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Measuring Baseline Overheads in Different Orchestration Mechanisms for Large FaaS Workflows.

, , , and . ICPE (Companion), page 61-68. ACM, (2022)

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Comparing Methods for Twitter Sentiment Analysis, , , and . Proceedings of the 6th International Conference on Knowledge Discovery and Information Retrieval - KDIR 2014, (2014)Employing traditional machine learning algorithms for big data streams analysis: the case of object trajectory prediction., , , , and . CoRR, (2016)CONSENSUS Project: Identifying Publicly Acceptable Policy Implementations.. EEPM@eGOV, volume 1553 of CEUR Workshop Proceedings, CEUR-WS.org, (2015)Real-time reconfiguration for guaranteeing QoS provisioning levels in Grid environments., , and . Future Gener. Comput. Syst., 25 (7): 779-784 (2009)Large-scale evaluation framework for local influence theories in Twitter., , , , and . Inf. Process. Manag., 51 (1): 226-252 (2015)Strand: scalable trilateration with Node.js., , and . J. Cloud Comput., (2019)Computationally Efficient Rehearsal for Online Continual Learning., , , , and . ICIAP (3), volume 13233 of Lecture Notes in Computer Science, page 39-49. Springer, (2022)AI-as-a-Service Toolkit for Human-Centered Intelligence in Autonomous Driving., , , , , , , , , and 4 other author(s). PerCom Workshops, page 91-93. IEEE, (2022)Measuring Baseline Overheads in Different Orchestration Mechanisms for Large FaaS Workflows., , , and . ICPE (Companion), page 61-68. ACM, (2022)Intelligent Multi-Domain Edge Orchestration for Highly Distributed Immersive Services: An Immersive Virtual Touring Use Case., , , , , , , , and . EDGE, page 381-392. IEEE, (2023)