Paolo Ballarini

Model Checking Medium Access Control for Sensor Networks

We describe verification of S-MAC, a medium access control protocol designed for wireless sensor networks, by means of the PRISM model checker. The S-MAC protocol is built on top of the IEEE 802.11 standard for wireless ad hoc networks and, as such, it uses the same randomised backoff procedure as a means to avoid collision. In order to minimise energy consumption, in S-MAC, nodes are periodically put into a sleep state. Synchronisation of the sleeping schedules is necessary for the nodes to be able to communicate. Intuitively, energy saving obtained through a periodic sleep mechanism will be at the expense of performance. In previous work on S-MAC verification, a combination of analytical techniques and simulation has been used to confirm the correctness of this intuition for a simplified (abstract) version of the protocol in which the initial schedules coordination phase is assumed correct. We show how we have used the PRISM model checker to verify the behaviour of S-MAC and compare it to that of IEEE 802.11.

Taming the complexity of biological pathways through parallel computing

Biological systems are characterised by a large number of interacting entities whose dynamics is described by a number of reaction equations. Mathematical methods for modelling biological systems are mostly based on a centralised solution approach: the modelled system is described as a whole and the solution technique, normally the integration of a system of ordinary differential equations (ODEs) or the simulation of a stochastic model, is commonly computed in a centralised fashion. In recent times, research efforts moved towards the definition of parallel/distributed algorithms as a means to tackle the complexity of biological models analysis. In this article, we present a survey on the progresses of such parallelisation efforts describing the most promising results so far obtained.

BlenX4Bio --- BlenX for Biologists

We introduce BlenX4Bio, a high-level interface for the programming language BlenX. BlenX4Bio allows biologists to write BlenX programs without having any programming skills. The main elements of a biological model are specified by filling in a number of tables. Such tables include descriptions of both static and dynamic aspects of the biological system at hand and can then be automatically mapped to BlenX programs for simulation and analysis by means of the CoSBi Lab software platform. In this paper we illustrate the main characteristics of BlenX4Bio through examples taken from biology textbooks.

Parametric stochastic well-formed nets and compositional modelling

Colored nets have been recognized as a powerful modelling paradigm for the validation and evaluation of systems, both in terms of compact representation and aggregate state space generation. In this paper we discuss the issue of adding compositionality to a class of stochastic colored nets named Stochastic Well-formed Nets, in order to increase modularity and reuse of the modelling efforts. This requires the notion of Parametric Stochastic Well-formed net: nets in which a certain amount of information is left unspecified, and is instantiated only upon model composition. The choice of the compositional rule has been based on previous work on layered models for integrated hardware and software systems (the processes, services and resources methodology), and an example of layered modelling with Parametric Stochastic Well-formed net is presented to show the efficacy of the proposed formalism.

Modeling tools for detecting DoS attacks in WSNs

Detecting denial-of-service (DoS) attacks and reducing the energy consumption are two important and frequent requirements in wireless sensor networks (WSNs). In this paper, we propose an energy-preserving solution to detect compromised nodes in hierarchically clustered WSNs. DoS detection is based on using dedicated inspector nodes (cNodes) whose role is to analyze the traffic inside a cluster and to send warnings to the cluster head whenever an abnormal behavior (i.e., high packets throughput) is detected. With previously introduced DoS detection schema, cNodes are statically displaced in strategic positions within the network topology. This guarantees good detection coverage but leads to quickly draining cNodes battery. In this paper, we propose a dynamic cNodes displacement schema according to which cNodes are periodically elected among ordinary nodes of each atomic cluster. Such a solution results in a better energy balance while maintaining good detection coverage. We analyze the tradeoffs between static and dynamic solutions by means of two complementary approaches: through simulation with the NS-2 simulation platform and by means of statistical model checking with the Hybrid Automata Stochastic Logic. Copyright

HASL: A new approach for performance evaluation and model checking from concepts to experimentation

