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PRACTISE - Demonstrating a Neural Network Based Framework for Robust Prediction of Data Center Workload.

, , , , , and . UCC, page 402-403. IEEE Computer Society, (2015)

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A delay-based aggregate rate control for P2P streaming systems., , , , , and . Computer Communications, 35 (18): 2237-2244 (2012)Delay-Based Cloud Congestion Control., , and . GLOBECOM, page 1-8. IEEE, (2009)Data Centers in the Cloud: A Large Scale Performance Study., , and . IEEE CLOUD, page 336-343. IEEE, (2012)(Big)data in a virtualized world: volume, velocity, and variety in cloud datacenters., , , , and . FAST, page 177-189. USENIX, (2014)A simulation framework for priority scheduling on heterogeneous clusters., , , and . Future Generation Comp. Syst., (2015)Cutting Latency Tail: Analyzing and Validating Replication without Canceling., , , , and . IEEE Trans. Parallel Distrib. Syst., 28 (11): 3128-3141 (2017)Managing Data Center Tickets: Prediction and Active Sizing., , , and . DSN, page 335-346. IEEE Computer Society, (2016)Exploring Deep Reinforcement Learning for Autonomous Powerline Tracking., , and . INFOCOM Workshops, page 496-501. IEEE, (2019)How elastic is your virtualized datacenter fabric?, , , and . INA-OCMC@HiPEAC, page 17-20. ACM, (2013)Defeating variability in cloud applications by multi-tier workload redundancy., , , and . INFOCOM Workshops, page 496-497. IEEE, (2016)