On the power and size of extended gemmating P systems

In [3] P systems with gemmation of mobile membranes were examined. It was shown that (extended) systems with eight membranes are as powerful as the Turing machines. Moreover, it was proved that extended gemmating P systems with only pre-dynamical rules are still computationally complete: in this case nine membranes are needed to obtain this computational power. In this paper we improve the above results concerning the size bound of extended gemmating P systems, namely we prove that these systems with at most five membranes (with meta-priority relations and without communication rules) form a class of universal computing devices, while in the case of extended systems with only pre-dynamical rules six membranes are enough to determine any recursively enumerable language.     

Transforming communicating X-machines into P systems

Tissue P systems (tPS) represent a class of P systems in which cells are arranged in a graph rather than a hierarchical structure. On the other hand, communicating X-machines (XMs) are state-based machines, extended with a memory structure and transition functions instead of simple inputs, which communicate via message passing. One could use communicating XMs to create models built out of components in a rather intuitive way. There are investigations showing how various classes of P systems can be modelled as communicating XMs. In this paper, we define a set of principles to transform communicating XMs into tPS. We describe the rules that govern such transformations, present an example to demonstrate the feasibility of this approach and discuss ways to extend it to more general models, such as population P systems, which involve dynamic structures.     

On the Computational Complexity of P Automata

We characterize the classes of languages over finite alphabets which may be described by P automata, i.e., accepting P systems with communication rules only. Motivated by properties of natural computing systems, and the actual behavior of P automata, we study computational complexity classes with a certain restriction on the use of the available workspace in the course of computations and relate these to the language classes described by P automata. We prove that if the rules of the P system are applied sequentially, then the accepted language class is strictly included in the class of languages accepted by one-way Turing machines with a logarithmically bounded workspace, and if the rules are applied in the maximally parallel manner, then the class of context-sensitive languages is obtained.     

带膜分裂和促进剂的通讯膜系统求解QSAT问题

膜计算是自然计算的一个分支,膜计算中所研究的模型均称为膜系统,而细胞间通讯是膜系统的一个重要特征。带膜分裂的通讯膜系统是一种分布式并行计算模型,可以在多项式时间内解决计算困难问题。文中将促进剂引入带膜分裂的类细胞型通讯膜系统,提出了膜系统的一种变型——带膜分裂和促进剂的通讯膜系统,其中,一个促进剂可以同时控制多条规则,而促进剂本身不参与该条规则的进化。文中研究了带膜分裂和促进剂的通讯膜系统的计算效率,证明该类膜系统在使用同向规则长度为2,每条规则中促进剂的个数最多为1时,可以在多项式时间内求解PSPACE完全问题(QSAT问题)的统一解。     

From Watson-Crick L systems to Darwinian P systems

Watson-Crick L systems are language generating devices making use ofWatson-Crick complementarity, a fundamental concept of DNA computing.These devices are Lindenmayer systems enriched with a trigger forcomplementarity transition: if a ``bad' string is obtained, then thederivation continues with its complement which is always a ``good'string. Membrane systems or P systems are distributed parallel computingmodels which were abstracted from the structure and the way offunctioning of living cells. In this paper, we first interpret theresults known about the computational completeness of Watson-Crick E0Lsystems in terms of membrane systems, then we introduce a related way ofcontrolling the evolution in P systems, by using the triggers not in theoperational manner (i.e., turning to the complement in a ``bad'configuration), but in a ``Darwinian' sense: if a ``bad' configurationis reached, then the system ``dies', that is, no result is obtained.The triggers (actually, the checkers) are given as finite state multisetautomata. We investigate the computational power of these P systems.Their computational completeness is proved, even for systems withnon-cooperative rules, working in the non-synchronized way, andcontrolled by only two finite state checkers; if the systems work in thesynchronized mode, then one checker for each system suffices to obtainthe computational completeness.     

