A formal framework for modelling and analysing mobile systems

This paper presents a formal framework for modelling and analysing mobile systems. The framework comprises a collection of models of the dominant design paradigms which are readily extended to incorporate details of particular technologies, i.e., programming languages and their run-time support, and applications. The modelling language is Object-Z, an extension of the well-known Z specification language with explicit support for object-oriented concepts. Its support for object orientation makes Object-Z particularly suited to our task. The system structuring techniques offered by object-orientation are well suited to modelling mobile systems. In addition, inheritance and polymorphism allow us to exploit commonalities in mobile systems by defining more complex models in terms of simpler ones.

Modelling and using imperfect context information

Most recently developed context-aware software applicationsmake unrealistic assumptions about the quality of the available context information, which can lead to inappropriate actions by the application and frustration on the part of the user. In this paper, we explore the problem of imperfect context information and some of its causes, and propose a novel approach for modelling incomplete and inaccurate information. Additionally, we present a discussion of our experiences in developing a contextaware communication application, highlighting design issues that are pertinent when developing applications that rely on imperfect context information.

Stochastic modelling and simulations for solute transport in porous media

A stochastic model for solute transport in aquifers is studied based on the concepts of stochastic velocity and stochastic diffusivity. By applying finite difference techniques to the spatial variables of the stochastic governing equation, a system of stiff stochastic ordinary differential equations is obtained. Both the semi-implicit Euler method and the balanced implicit method are used for solving this stochastic system. Based on the Karhunen-Loeve expansion, stochastic processes in time and space are calculated by means of a spatial correlation matrix. Four types of spatial correlation matrices are presented based on the hydraulic properties of physical parameters. Simulations with two types of correlation matrices are presented.