Using Probability to Reason about Soft Deadlines

Soft deadlines are significant in systems in which a bound on the response time is important, but the failure to meet the response time is not a disaster. Soft deadlines occur, for example, in telephony and switching networks. We investigate how to put probabilistic bounds on the time-complexity of a concurrent logic program by combining (on-line) profiling with an (off-line) probabilistic complexity analysis. The profiling collects information on the likelihood of case selection and the analysis uses this information to infer the probability of an agent terminating within k steps. Although the approach does not reason about synchronization, we believe that its simplicity and good (essentially quadratic) complexity mean that it is a promising first step in reasoning about soft deadlines

Analysis of a Multimedia Stream using Stochastic Process Algebra

It is now well recognised that the next generation of distributed systems will be distributed multimedia systems. Central to multimedia systems is quality of service, which defines the non-functional requirements on the system. In this paper we investigate how stochastic process algebra can be used in order to determine the quality of service properties of distributed multimedia systems. We use a simple multimedia stream as our basic example. We describe it in the Stochastic Process Algebra PEPA and then we analyse whether the stream satisfies a set of quality of service parameters: throughput, end-to-end latency, jitter and error rates

Modelling opacity using petri nets

We consider opacity as a property of the local states of the secure (or high-level) part of the system, based on the observation of the local states of a low-level part of the system as well as actions. We propose a Petri net modelling technique which allows one to specify different information flow properties, using suitably defined observations of system behaviour. We then discuss expressiveness of the resulting framework and the decidability of the associated verification problems

Common Representation of Information Flows for Dynamic Coalitions

We propose a formal foundation for reasoning about access control policies within a Dynamic Coalition, defining an abstraction over existing access control models and providing mechanisms for translation of those models into information-flow domain. The abstracted information-flow domain model, called a Common Representation, can then be used for defining a way to control the evolution of Dynamic Coalitions with respect to information flow

Constraint Oriented Specification with CSP and Real Time Temporal Logic

A popular specification style, particularly for the initial specification of a system, is the em constraint-oriented style, where the constraints are properties required to hold of the final system. One of the difficulties of using this style is that, for any particular notation, certain types of constraints are much harder to capture than others. In this paper we propose such a specification framework, which allows the specifier a choice of two languages: Communicating Sequential Processes (CSP) and a version of Propositional Temporal Logic (PTL). The components of a specification have to be checked for mutual consistency, to do this we present a common semantic framework for both PTL and CSP

Stochastic specification and verification

Modern distributed systems include a class of applications in which non-functional requirements are important. In particular, these applications include multimedia facilities where real time constraints are crucial to their correct functioning. In order to specify such systems it is necessary to describe that events occur at times given by probability distributions. Stochastic process algebras have emerged as a useful technique by which such systems can be specified and verified. However, stochastic descriptions are very general, in particular they allow the use of general probability distribution functions, and therefore their verification can be complex. In this paper we define a translation from stochastic process algebras to timed automata. By doing so we aim to use the simpler verification methods for timed automata (e.g. reachability properties) for the more complex stochastic descriptions

A Model Checking Algorithm for Stochastic Systems

In this report we present an algorithm for model checking stochastic automata. The algorithm, which is essentially based on discretising time, permits generalised distributions to be used

Specification and Analysis of Automata-based Designs

One of the results of research into formal system specification has been the large number of notations which have been developed. Of these notations, automata have emerged as a promising vehicle for the specification, and particularly the analysis, of systems. This is especially so when the systems under consideration include timing requirements, and timed automata model such systems as a finite set of states with timed transitions between them. However, not all specifications involve deterministic timing, and stochastic automata can be used in these circumstances. In this paper we consider both timed and stochastic automata, and demonstrate how they can be used in the same design. We will also consider what analysis of the specification can then be performed. In particular, we will describe how to translate stochastic to timed automata, and look at two approaches to model checking the stochastic components of an integrated design

A Manual for a ModelChecker for Stochastic Automata

This technical report describes a modelchecker for Stochastic Automata, which was built based on the theory described in [BBD00]. The tool is available from: http://www.cs.ukc.ac.uk/people/staff/dha/index.html It accepts a stochastic automaton, a 'timed probabilistic until' formula pattern and a time step parameter. Note that we do not yet allow adversaries, a clock which guards two or more transitions is considered a (run-time) error. Also, we have not yet implemented the full range of the temporal logic in [BBD00]; only the 'timed probabilistic until' queries are allowed, and propositions must be atomic. The algorithm will return one of three results: true, false or undecided. If it returns true, then the automaton models the formula. If it returns false, then the automaton does not model the formula. If it returns undecided, then the algorithm was unable to determine whether the automaton models the formula