Description of membrane systems with time Petri nets: promoters/inhibitors, membrane dissolution, and priorities

Battyányi, Péter; Vaszil, György

doi:10.1007/s41965-020-00062-y

Cited by 4 publications

(1 citation statement)

References 14 publications

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“…In [22] the authors demonstrated three universal antiport P systems of bounded size and presented universal antiport P systems. The authors of [23] constructed simulating time Petri net to retain important characteristics of the Petri net model, that the firings of the transitions can take place in any order, and it is not needed to introduce maximal parallelism in the Petri net semantics, so they exploited the gain in computational strength obtained by the introduction of the timing feature for Petri nets.…”

Section: Membrane Systemsmentioning

confidence: 99%

P System–Based Clustering Methods Using NoSQL Databases

2021

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Models of computation are fundamental notions in computer science; consequently, they have been the subject of countless research papers, with numerous novel models proposed even in recent years. Amongst a multitude of different approaches, many of these methods draw inspiration from the biological processes observed in nature. P systems, or membrane systems, make an analogy between the communication in computing and the flow of information that can be perceived in living organisms. These systems serve as a basis for various concepts, ranging from the fields of computational economics and robotics to the techniques of data clustering. In this paper, such utilization of these systems—membrane system–based clustering—is taken into focus. Considering the growing number of data stored worldwide, more and more data have to be handled by clustering algorithms too. To solve this issue, bringing these methods closer to the data, their main element provides several benefits. Database systems equip their users with, for instance, well-integrated security features and more direct control over the data itself. Our goal is if the type of the database management system is given, e.g., NoSQL, but the corporation or the research team can choose which specific database management system is used, then we give a perspective, how the algorithms written like this behave in such an environment, so that, based on this, a more substantiated decision can be made, meaning which database management system should be connected to the system. For this purpose, we discover the possibilities of a clustering algorithm based on P systems when used alongside NoSQL database systems, that are designed to manage big data. Variants over two competing databases, MongoDB and Redis, are evaluated and compared to identify the advantages and limitations of using such a solution in these systems.

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Section: Membrane Systemsmentioning

confidence: 99%