Quantitative Analysis of Collective Adaptive Systems

  title={Quantitative Analysis of Collective Adaptive Systems},
  author={Jane Hillston},
  booktitle={Ershov Memorial Conference},
  • J. Hillston
  • Published in Ershov Memorial Conference 24 August 2015
  • Computer Science
Quantitative formal methods, such as stochastic process algebras, have been used for the last twenty years to support modelling of dynamic systems in order to investigate their performance. Application domains have ranged from computer and communication systems [1, 2], to intracellular signalling pathways in biological cells [3, 4]. Nevertheless this modelling approach is challenged by the demands of modelling modern collective adaptive systems, many of which have a strong spatial aspect… 



Hybrid behaviour of Markov population models

Bio-PEPA: A framework for the modelling and analysis of biological systems

CARMA: Collective Adaptive Resource-sharing Markovian Agents

The basic principles of CARMA are introduced and then it is shown how the language can be used to support specification with a simple but illustrative example of a socio-technical collective adaptive system.

The Benefits of Sometimes Not Being Discrete

This paper will motivate this approach, explaining the theoretical foundations and their practical benefits of the approach, by approximating the discrete system by a continuous one.

Specification and Analysis of Open-Ended Systems with CARMA

The environment in Carma models can evolve at runtime, due to the feedback from the system, and it further modulates the interaction between components, by shaping rates and interaction probabilities.

Formal modeling and quantitative analysis of KLAIM-based mobile systems

STOCKLAIM is proposed, a STOchastic extension of cKLAIM, the core subset of KLAIM that makes it possible to integrate the modeling of quantitative aspects of mobile systems with the functional specification of such systems.

A class of generalized stochastic Petri nets for the performance evaluation of multiprocessor systems

It is shown that GSPN are equivalent to continuous-time stochastic processes, and solution methods for the derivation of the steady state probability distribution are presented.

Interactive Markov Chains

  • H. Hermanns
  • Mathematics, Art
    Lecture Notes in Computer Science
  • 2002
This paper presents a meta-analyses of interactive Markov Chains and its applications to knowledge representation, specifically in the context of knowledge representation and representation in the discrete-time model.

Sequential Processing Machines (S.P.M) Analyzed With a Queuing Theory Model

The results are obtained directly by recognizing that a sequential processing may be viewed as a cyclic queue, and are good only for exponentially distributed computation times.