Ross Shannon

A first approach to the closed-form specification and analysis of an autonomic control system

Control systems must increasingly be designed to involve collections of hardware and software components, both of which may evolve over the lifetime of the system, and which are expected to provide self-managing, adaptive, autonomic behaviour. Understanding the behaviour such a system will exhibit under any specific conditions is a significant design challenge. We present a model derived from approaches to modelling dynamical systems in which the adaptive behaviour of an autonomic system may be described and analysed as a whole. We explain our ideas with reference to a hybrid hardware/software system, and argue that it generalises to other classes of autonomic systems.

Situvis: A Visual Tool for Modeling a User's Behaviour Patterns in a Pervasive Environment

One of the key challenges faced when developing context-aware pervasive systems is to capture the set of inputs that we want a system to adapt to. Arbitrarily specifying ranges of sensor values to respond to will lead to incompleteness of the specification, and may also result in conflicts, when multiple incompatible adaptations may be triggered by a single user action. We posit that the ideal approach combines the use of past traces of real, annotated context data with the ability for a system designer or user to go in and interactively modify the specification of the set of inputs a particular adaptation should be responsive to. We introduce Situvis, an interactive visualisation tool we have developed which assists users and developers of context-aware pervasive systems by visually representing the conditions that need to be present for a situation to be triggered in terms of the real-world context that is being recorded, and allows the user to visually inspect these properties, evaluate their correctness, and change them as required. This tool provides the means to understand the scope of any adaptation defined in the system, and intuitively resolve conflicts inherent in the specification.

Situvis: A sensor data analysis and abstraction tool for pervasive computing systems

Pervasive systems are large-scale systems consisting of many sensors capturing numerous types of information. As this data is highly voluminous and dimensional, data analysis tasks can be extremely cumbersome and time-consuming. Enabling computers to recognise real-world situations is an even more difficult problem, involving not only data analysis, but also consistency checking. Here we present Situvis, an interactive visualisation tool for representing sensor data and creating higher-level abstractions from the data. This paper builds on previous work, Clear et al. (2009) [8] through evolved tool functionality and an evaluation of Situvis. A user-trial consisting of 10 participants shows that Situvis can be used to complete the key tasks in the development process of situation specifications in over 50% less time than an improvised alternative toolset.

Showtime: increasing viewer understanding of dynamic network visualisations

Visualisations of dynamic networks are animated over time, reflecting changes in the underlying data structure. As viewers of these visualisations, it is up to us to accurately perceive and keep up with the constantly shifting view, mentally noting as visual elements are added, removed, changed and rearranged, sometimes at great pace. In a complex data set with a lot happening, this can put a strain on the observers perceptions, with changes in layout and visual population disrupting their internalised mental model of the visualisation, making it difficult to understand what the changes represent. We present Showtime, a novel visualisation technique which dilates the flow of time so that observers have proportionally more time to understand each change based on the density of activity in the visualisation. This is paired with a novel timeline element which tracks the flow of time visually.

Collaborating in context: immersive visualisation environments

As visualizations of large systems get more and more complex, larger collaborative spaces are required so that a team of designers may work together while visualising their system. This paper describes the outfitting of a room to turn it into an immersive visualisation environment. The environment consists of large display areas, onto which are projected high resolution visualisations of software systems. Specialised hardware allows the environment to support multiple concurrent users, who are encouraged to collaborate on team-based tasks and interact with the environment using novel interaction metaphors. We will describe applications that demonstrate the efficacy of this new approach to collaboration.

Graphemes: self-organizing shape-based clustered structures for network visualisations

Network visualisations use clustering approaches to simplify the presentation of complex graph structures. We present a novel application of clustering algorithms, which controls the visual arrangement of the vertices in a cluster to explicitly encode information about that cluster. Our technique arranges parts of the graph into symbolic shapes, depending on the relative size of each cluster. Early results suggest that this layout augmentation helps viewers make sense of a graphs scale and number of elements, while facilitating recall of graph features, and increasing stability in dynamic graph scenarios.