Abstract
The use of volatile decentralized computational platforms such as, e.g., peer-to-peer networks, is becoming an increasingly popular option to gain access to vast computing resources. Making an effective use of these resources requires algorithms adapted to such a changing environment, being resilient to resource volatility. We consider the use of a variant of evolutionary algorithms endowed with a classical fault-tolerance technique, namely the creation of checkpoints in a safe external storage. We analyze the sensitivity of this approach on different kind of networks (scale-free and small-world) and under different volatility scenarios. We observe that while this strategy is robust under low volatility conditions, in cases of severe volatility performance degrades sharply unless a high checkpoint frequency is used. This suggest that other fault-tolerance strategies are required in these situations.
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Acknowledgements
This work is partially supported by the MINECO project EphemeCH (TIN2014-56494-C4-1-P), by the Junta de Andalucía project DNEMESIS (P10-TIC-6083) and by the Universidad de Málaga, Campus de Excelencia Internacional Andalucía Tech.
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Nogueras, R., Cotta, C. (2015). Sensitivity Analysis of Checkpointing Strategies for Multimemetic Algorithms on Unstable Complex Networks. In: Lirkov, I., Margenov, S., Waśniewski, J. (eds) Large-Scale Scientific Computing. LSSC 2015. Lecture Notes in Computer Science(), vol 9374. Springer, Cham. https://doi.org/10.1007/978-3-319-26520-9_26
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DOI: https://doi.org/10.1007/978-3-319-26520-9_26
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