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Project: Discovery and maintenance of heavy hitters over sliding windows, in a distributed environment.


Synopses are extensively used for summarizing high-frequency streaming data, e.g., input from sensors, network packets, financial transactions. Some examples include Count-Min sketches, Bloom filters, AMS sketches, samples, and histogram. This project will focus on designing, developing, and evaluating synopses for the discovery of heavy hitters over sliding windows, in a distributed environment, and over high-frequency streams.

This project may include collaboration with international partners.

Prerequisites: ability to write efficient code in *Java or Scala*, comfortable with mathematical proofs, ability to read and understand scientific literature (conference papers and journal articles), successful completion of 2AMD15 with a high grade.

Reading material:

Introduction to synopses:
Space saving algorithm and extensions:
Memento algorithm
ECM sketches

Odysseas Papapetrou
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