Visible to the public Biblio

Filters: Author is Clinch, Sarah  [Clear All Filters]
2022-08-12
Ventirozos, Filippos, Batista-Navarro, Riza, Clinch, Sarah, Arellanes, Damian.  2021.  IoT Cooking Workflows for End-Users: A Comparison Between Behaviour Trees and the DX-MAN Model. 2021 ACM/IEEE International Conference on Model Driven Engineering Languages and Systems Companion (MODELS-C). :341–350.
A kitchen underpinned by the Internet of Things (IoT) requires the management of complex procedural processes. This is due to the fact that when supporting an end-user in the preparation of even only one dish, various devices may need to coordinate with each other. Additionally, it is challenging— yet desirable—to enable an end-user to program their kitchen devices according to their preferred behaviour and to allow them to visualise and track their cooking workflows. In this paper, we compared two semantic representations, namely, Behaviour Trees and the DX-MAN model. We analysed these representations based on their suitability for a range of end-users (i.e., novice to experienced). The methodology required the analysis of smart kitchen user requirements, from which we inferred that the main architectural requirements for IoT cooking workflows are variability and compositionality. Guided by the user requirements, we examined various scenarios and analysed workflow complexity and feasibility for each representation. On the one hand, we found that execution complexity tends to be higher on Behaviour Trees. However, due to their fallback node, they provide more transparency on how to recover from unprecedented circumstances. On the other hand, parameter complexity tends to be somewhat higher for the DX-MAN model. Nevertheless, the DX-MAN model can be favourable due to its compositionality aspect and the ease of visualisation it can offer.
2017-06-27
Davies, Nigel, Taft, Nina, Satyanarayanan, Mahadev, Clinch, Sarah, Amos, Brandon.  2016.  Privacy Mediators: Helping IoT Cross the Chasm. Proceedings of the 17th International Workshop on Mobile Computing Systems and Applications. :39–44.

Unease over data privacy will retard consumer acceptance of IoT deployments. The primary source of discomfort is a lack of user control over raw data that is streamed directly from sensors to the cloud. This is a direct consequence of the over-centralization of today's cloud-based IoT hub designs. We propose a solution that interposes a locally-controlled software component called a privacy mediator on every raw sensor stream. Each mediator is in the same administrative domain as the sensors whose data is being collected, and dynamically enforces the current privacy policies of the owners of the sensors or mobile users within the domain. This solution necessitates a logical point of presence for mediators within the administrative boundaries of each organization. Such points of presence are provided by cloudlets, which are small locally-administered data centers at the edge of the Internet that can support code mobility. The use of cloudlet-based mediators aligns well with natural personal and organizational boundaries of trust and responsibility.