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Rare Event Detection Using Error-corrected DNA and RNA Sequencing
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Threshold-Based Widespread Event Detection.

You Zhou1,2, Yian Zhou1,2, Shigang Chen1

  • 1Department of Computer & Information Science & Engineering, University of Florida, Gainesville, FL, USA.

Proceedings. International Conference on Distributed Computing Systems
|November 2, 2020
PubMed
Summary
This summary is machine-generated.

This study introduces a novel probabilistic threshold-based method for widespread event detection across networks. The solution efficiently identifies events in w-out-of-a monitors with guaranteed accuracy and low communication overhead.

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Area of Science:

  • Computer Science
  • Network Engineering
  • Data Mining

Background:

  • Widespread event detection is crucial for cybersecurity, traffic engineering, and distributed data mining.
  • Existing methods may lack efficiency or probabilistic guarantees for large-scale networks.

Purpose of the Study:

  • To introduce a new probabilistic threshold-based event detection problem.
  • To develop efficient solutions for detecting events appearing in any w-out-of-a monitors.
  • To ensure probabilistic guarantees on false positives while minimizing communication overhead.

Main Methods:

  • Development of an efficient threshold filter solution and its improved versions.
  • Combination of Bloom filters, counting Bloom filters, threshold filters, and compressed filters.
  • Theoretical optimization of system parameters to minimize communication overhead under detection constraints.

Main Results:

  • Proposed solutions effectively detect widespread events in large networks.
  • Achieved low false positive rates and reduced communication overhead.
  • Demonstrated a practical tradeoff between detection accuracy and communication costs.

Conclusions:

  • The developed threshold filter solutions are practically viable for widespread event detection.
  • The approach offers an efficient and accurate method for network monitoring applications.
  • Optimized parameters ensure effective event detection with minimal resource utilization.