Abstract
In this article we use a Genetic Algorithm to perform parameter tuning on Google Guava’s Cache library, specialising it to OpenTripPlanner. A new tool, Opacitor, is used to deterministically measure the energy consumed, and we find that the energy consumption of OpenTripPlanner may be significantly reduced by tuning the default parameters of Guava’s Cache library. Finally we use Jalen, which uses time and CPU utilisation as a proxy to calculate energy consumption, to corroborate these results.
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Notes
- 1.
Available at https://github.com/google/guava.
- 2.
Available at http://www.opentripplanner.org.
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Acknowledgement
Work funded by UK EPSRC grant EP/J017515/1. Data available at https://github.com/nburles/burles2015specialising.
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Burles, N., Bowles, E., Bruce, B.R., Srivisut, K. (2015). Specialising Guava’s Cache to Reduce Energy Consumption . In: Barros, M., Labiche, Y. (eds) Search-Based Software Engineering. SSBSE 2015. Lecture Notes in Computer Science(), vol 9275. Springer, Cham. https://doi.org/10.1007/978-3-319-22183-0_23
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DOI: https://doi.org/10.1007/978-3-319-22183-0_23
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