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Related Experiment Video

Updated: Apr 11, 2026

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit
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Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit

Published on: September 8, 2023

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Efficient hash tables for network applications.

Thomas Zink1, Marcel Waldvogel1

  • 1Distributed Systems Laboratory, University of Konstanz, Konstanz, Germany.

Springerplus
|May 29, 2015
PubMed
Summary
This summary is machine-generated.

This study introduces a novel hashing approach for real-time systems, reducing memory needs and ensuring constant lookup times. It makes efficient hash table implementations more practical and predictable.

Related Experiment Videos

Last Updated: Apr 11, 2026

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit
05:30

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit

Published on: September 8, 2023

1.2K

Area of Science:

  • Computer Science
  • Algorithm Design
  • Hardware Acceleration

Background:

  • Hashing is not widely adopted in hard real-time systems due to unpredictable performance from collisions.
  • Perfect hashing is theoretically optimal but computationally expensive for high-speed applications.
  • Existing methods like d-left hashing require significant high-speed SRAM for predictable DRAM access.

Purpose of the Study:

  • To address the limitations of current hashing techniques in real-time systems.
  • To propose a more practical and predictable hashing solution for hardware and high-speed lookups.
  • To reduce the reliance on expensive on-chip memory while maintaining performance.

Main Methods:

  • Exploiting four specific degrees of freedom in practical applications.
  • Developing a hashing approach tailored for hardware and high-speed lookup scenarios.
  • Designing a system that guarantees constant lookup and update times.

Main Results:

  • Reduced on-chip memory requirements by up to an order of magnitude.
  • Guaranteed constant lookup and update times.
  • Achieved these improvements with only minor additional hardware.

Conclusions:

  • The proposed hashing method overcomes the limitations of previous general-purpose approaches.
  • This design makes efficient hash table implementations cheaper, more predictable, and more practical for real-time systems.
  • It offers a viable solution for applications requiring deterministic memory access without excessive hardware costs.