Distributed Mega-Datasets: The Need for Novel Computing Primitives

@article{Semmler2019DistributedMT,
  title={Distributed Mega-Datasets: The Need for Novel Computing Primitives},
  author={Niklas Semmler and Georgios Smaragdakis and A. Feldmann},
  journal={2019 IEEE 39th International Conference on Distributed Computing Systems (ICDCS)},
  year={2019},
  pages={1684-1692}
}
  • Niklas Semmler, Georgios Smaragdakis, A. Feldmann
  • Published 2019
  • Computer Science
  • 2019 IEEE 39th International Conference on Distributed Computing Systems (ICDCS)
  • With the ongoing digitalization, an increasing number of sensors is becoming part of our digital infrastructure. These sensors produce highly, even globally, distributed data streams. The aggregate data rate of these streams far exceeds local storage and computing capabilities. Yet, for radical new services (e.g., predictive maintenance and autonomous driving), which depend on various control loops, this data needs to be analyzed in a timely fashion. In this position paper, we outline a system… CONTINUE READING
    2 Citations
    Online Replication Strategies for Distributed Data Stores
    • 2
    • PDF
    Edge replication strategies for wide-area distributed processing
    • PDF

    References

    SHOWING 1-10 OF 25 REFERENCES
    Spark: Cluster Computing with Working Sets
    • 4,369
    • PDF
    Flowtree: Enabling Distributed Flow Summarization at Scale
    • 1
    • PDF
    Supporting fine-grained data lineage in a database visualization environment
    • 238
    • PDF
    Apache Flink™: Stream and Batch Processing in a Single Engine
    • 846
    • PDF
    Lineage tracing for general data warehouse transformations
    • 391
    • PDF
    SmartFactory - Towards a factory-of-things
    • D. Zühlke
    • Engineering, Computer Science
    • Annu. Rev. Control.
    • 2010
    • 463
    • PDF
    The constrained Ski-Rental problem and its application to online cloud cost optimization
    • 42
    • PDF
    Competitive snoopy caching
    • 311
    Empirical studies of competitve spinning for a shared-memory multiprocessor
    • 163
    Fog Computing: A Platform for Internet of Things and Analytics
    • 832
    • PDF