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Universität Tübingen 15 Wilhelm Schickard-Institut für Informatik 15. Theorietag der GI Fachgruppe 0.1.5 Automaten und Forn1ale Sprachen Henning Fernau (Ed.) WSI-2005-16 Universität Tübingen 15. Theorietag der GI Fachgruppe 0.1.5 A uton1aten und Forn1ale Sprachen Henning Fernau (Ed.) WSI-2005-16 Henning Fernau Wilhelm-Schickard-Institut für Informatik Universität Tübingen Sand 13 D-72076 Tübingen Germany E-Mail: f ernau©informatik. uni-tuebingen. de Telefon: (07071) 29-77565 Telefax: (07071) 29-5061 © Wilhelm-Schickard-Institut für Informatik, 2005 ISSN 0946-3852 15. Theorietag der GI Fachgruppe 0.1.5 Automaten und Formale Sprachen Henning Fernau (Ed.) WSI-2005-16 Dies ist nun bereits der 15. "Jahrestag" der GI Fachgruppe 0.1.5 "Automa­ ten und Formale Sprachen," der "reihum" an verschiedenen Orten Deutschlands (und auch Österreichs) stattfindet. Am 28. und am 29. September 2005 fand die­ ses Treffen statt in Lauterbad bei Freudenstadt, organisatorisch betreut von der Formalsprachlergruppe in Tübingen. Der Theorietag gibt die Gelegenheit, Ergebnisse formalsprachlicher Forschun­ gen aus Deutschland und dem angrenzenden Ausland kennenzulernen und natür­ lich eigene Resultate vorzustellen. Wichtiger vielleicht ist noch der persönliche Kontakt, der durch solche Treffen ermöglicht wird. Manch eine Arbeit wäre ver­ mutlich gar nicht zustande gekommen ohne vorherige Treffen, Gespräche und Anregungen. Daneben soll der Theorietag Gelegenheit geben, ein bestimmtes Themenge­ biet aus dem Bereich der Formalen Sprachen (im weitesten Sinne) vertiefend zu behandeln. Dazu dienen eingeladene Vorträge an einem dem "eigentlichen" Theorietag (der sich ja über anderthalb Tage erstreckt) "vorgelagerten" Tag. In diesem Jahr ist das Thema dieser Überblicksvorträge "Lernen von Automaten und Grammatiken." Als Sprecher konnten gewonnen werden: • Colin de la Higuera von der Universität von St. Etienne, • Hans-Ulrich Krieger vom MPI Saarbrücken und • Joachim Niehren von der Universität 3 aus Lille. Die entsprechenden Zusammenfassungen sind m emem separaten Technischen Bericht (WSI-2005-15) zusammengetragen. Um diesen Aspekt noch weiter zu betonen, wurde jenem Tag mit Überblicks• vorträgen ein weiterer Tag vorgelagert, an dem sich einige (inter )nationale For­ scher über "Lernen von Automaten und Grammatiken" austauschen können. Die zugehörigen Zusammenfassungen sind im Technischen Bericht WSI-2005-14 zu­ sammengetragen. In dieser Abfolge äußert sich die Hoffnung, dass doch das ein oder andere "Gespräch am Rari9e" stattfindet, das manchen Formalsprachler für Grammatische Inferenz interessieren mag oder auch manchen "Lerner" auf (möglicherweise zu seinem Arbeitsgebiet verwandte) Fragestellungen (und viel­ leicht auch Antworten / Ergebnisse) aus dem Bereich der Formalen Sprachen aufmerksam macht. Natürlich dienen zu diesem Zweck auch die Vorträge. Wir sind dankbar für die finanzielle Unterstützung durch IBM und die Ge­ sellschaft für Informatik (GI) und für die vor allem administrative Unterstützung von Seiten der Universität Tübingen. 11 Membrane systems as a model for distributed computing ________ 1 A . Binder, R. Freund, G. Lojka und M. Oswald Formal language characterizations of P, NP, and PSPACE ________ 6 B. Borchert Revolving-input finite automata __________________ 7 H. Bordihn, M. Holzer und M . Kutrib Path languages of rpc tree grammars ________________ 9 F. Drewes und B. v. d. M erwe Optimal nonterminal complexity of graph-controlled grammars _____ 13 H. Fernau, R. Freund, M . Oswald und K . Reinhardt Eindeutige Homomorphismen in freien Monoiden ___________ 18 D. D. Freydenberger, D. Reidenbach und J. C. Schneider Einige Bemerkungen zu Forgetting Automata ____________ 22 J. Glöckler A note on the number of transitions of nondeterministic finite automata __ 24 H. Gruber und M. Holzer On Parikh images of higher-order pushdown automata _________ 26 W. Karianto Fast substring matching _ _ ___________________ 30 A . Klein Context-dependent nondeterminism for pushdown automata _______ 33 M. K utrib und A. M alcher Finite turns and the regular closure of linear context-free languages ____ 37 M. K utrib und A. M alcher Endliche Automaten und verallgemeinerte disjunktive Sequenzen _____ 41 J. Mielke Parametrized syntactic analysis by freely rewriting Restarting Automata _ 45 F. Mraz, F. Otto und M. Platek On the Descriptional Complexity of Restarting Automata ________ 49 J. Reimann lll Reachability in Petri nets with inhibitor arcs, priority multicounter automata and first order logic with monotone transitive closure 53 K. Reinhardt Äquivalenz von Bildsprachen synchroner, deterministischer Ketten-Code-Bild­ Systeme ~~~~~~~~~~~~~~~~~~~~~~~~~~~ 59 B. Truthe lV Membrane Systems as a Model for Distributed Computing ANETA BINDER, RUDOLF FREUND, GEORG LOJKA, MARION ÜSWALD 1 Institut für Computersprachen, Fakultät für Informatik Technische Universität Wien, Favoritenstr. 