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Publication Detail
Optimising Quantisation Noise in Energy Measurement
  • Publication Type:
    Conference
  • Authors:
    Langdon WB, Petke J, Bruce BR
  • Publication date:
    27/01/2016
  • Place of publication:
    Computer Science, University College, London
  • Addresses:
    Gower Street, London
  • Notes:
    keywords: theory, genetic improvement, software engineering, SBSE, artificial intelligence, distributed power monitoring, local area network, Ethernet, jitter size: 13 pages
Abstract
A simple model of distributed Genetic Improvement running in parallel across a local area network in which start/stop commands are sent to measuring devices calculates a minimum usable software mutation effect based on the analogue to digital convert (ADC)’s resolution. With modern low cost power monitors, the high speed Ethernet LAN’s jitter and delays appear to have little effect. Where the software to be improved permits it, optimal test duration is inversely proportionate to minimum mutation effect size, typically well under a second.
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Dept of Computer Science
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Dept of Computer Science
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