Virtual Membrane Systems

Within the membrane computing research field, there are many papers about software simulations and a few about hardware implementations. In both cases, algorithms for implementing membrane systems in software and hardware that try to take advantages of massive parallelism are implemented. P-systems are parallel and non deterministic systems which simulate membranes behavior when processing information. This paper presents software techniques based on the proper utilization of virtual memory of a computer. There is a study of how much virtual memory is necessary to host a membrane model. This method improves performance in terms of time.

Membrane Systems Working with the PFactor: Best Strategy to Solve Complex Problems.

A membrane system is a massive parallel system, which is inspired by the living cells when processing information. As a part of unconventional computing, membrane systems are proven to be effective in solving complex problems. A new factor is introduced. This factor can decide whether a technique is worthwhile being used or not. The use of this factor provides the best chances for selecting the strategy for the rules application phase. Referring to the “best” is in reference to the one that reduces execution time within the membrane system. A pre-analysis of the membrane system determines the P-factor, which in return advises the optimal strategy to use. In particular, this paper compares the use of two strategies based on the P-factor and provides results upon the application of them. The paper concludes that the P-factor is an effective indicator for choosing the right strategy to implement the rules application phase in membrane systems.

MEIA SYSTEMS: Membrane Encrypted Information Applications Systems

Membrane computing is a recent area that belongs to natural computing. This field works on computational models based on nature's behavior to process the information. Recently, numerous models have been developed and implemented with this purpose. P-systems are the structures which have been defined,developed and implemented to simulate the behavior and the evolution of membrane systems which we find in nature. What we show in this paper is a new model that deals with encrypted information which provides security the membrane systems communication. Moreover we find non deterministic and random applications in nature that are suitable to MEIA systems. The inherent parallelism and non determinism make this applications perfect object to implement MEIA systems.

Distributed models in P-Systems architectures to reduce computation time

Membrane systems are computational equivalent to Turing machines. However, their distributed and massively parallel nature obtains polynomial solutions opposite to traditional non-polynomial ones. At this point, it is very important to develop dedicated hardware and software implementations exploiting those two membrane systems features. Dealing with distributed implementations of P systems, the bottleneck communication problem has arisen. When the number of membranes grows up, the network gets congested. The purpose of distributed architectures is to reach a compromise between the massively parallel character of the system and the needed evolution step time to transit from one configuration of the system to the next one, solving the bottleneck communication problem. The goal of this paper is twofold. Firstly, to survey in a systematic and uniform way the main results regarding the way membranes can be placed on processors in order to get a software/hardware simulation of P-Systems in a distributed environment. Secondly, we improve some results about the membrane dissolution problem, prove that it is connected, and discuss the possibility of simulating this property in the distributed model. All this yields an improvement in the system parallelism implementation since it gets an increment of the parallelism of the external communication among processors. Proposed ideas improve previous architectures to tackle the communication bottleneck problem, such as reduction of the total time of an evolution step, increase of the number of membranes that could run on a processor and reduction of the number of processors.

Solving complex problems with a bioinspired model

Membrane systems are parallel and bioinspired systems which simulate membranes behavior when processing information. As a part of unconventional computing, P-systems are proven to be effective in solvingcomplexproblems. A software technique is presented here that obtain good results when dealing with such problems. The rules application phase is studied and updated accordingly to obtain the desired results. Certain rules are candidate to be eliminated which can make the model improving in terms of time.

Membrane Dissolution in Distributed Architectures of P-Systems

The goal of this paper is twofold. Firstly, to survey in a systematic and uniform way the main results regarding the way membranes can be placed on processors in order to get a software/hardware simulation of P-Systems in a distributed environment. Secondly, we improve some results about the membrane dissolution problem, prove that it is connected, and discuss the possibility of simulating this property in the distributed model. All this yields an improvement in the system parallelism implementation since it gets an increment of the parallelism of the external communication among processors. Also, the number of processors grows in such a way that is notorious the increment of the parallelism in the application of the evolution rules and the internal communica-tionsstudy because it gets an increment of the parallelism in the application of the evolution rules and the internal communications. Proposed ideas improve previous architectures to tackle the communication bottleneck problem, such as reduction of the total time of an evolution step, increase of the number of membranes that could run on a processor and reduction of the number of processors

Solving SAT in linear time with a neural-like membrane system

We present in this paper a neural-like membrane system solving the SAT problem in linear time. These neural Psystems are nets of cells working with multisets. Each cell has a finite state memory, processes multisets of symbol-impulses, and can send impulses (?excitations?) to the neighboring cells. The maximal mode of rules application and the replicative mode of communication between cells are at the core of the eficiency of these systems.

Simulating accepting networks of evolutionary processors with filtered connections by accepting evolutionary P systems

In this work, we propose a variant of P system based on the rewriting of string-objects by means of evolutionary rules. The membrane structure of such a P system seems to be a very natural tool for simulating the filters in accepting networks of evolutionary processors with filtered connections. We discuss an informal construction supporting this simulation. A detailed proof is to be considered in an extended version of this work.

Limits of the power of Tissue P systems with cell division

Tissue P systems generalize the membrane structure tree usual in original models of P systems to an arbitrary graph. Basic opera- tions in these systems are communication rules, enriched in some variants with cell division or cell separation. Several variants of tissue P systems were recently studied, together with the concept of uniform families of these systems. Their computational power was shown to range between P and NP ? co-NP , thus characterizing some interesting borderlines between tractability and intractability. In this paper we show that com- putational power of these uniform families in polynomial time is limited by the class PSPACE . This class characterizes the power of many clas- sical parallel computing models

Identification and functional characterization of Rhizobium leguminosarum bv. viciae genetic systems involved in nickel homeostasis.

A collection of Rhizobium leguminosarum bv. viciae strains isolated from ultramafic and contaminated soils in Italy and Germany, respectively, was analyzed for resistance to nickel and cobalt ions. These assays led to the identification of strain UPM1137, which is able to grow at high concentrations of nickel and cobalt. In order to identify genetic systems involved in the homeostasis to these metals, a random mutagenesis was carried out in UPM1137 by inserting a Tn5-derivative minitransposon. As a result 4313 transconjugants were obtained, being 39 of them (0.90%) unable to grow at 1.5 mM NiCl2. The identification of the transposon insertion site in these mutants showed that the disrupted genes encode proteins belonging to different functional categories, where the secreted and membrane proteins were the most numerous. The analysis of heavy metal resistance and phenotypes in symbiotic and free –living cells will define the contribution of these genes to metal homeostasis.