Compositional Performance Modelling with the TIPPtool

Stochastic process algebras have been proposed as compositional specification formalisms for performance models. In this paper, we describe a tool which aims at realising all beneficial aspects of compositional performance modelling, the TIPPtool. It incorporates methods for compositional specification as well as solution, based on state-of-the-art techniques, and wrapped in a user-friendly graphical front end. Apart from highlighting the general benefits of the tool, we also discuss some lessons learned during development and application of the TIPPtool. A non-trivial model of a real life communication system serves as a case study to illustrate benefits and limitations

Proceedings of International Workshop "Global Computing: Programming Environments, Languages, Security and Analysis of Systems"

According to the IST/ FET proactive initiative on GLOBAL COMPUTING, the goal is to obtain techniques (models, frameworks, methods, algorithms) for constructing systems that are flexible, dependable, secure, robust and efficient. The dominant concerns are not those of representing and manipulating data efficiently but rather those of handling the co-ordination and interaction, security, reliability, robustness, failure modes, and control of risk of the entities in the system and the overall design, description and performance of the system itself. Completely different paradigms of computer science may have to be developed to tackle these issues effectively. The research should concentrate on systems having the following characteristics: • The systems are composed of autonomous computational entities where activity is not centrally controlled, either because global control is impossible or impractical, or because the entities are created or controlled by different owners. • The computational entities are mobile, due to the movement of the physical platforms or by movement of the entity from one platform to another. • The configuration varies over time. For instance, the system is open to the introduction of new computational entities and likewise their deletion. The behaviour of the entities may vary over time. • The systems operate with incomplete information about the environment. For instance, information becomes rapidly out of date and mobility requires information about the environment to be discovered. The ultimate goal of the research action is to provide a solid scientific foundation for the design of such systems, and to lay the groundwork for achieving effective principles for building and analysing such systems. This workshop covers the aspects related to languages and programming environments as well as analysis of systems and resources involving 9 projects (AGILE , DART, DEGAS , MIKADO, MRG, MYTHS, PEPITO, PROFUNDIS, SECURE) out of the 13 founded under the initiative. After an year from the start of the projects, the goal of the workshop is to fix the state of the art on the topics covered by the two clusters related to programming environments and analysis of systems as well as to devise strategies and new ideas to profitably continue the research effort towards the overall objective of the initiative. We acknowledge the Dipartimento di Informatica and Tlc of the University of Trento, the Comune di Rovereto, the project DEGAS for partially funding the event and the Events and Meetings Office of the University of Trento for the valuable collaboration

Automata-based adaptive behavior for economic modeling using game theory

In this paper, we deal with some specific domains of applications to game theory. This is one of the major class of models in the new approaches of modelling in the economic domain. For that, we use genetic automata which allow to buid adaptive strategies for the players. We explain how the automata-based formalism proposed - matrix representation of automata with multiplicities - allows to define a semi-distance between the strategy behaviors. With that tools, we are able to generate an automatic processus to compute emergent systems of entities whose behaviors are represented by these genetic automata

A Local Logic for Realizability in Web Service Choreographies

Web service choreographies specify conditions on observable interactions among the services. An important question in this regard is realizability: given a choreography C, does there exist a set of service implementations I that conform to C ? Further, if C is realizable, is there an algorithm to construct implementations in I ? We propose a local temporal logic in which choreographies can be specified, and for specifications in the logic, we solve the realizability problem by constructing service implementations (when they exist) as communicating automata. These are nondeterministic finite state automata with a coupling relation. We also report on an implementation of the realizability algorithm and discuss experimental results.Comment: In Proceedings WWV 2014, arXiv:1409.229

SCOOP: A Tool for SymboliC Optimisations Of Probabilistic Processes

This paper presents SCOOP: a tool that symbolically optimises process-algebraic specifications of probabilistic processes. It takes specifications in the prCRL language (combining data and probabilities), which are linearised first to an intermediate format: the LPPE. On this format, optimisations such as dead-variable reduction and confluence reduction are applied automatically by SCOOP. That way, drastic state space reductions are achieved while never having to generate the complete state space, as data variables are unfolded only locally. The optimised state spaces are ready to be analysed by for instance CADP or PRISM

Symbolic Implementation of Connectors in BIP

BIP is a component framework for constructing systems by superposing three layers of modeling: Behavior, Interaction, and Priority. Behavior is represented by labeled transition systems communicating through ports. Interactions are sets of ports. A synchronization between components is possible through the interactions specified by a set of connectors. When several interactions are possible, priorities allow to restrict the non-determinism by choosing an interaction, which is maximal according to some given strict partial order. The BIP component framework has been implemented in a language and a tool-set. The execution of a BIP program is driven by a dedicated engine, which has access to the set of connectors and priority model of the program. A key performance issue is the computation of the set of possible interactions of the BIP program from a given state. Currently, the choice of the interaction to be executed involves a costly exploration of enumerative representations for connectors. This leads to a considerable overhead in execution times. In this paper, we propose a symbolic implementation of the execution model of BIP, which drastically reduces this overhead. The symbolic implementation is based on computing boolean representation for components, connectors, and priorities with an existing BDD package