Efficient simulation of tissue-like P systems by transition cell-like P systems

In the framework of P systems, it is known that the construction of exponential number of objects in polynomial time is not enough to efficiently solve NP-complete problems. Nonetheless, it could be sufficient to create an exponential number of membranes in polynomial time. Working with P systems whose membrane structure does not increase in size, it is known that it is not possible to solve computationally hard problems (unless P = NP), basically due to the impossibility of constructing exponential number of membranes, in polynomial time, using only evolution, communication and dissolution rules. In this paper we show how a family of recognizer tissue P systems with symport/antiport rules which solves a decision problem can be efficiently simulated by a family of basic recognizer P systems solving the same problem. This simulation allows us to transfer the result about the limitations in computational power, from the model of basic cell-like P systems to this kind of tissue-like P systems.     

Computational power of two stacks with restricted communication

Rewriting systems working on words with a center marker are considered. The derivation is done by erasing a prefix or a suffix and then adding a prefix or a suffix. This models a communication of two stacks according to a fixed protocol defined by the choice of rewriting rules. The paper systematically considers different cases of these systems and determines their expressive power. Several cases are identified where very restricted communication surprisingly yields computational universality.     

Uncovering network traffic anomalies based on their sparse distributions

Characterizing network traffic with higher-dimensional features results in increased complexity of most detectors and classifiers for identifying traffic anomalies. Several key observations from existing studies confirm that network anomalies are typically distributed in a sparse way,with each anomaly essentially characterized by its lower-dimensional features. Based on this important finding,we exploit sparsity in designing a novel detection method for anomalies that ignores redundancies that are dynamically filtered from the feature sets and accurately classifies anomalies. Comparison of our method with three well known techniques shows a10% improvement in accuracy with an O（n） complexity of the classifier.     

Small universal simple spiking neural P systems with weights

Spiking neural P systems with weights（WSN P systems,for short） are a new variant of spiking neural P systems,where the rules of a neuron are enabled when the potential of that neuron equals a given value.It is known that WSN P systems are universal by simulating register machines. However,in these universal systems,no bound is considered on the number of neurons and rules. In this work,a restricted variant of WSN P systems is considered,called simple WSN P systems,where each neuron has only one rule. The complexity parameter,the number of neurons,to construct a universal simple WSN P system is investigated. It is proved that there is a universal simple WSN P system with 48 neurons for computing functions; as generator of sets of numbers,there is an almost simple（that is,each neuron has only one rule except that one neuron has two rules） and universal WSN P system with 45 neurons.     

Parallel communicating grammar systems with regular control and skeleton preserving FRR automata

Parallel communicating grammar systems with regular control (RPCGS, for short) are introduced, which are obtained from returning regular parallel communicating grammar systems by restricting the derivations that are executed in parallel by the various components through a regular control language. For the class of languages that are generated by RPCGSs with constant communication complexity we derive a characterisation in terms of a restricted type of freely rewriting restarting automaton. From this characterisation we obtain that these languages are semi-linear, and that for RPCGSs with constant communication complexity, the centralised variant has the same generative power as the non-centralised variant.     

Complexity Theory and Genetics: The Computational Power of Crossing Over

We study the computational power of systems where information is stored in independent strings and each computational step consists of exchanging information between randomly chosen pairs. To this end we introduce a population genetics model in which the operators of selection and inheritance are effectively computable (in polynomial time on probabilistic Turing machines). We show that such systems are as powerful as the usual models of parallel computations, namely they can simulate polynomial space computations in polynomially many steps. We also show that the model has the same power if the recombination rules for strings are very simple (context sensitive crossing over).     

Lattice based communication P systems with applications in cluster analysis

Membrane computing is widely used in many areas, however, there are several limitations in its structures and rules. Although many researchers are engaged in the study of P systems, seldom focus on improving membrane structures. The purpose of this paper is to propose a new kind of communication P system on lattice (LTC-P systems). We describe membrane structures on lattice with communication rules. The computational completeness of the new P system is proved by simulation of register machine. The new P system is used in solving clustering problems. It is combined with the thought of density-based, partition-based and hierarchical clustering algorithm. Clustering is implemented by supremum and infimum rules. The result is obtained through output membrane. All the processes are conducted in membranes. Cluster result via a \(20\) points data set verifies that the proposed new P systems cluster data set accurately and reduce time complexity. Wine data set are also used in testing the influence of parameters. More suitable \(\varepsilon \) and \({ MinPts}\) are found to gain less missing data which are seen as noise. Comparative results in various aspects indicate LTC-P system based clustering algorithm consumes less time than traditional algorithms significantly. It also uses less rules and gives more simple membrane structures than conventional cell-like P system. The new P system provides an alternative for traditional membrane computing.     

