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Resource aware placement of IoT application modules in Fog-Cloud Computing Paradigm.

, and . IM, page 1222-1228. IEEE, (2017)

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Distributed Decomposed Data Analytics in Fog Enabled IoT Deployments., , and . IEEE Access, (2019)Machine learning based fog computing assisted data-driven approach for early lameness detection in dairy cattle., , , , , and . Comput. Electron. Agric., (2020)A Deep Neural Network-Based Multi-Label Classifier for SLA Violation Prediction in a Latency Sensitive NFV Application., , and . IEEE Open J. Commun. Soc., (2021)Methodical Analysis of a Fog Computing Assisted Animal-Welfare Software System in a Real-World Smart Dairy Farm IoT Deployment., , , and . WF-IoT, page 857-864. IEEE, (2021)Lameness Detection as a Service: Application of Machine Learning to an Internet of Cattle., , , and . CCNC, page 1-6. IEEE, (2019)Connected Cows: Utilizing Fog and Cloud Analytics toward Data-Driven Decisions for Smart Dairy Farming., , , , , and . IEEE Internet Things Mag., 2 (4): 32-37 (2019)SmartHerd management: A microservices-based fog computing-assisted IoT platform towards data-driven smart dairy farming., , , , and . Softw. Pract. Exp., 49 (7): 1055-1078 (2019)Resource aware placement of IoT application modules in Fog-Cloud Computing Paradigm., and . IM, page 1222-1228. IEEE, (2017)A Graph Neural Networks based Framework for Topology-Aware Proactive SLA Management in a Latency Critical NFV Application Use-case., , and . CoRR, (2022)DARAC: DDoS Mitigation Using DDoS Aware Resource Allocation in Cloud., , , , , and . ICISS, volume 9478 of Lecture Notes in Computer Science, page 263-282. Springer, (2015)