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Using grid computing based components in on demand environmental data delivery., , и . UPGRADE-CN, стр. 81-86. ACM, (2007)Using GPGPU Accelerated Interpolation Algorithms for Marine Bathymetry Processing with On-Premises and Cloud Based Computational Resources., , , , , , , , , и . PPAM (2), том 10778 из Lecture Notes in Computer Science, стр. 14-24. Springer, (2017)Development of a GT4-Based Resource Broker Service: An Application to On-demand Weather and Marine Forecasting.. GPC, том 4459 из Lecture Notes in Computer Science, стр. 204-217. Springer, (2007)Performance, Resilience, and Security in Moving Data from the Fog to the Cloud: The DYNAMO Transfer Framework Approach., , , , и . IDCS, том 11226 из Lecture Notes in Computer Science, стр. 197-208. Springer, (2018)Internet of Things orchestration using DagOn* workflow engine., , , и . WF-IoT, стр. 95-100. IEEE, (2019)Virtualizing high-end GPGPUs on ARM clusters for the next generation of high performance cloud computing., , и . Clust. Comput., 17 (1): 139-152 (2014)Heterogeneous Secure Multi-level Remote Acceleration Service for Low-power Integrated Systems and Devices., , , , , , , и . Cloud Forward, том 97 из Procedia Computer Science, стр. 118-121. Elsevier, (2016)Towards a GPU parallel software for environmental data fitting., , , , , и . PETRA, стр. 469-472. ACM, (2022)WaComM: A Parallel Water Quality Community Model for Pollutant Transport and Dispersion Operational Predictions., , , , , и . SITIS, стр. 717-724. IEEE Computer Society, (2016)A fast, secure, reliable, and resilient data transfer framework for pervasive IoT applications., , и . INFOCOM Workshops, стр. 710-715. IEEE, (2018)