We introduce the Hybrid Automata Stochastic Language (HASL), a new temporal logic formalism for the verification of Discrete Event Stochastic Processes (DESP). HASL employs a Linear Hybrid Automaton (LHA) to select prefixes of relevant execution paths of a DESP. LHA allows rather elaborate information to be collected on-the-fly during path selection, providing the user with powerful means to express sophisticated measures. A formula of HASL consists of an LHA and an expression Z referring to moments of path random variables. A simulation-based statistical engine is employed to obtain a confidence interval estimate of the expected value of Z. In essence, HASL provides a unifying verification framework where temporal reasoning is naturally blended with elaborate reward-based analysis. Moreover, we have implemented a tool, named COSMOS, for performing analysis of HASL formula for DESP modelled by Petri nets. Using this tool we have developed two detailed case studies: a flexible manufacturing system and a genetic oscillator.

An LTL Model Checking Approach for Biological Parameter Inference

The identification of biological parameters governing dynamics of Genetic Regulatory Networks (GRN) poses a problem of combinatorial explosion, since the possibilities of parameter instantiation are numerous even for small networks. In this paper, we propose to adapt LTL model checking algorithms to infer biological parameters from biological properties given as LTL formulas. In order to reduce the combinatorial explosion, we represent all the dynamics with one parametric model, so that all GRN dynamics simply result from all eligible parameter instantiations. LTL model checking algorithms are adapted by postponing the parameter instantiation as far as possible. Our approach is implemented within the SPuTNIk tool.

Transient analysis of networks of stochastic timed automata using stochastic state classes

Stochastic Timed Automata (STA) associate logical locations with continuous, generally distributed sojourn times. In this paper, we introduce Networks of Stochastic Timed Automata (NSTA), where the components interact with each other by message broadcasts. This results in an underlying stochastic process whose state is made of the vector of logical locations, the remaining sojourn times, and the value of clocks. We characterize this general state space Markov process through transient stochastic state classes that sample the state and the absolute age after each event. This provides an algorithmic approach to transient analysis of NSTA models, with fairly general termination conditions which we characterize with respect to structural properties of individual components that can be checked through straightforward algorithms.

Validation and evaluation of a software solution for fault tolerant distributed synchronization

This paper presents a case study on the combined use of different tools and techniques for the validation and evaluation, from, the early stages of the design, of a fault tolerant software mechanism named distributed synchronization. The mechanism has been specified using UML state charts and sequence diagrams. A number of stochastic well-formed nets (SWN) models have been derived from the specifications: they have been composed using the tool algebra, and the resulting model has been model-checked using the PROD tool for temporal logic properties, thanks to a GreatSPN-to-PROD translator. The quantitative analysis has been performed using the SWN solvers of the Great-SPN tool.

Expressing and computing passage time measures of GSPN models with HASL

Passage time measures specification and computation for Generalized Stochastic Petri Net models have been faced in the literature from different points of view. In particular three aspects have been developed: (1) how to select a specific token (called the tagged token) and measure the distribution of the time employed from an entry to an exit point in a subnet; (2) how to specify in a flexible way any condition on the paths of interest to be measured, (3) how to efficiently compute the required distribution. In this paper we focus on the last two points: the specification and computation of complex passage time measures in (Tagged) GSPNs using the Hybrid Automata Stochastic Logic (HASL) and the statistical model checker COSMOS. By considering GSPN models of two different systems (a flexible manufacturing system and a workflow), we identify a number of relevant performance measures (mainly passage-time distributions), formally express them in HASL terms and assess them by means of simulation in the COSMOS tool. The interest from the measures specification point of view is provided by the possibility of setting one or more timers along the paths, and setting the conditions for the paths selection, based on the measured values of such timers. With respect to other specification languages allowing to use timers in the specification of performance measures, HASL provides timers suspension, reactivation, and rate change along a path.