Implementation of P Systems by Using Big Data Technologies

  • Alex Ciobanu
  • Florentin Ipate
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8340)


Due to their inherent parallel and non-deterministic nature, P system implementations require vast computing and storage resources. This significantly limits their applications, even more so when the calculation of all possible evolutions of the P system is required. This article exposes the scalability possibilities available with the Big Data ecosystem for P systems implementations, using Map Reduce parallelism to build the P system computation tree. The Hadoop based implementation is then used for generating test suites for cell like P systems, in particular for context-dependent rule coverage testing. Our preliminary evaluations on a benchmark of automatically generated P systems confirm that the proposed approach scales well.


P systems testing Hadoop P system computation tree Map Reduce Big Data NoSQL 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2014

Authors and Affiliations

  • Alex Ciobanu
    • 1
  • Florentin Ipate
    • 2
    • 1
  1. 1.Department of Computer Science, Faculty of Mathematics and Computer ScienceUniversity of PitestiPitestiRomania
  2. 2.Department of Computer Science, Faculty of Mathematics and Computer ScienceUniversity of BucharestBucharestRomania

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