9-11, A-104 0 Wien, A ustria e-mail: { ani, rudi, georg ,marion}©emcc. at ABSTRACT Based on the biological model of cell-to-cell communication proposed by A. Rustom et al. in [10], cells able to dynamically form connections (channels) between them according to specific constraints possibly relying on some attributes assigned to the memb"tanes of the cells as weil as of their contents were investigated in (5] and shown to be computationally complete even when using only some of the characteristic features of the general model. These P systems with dynamic channels transporting membrane vesicles here are considered as models for describing distributed systems; the efficiency of modelling specific processes in various applications depends on the specific features of the chosen model of P systems with dynamic channels transporting membrane vesicles. Keywords: distributed systems, membrane computing 1. Introduction Membrane systems were introduced in 1998 by Gh. Päun in [7] as a parallel distributed model of computation abstracted from cell functioning. In a membrane structure (that can be represented as a tree in P systems or as an arbitrary graph in the more general case of tissue P systems), multisets of objects can evolve according to given evolution rules. Many variants of membrane systems (P systems) have been considered so far, see [8] for a comprehensive overview and [9] for the actual status of research. Like in the biological model of cell-to-cell communication proposed by A. Rustom et al. in [10], in [5] cells (like in tissue P systems) able to dynamically form connections ( channels or nanotubes in the sense of [10]) between them according to specific constraints possibly relying on some attributes assigned to the membranes of the cells as well as of their contents were considered. In contrast to other models of P systems, there multisets of elementary objects are transported in membrane vesicles through nanotubes (channels). The transport of a membrane vesicle through a nanotu be between two cells may depend on the contents of the membrane vesicle itself as well as on the objects contained in the two cells connected by this nanotube, on the specific attributes assigned to the cell membr.anes and the membrane of the vesicle to be transported through the nanotube as well as on th_e specific state of the nanotube ( channel). To model these biological systems as described by A. Rustom et al., in [5] P systems with dynamic channels transporting membrane vesicles were considered to work in the asynchronous mode (an arbitrary number of rules that do not interfere with each other can be carried out in parallel in one derivation step) or in the sequential mode ( exactly one rule is carried out in one derivation step); for an overview on P systems working in the asynchronous or in the sequential mode see [4]. On the other hand, for simulating models of distributed systems and 1 Supported by the FWF-project T225-N04. 2 Binder, Freund, Lojka, Oswald mobile software agents we can also use P systems with dynamic channels transporting membrane vesicles working in the maximally parallel mode (which means that as many processes as possible are carried out in parallel). In this paper we discuss the potentials of this model of P systems (membrane systems) for modelling and simulating (processes in) distributed systems. After pointing out some features of distributed systems in the second section, in the third section we introduce the general model of P systems with dynamic channels transporting mem­ brane vesicles (which were shown tobe co_mputationally complete in [5]). The potentials of this model of P systems (membrane systems) for modelling and simulating (processes in) distributed systems are discussed in the fourth section. 2. D istributed Systems A distributed system consists of a collection of autonomous, geograplücally-dispersed computing entities (e.g., see [1], [6]) which are equipped with suitable software and are connected by some suitable communication medium (LAN, WAN or the Internet); the software enables the single computers ( components) of the network to coordinate their activities and share their resources of the system - hardware, software and data. Traditionally, we may distinguish four "categories of distributed computing": cluster comput­ ing (similar machines, generally servers of similar power and configuration, are joined to form a virtual machine); peer-to-peer (many computers are linked to aggregate processing power; the communication often is carried out via the Internet); distributed computing (a wide variety of computer types and computing resources, such as storage area networks, is connected
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