Frugal Streaming for Estimating Quantiles

  title={Frugal Streaming for Estimating Quantiles},
  author={Q. Ma and S. Muthukrishnan and Mark Sandler},
  booktitle={Space-Efficient Data Structures, Streams, and Algorithms},
  • Q. Ma, S. Muthukrishnan, Mark Sandler
  • Published in
    Space-Efficient Data…
  • Computer Science
  • Modern applications require processing streams of data for estimating statistical quantities such as quantiles with small amount of memory. In many such applications, in fact, one needs to compute such statistical quantities for each of a large number of groups (e.g.,network traffic grouped by source IP address), which additionally restricts the amount of memory available for the stream for any particular group. We address this challenge and introduce frugal streaming, that is algorithms that… CONTINUE READING
    22 Citations
    Tracking of multiple quantiles in dynamically varying data streams
    • 2
    • PDF
    Estimation of Multiple Quantiles in Dynamically Varying Data Streams
    • 2
    • PDF
    A Higher-Fidelity Frugal Quantile Estimator
    • 1
    Online anomaly detection over Big Data streams
    • 39
    • PDF
    Joint Tracking of Multiple Quantiles Through Conditional Quantiles
    • 1
    • PDF
    Optimal Quantile Approximation in Streams
    • 33
    • PDF
    1 Heavy Hitters 11.1 Streaming
      • PDF


      Continuously maintaining quantile summaries of the most recent N elements over a data stream
      • 90
      • PDF
      A One-Pass Space-Efficient Algorithm for Finding Quantiles
      • 52
      • PDF
      Space-efficient online computation of quantile summaries
      • 496
      • PDF
      An improved data stream summary: the count-min sketch and its applications
      • 1,578
      • PDF
      Stream Order and Order Statistics: Quantile Estimation in Random-Order Streams
      • 74
      • PDF