81 research outputs found

    Do I need to fix a failed component now, or can I wait until tomorrow?

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    We investigate how predictive event-based modelling can inform operational decision making in complex systems with component failures. By relating the status of components to service availability, and using stochastic temporal logic reasoning, we quantify the risk of service failure now, and in the future, after a given elapsed time. Decisions can then be taken according to those risks. We demonstrate the approach through application to an industrial case study system in which component failures are sensed and monitored. The system has been deployed for some time. A novel aspect is we calibrate the model(s) according to inferences over historical field data, thus the results of our reasoning can inform decision making in the actual deployed system

    Modelling IEEE 802.11 CSMA/CA RTS/CTS with stochastic bigraphs with sharing

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    Stochastic bigraphical reactive systems (SBRS) is a recent formalism for modelling systems that evolve in time and space. However, the underlying spatial model is based on sets of trees and thus cannot represent spatial locations that are shared among several entities in a simple or intuitive way. We adopt an extension of the formalism, SBRS with sharing, in which the topology is modelled by a directed acyclic graph structure. We give an overview of SBRS with sharing, we extend it with rule priorities, and then use it to develop a model of the 802.11 CSMA/CA RTS/CTS protocol with exponential backoff, for an arbitrary network topology with possibly overlapping signals. The model uses sharing to model overlapping connectedness areas, instantaneous prioritised rules for deterministic computations, and stochastic rules with exponential reaction rates to model constant and uniformly distributed timeouts and constant transmission times. Equivalence classes of model states modulo instantaneous reactions yield states in a CTMC that can be analysed using the model checker PRISM. We illustrate the model on a simple example wireless network with three overlapping signals and we present some example quantitative properties

    Stochastic model checking for predicting component failures and service availability

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    When a component fails in a critical communications service, how urgent is a repair? If we repair within 1 hour, 2 hours, or n hours, how does this affect the likelihood of service failure? Can a formal model support assessing the impact, prioritisation, and scheduling of repairs in the event of component failures, and forecasting of maintenance costs? These are some of the questions posed to us by a large organisation and here we report on our experience of developing a stochastic framework based on a discrete space model and temporal logic to answer them. We define and explore both standard steady-state and transient temporal logic properties concerning the likelihood of service failure within certain time bounds, forecasting maintenance costs, and we introduce a new concept of envelopes of behaviour that quantify the effect of the status of lower level components on service availability. The resulting model is highly parameterised and user interaction for experimentation is supported by a lightweight, web-based interface

    Bigraphs with sharing

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    Bigraphical Reactive Systems (BRS) were designed by Milner as a universal formalism for modelling systems that evolve in time, locality, co-locality and connectivity. But the underlying model of location (the place graph) is a forest, which means there is no straightforward representation of locations that can overlap or intersect. This occurs in many domains, for example in wireless signalling, social interactions and audio communications. Here, we define bigraphs with sharing, which solves this problem by an extension of the basic formalism: we define the place graph as a directed acyclic graph, thus allowing a natural representation of overlapping or intersecting locations. We give a complete presentation of the theory of bigraphs with sharing, including a categorical semantics, algebraic properties, and several essential procedures for computation: bigraph with sharing matching, a SAT encoding of matching, and checking a fragment of the logic BiLog. We show that matching is an instance of the NP-complete sub-graph isomorphism problem and our approach based on a SAT encoding is also efficient for standard bigraphs. We give an overview of BigraphER (Bigraph Evaluator & Rewriting), an efficient implementation of bigraphs with sharing that provides manipulation, simulation and visualisation. The matching engine is based on the SAT encoding of the matching algorithm. Examples from the 802.11 CSMA/CA RTS/CTS protocol and a network management support system illustrate the applicability of the new theory

    An adequate logic for full LOTOS

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    We present a novel result for a logic for symbolic transition systems based on LOTOS processes. The logic is adequate with respect to bisimulation defined on symbolic transition systems

    Is my configuration any good: checking usability in an interactive sensor-based activity monitor

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    We investigate formal analysis of two aspects of usability in a deployed interactive, configurable and context-aware system: an event-driven, sensor-based homecare activity monitor system. The system was not designed from formal requirements or specification: we model the system as it is in the context of an agile development process. Our aim was to determine if formal modelling and analysis can contribute to improving usability, and if so, which style of modelling is most suitable. The purpose of the analysis is to inform configurers about how to interact with the system, so the system is more usable for participants, and to guide future developments. We consider redundancies in configuration rules defined by carers and participants and the interaction modality of the output messages.Two approaches to modelling are considered: a deep embedding in which devices, sensors and rules are represented explicitly by data structures in the modelling language and non-determinism is employed to model all possible device and sensor states, and a shallow embedding in which the rules and device and sensor states are represented directly in propositional logic. The former requires a conventional machine and a model-checker for analysis, whereas the latter is implemented using a SAT solver directly on the activity monitor hardware. We draw conclusions about the role of formal models and reasoning in deployed systems and the need for clear semantics and ontologies for interaction modalities

    Data-driven modelling and probabilistic analysis of interactive software usage

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    This paper answers the research question: how can we model and understand the ways in which users actually interact with software, given that usage styles vary from user to user, and even from use to use for an individual user. Our first contribution is to introduce two new probabilistic, admixture models, inferred from sets of logged user traces, which include observed and latent states. The models encapsulate the temporal and stochastic aspects of usage, the heterogeneous and dynamic nature of users, and the temporal aspects of the time interval over which the data was collected (e.g. one day, one month, etc.). A key concept is activity patterns, which encapsulate common observed temporal behaviours shared across a set of logged user traces. Each activity pattern is a discrete-time Markov chain in which observed variables label the states; latent states specify the activity patterns. The second contribution is how we use parametrised, probabilistic, temporal logic properties to reason about hypothesised behaviours within an activity pattern, and between activity patterns. Different combinations of inferred model and hypothesised property afford a rich set of techniques for understanding software usage. The third contribution is a demonstration of the models and temporal logic properties by application to user traces from a software application that has been used by tens of thousands of users worldwide

    Modelling and analysis of biochemical signalling pathway cross-talk

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    Signalling pathways are abstractions that help life scientists structure the coordination of cellular activity. Cross-talk between pathways accounts for many of the complex behaviours exhibited by signalling pathways and is often critical in producing the correct signal-response relationship. Formal models of signalling pathways and cross-talk in particular can aid understanding and drive experimentation. We define an approach to modelling based on the concept that a pathway is the (synchronising) parallel composition of instances of generic modules (with internal and external labels). Pathways are then composed by (synchronising) parallel composition and renaming; different types of cross-talk result from different combinations of synchronisation and renaming. We define a number of generic modules in PRISM and five types of cross-talk: signal flow, substrate availability, receptor function, gene expression and intracellular communication. We show that Continuous Stochastic Logic properties can both detect and distinguish the types of cross-talk. The approach is illustrated with small examples and an analysis of the cross-talk between the TGF-b/BMP, WNT and MAPK pathways

    Temporal analytics for software usage models

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    We address the problem of analysing how users actually interact with software. Users are heterogeneous: they adopt different usage styles and each individual user may move between different styles, from one interaction session to another, or even during an interaction session. For analysis, we require new temporal analytics: techniques to model and analyse temporal data sets of logged interactions with the purpose of discovering, interpreting, and communicating meaningful patterns of usage. We define new probabilistic models whose parameters are inferred from logged time series data of user-software interactions. We formulate hypotheses about software usage together with the developers, encode them in probabilistic temporal logic, and analyse the models according to the probabilistic properties. We illustrate by application to logged data from a deployed mobile application software used by thousands of users

    Preface

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