Microbenchmark performance comparison of high-speed cluster interconnects

Today's distributed and high-performance applications require high computational power and high communication performance. Recently, the computational power of commodity PCs has doubled about every 18 months. At the same time, network interconnects that provide very low latency and very high bandwidth are also emerging. This is a promising trend in building high-performance computing environments by clustering - combining the computational power of commodity PCs with the communication performance of high-speed network interconnects. There are several network interconnects that provide low latency and high bandwidth. Traditionally, researchers have used simple microbenchmarks, such as latency and bandwidth tests, to characterize a network interconnects communication performance. Later, they proposed more sophisticated models such as LogP. However, these tests and models focus on general parallel computing systems and do not address many features present in these emerging commercial interconnects. Another way to evaluate different network interconnects is to use real-world applications. However, real applications usually run on top of a middleware layer such as the message passing interface (MPI). Our results show that to gain more insight into the performance characteristics of these interconnects, it is important to go beyond simple tests such as those for latency and bandwidth. In future, we plan to expand our microbenchmark suite to include more tests and more interconnects.     

Characterizing the computational power of energy-based P systems

We investigate the computational power of energy-based P systems, a model of membrane systems, where a fixed amount of energy is associated with each object and the rules transform single objects by adding or removing energy from them. We answer the recently proposed open questions about the power of such systems without priorities associated with the rules, for both sequential and maximally parallel modes. We also conjecture that deterministic energy-based P systems are not computationally complete.     

Tissue P systems with cell separation: attacking the partition problem

Tissue P systems are distributed parallel and non-deterministic computing models in the framework of membrane computing, which are inspired by intercellular communication and cooperation between neurons. Recently, cell separation is introduced into tissue P systems, which enables systems to generate an exponential workspace in a polynomial time. In this work, the computational power of tissue P systems with cell separation is investigated. Specifically, a uniform family of tissue P systems with ce...     

Cell communication in tissue P systems: universality results

We introduce an evolution-communication model for tissue P systems where communication rules are inspired by the general mechanism of cell communication based on signals and receptors: a multiset can enter a cell only in the presence of another multiset. Some basic variants of this model are also considered where communication is restricted either to be unidirectional or to use special multisets of objects called receptors. The universality for all these variants of tissue P systems is then proved by using two cells (three cells in the case of unidirectional communication) and rules of a minimal size.     

Computationally universal P systems without priorities: two catalysts are sufficient

The original model of P systems with symbol objects introduced by Păun was shown to be computationally universal, provided that catalysts and priorities of rules are used. By reduction via register machines Sosík and Freund proved that the priorities may be omitted from the model without loss of computational power. Freund, Oswald, and Sosík considered several variants of P systems with catalysts (but without priorities) and investigated the number of catalysts needed for these specific variants to be computationally universal. It was shown that for the classic model of P systems with the minimal number of two membranes the number of catalysts can be reduced from six to five; using the idea of final states the number of catalysts could even be reduced to four. In this paper we are able to reduce the number of catalysts again: two catalysts are already sufficient. For extended P systems we even need only one membrane and two catalysts. For the (purely) catalytic systems considered by Ibarra only three catalysts are already enough.     

Extended person-machine interface

Current computer natural language systems lack discourse capabilities. They mainly treat utterances in isolation and are not able to track the coherence of extended dialogue. In general, however, human communication and task performance are not accomplished in this manner. Useful interface systems should incorporate extended conversational power. In this paper, we present an abstract computational system for extended person-machine interface. The system is theoretically motivated by an investigation into the human conversational system. The computer system incorporates many of the rules used by individuals in everyday interactions. Use of these rules enable implicit communication between conversants about their underlying models of an interaction. They function in place of explicit meta-communication about the structure of an ongoing exchange. Such communication is necessary since building compatible models of an interaction is necessary for effective interaction. Providing a comparable system of rules for the computer is then mandatory if we expect it to be able to integrate subsequent requests and exchanges to earlier ones.