMC). IEEE, pp 1824–1829
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