The Future of the Internet

Presents findings from a survey of technology leaders, scholars, industry officials, and analysts. Evaluates the network infrastructure's vulnerability to attack, and the Internet's impact on various institutions and activities in the coming decade

An Activity-Centric Approach to Configuration Work in Distributed Interaction

The widespread introduction of new types of computing devices, such as smartphones, tablet computers, large interactive displays or even wearable devices, has led to setups in which users are interacting with a rich ecology of devices. These new device ecologies have the potential to introduce a whole new set of cross-device and cross-user interactions as well as to support seamless distributed workspaces that facilitate coordination and communication with other users. Because of the distributed nature of this paradigm, there is an intrinsic difficulty and overhead in managing and using these kind of complex device ecologies, which I refer to as configuration work. It is the effort required to set up, manage, communicate, understand and use information, applications and services that are distributed over all devices in use and people involved. Because current devices and their containing software are still document- and application-centric, they fail to capture and support the rich activities and context in which they are being used. This leaves users without a stable concept for cross-device information management, forcing them to perform a large amount of manual configuration work. In this dissertation, I explore an activity-centric approach to configuration work in distributed interaction. The central goal of this dissertation is to develop and apply concepts and ideas from Activity-Centric Computing to distributed interaction. Using the triangulation approach, I explore these concepts on a conceptual, empirical and technological level and present a framework and use cases for designing activitycentric configurations in multi-device information systems. The dissertation presents two major contributions: First, I introduce the term configuration work as an abstract analytical unit that describes and captures the problems and challenges of distributed interaction. Using both empirical data and related work, I argue that configuration work is composed of: curation work, task resumption lag, mobility work, physical handling and articulation work. Using configuration work as a problem description, I operationalize Activity Theory and Activity-Centric Computing to mitigate and reduce configuration work in distributed interaction. By allowing users to interact with computational representations of their real-world activities, creating complex multi-user device ecologies and switching between cross-device information configurations will be more efficient, more effective and provide better support for users’ mental model about a multi-user and multi-device environment. Using activity configuration as a central concept, I introduce a framework that describes how digital representations of human activity can be distributed, fragmented and used across multiple devices and users. Second, I present a technical infrastructure and four applications that apply the concepts of activity configuration. The infrastructure is a general purpose platform for the design, development and deployment of distributed activitycentric systems. The infrastructure simplifies the development of activity-centric systems as it presents complex distributed computing processes and services into high level activity system abstractions. Using this infrastructure and conceptual framework, I describe four fully working applications that explore multi-device interactions in two specific domains: office work and hospital work. The systems are evaluated and tested with end-users in a number of lab and field studies

Trust models for mobile content-sharing applications

Using recent technologies such as Bluetooth, mobile users can share digital content (e.g., photos, videos) with other users in proximity. However, to reduce the cognitive load on mobile users, it is important that only appropriate content is stored and presented to them. This dissertation examines the feasibility of having mobile users filter out irrelevant content by running trust models. A trust model is a piece of software that keeps track of which devices are trusted (for sending quality content) and which are not. Unfortunately, existing trust models are not fit for purpose. Specifically, they lack the ability to: (1) reason about ratings other than binary ratings in a formal way; (2) rely on the trustworthiness of stored third-party recommendations; (3) aggregate recommendations to make accurate predictions of whom to trust; and (4) reason across categories without resorting to ontologies that are shared by all users in the system. We overcome these shortcomings by designing and evaluating algorithms and protocols with which portable devices are able automatically to maintain information about the reputability of sources of content and to learn from each other’s recommendations. More specifically, our contributions are: 1. An algorithm that formally reasons on generic (not necessarily binary) ratings using Bayes’ theorem. 2. A set of security protocols with which devices store ratings in (local) tamper-evident tables and are able to check the integrity of those tables through a gossiping protocol. 3. An algorithm that arranges recommendations in a “Web of Trust” and that makes predictions of trustworthiness that are more accurate than existing approaches by using graph-based learning. 4. An algorithm that learns the similarity between any two categories by extracting similarities between the two categories’ ratings rather than by requiring a universal ontology. It does so automatically by using Singular Value Decomposition. We combine these algorithms and protocols and, using real-world mobility and social network data, we evaluate the effectiveness of our proposal in allowing mobile users to select reputable sources of content. We further examine the feasibility of implementing our proposal on current mobile phones by examining the storage and computational overhead it entails. We conclude that our proposal is both feasible to implement and performs better across a range of parameters than a number of current alternatives

Edge Computing for Extreme Reliability and Scalability

The massive number of Internet of Things (IoT) devices and their continuous data collection will lead to a rapid increase in the scale of collected data. Processing all these collected data at the central cloud server is inefficient, and even is unfeasible or unnecessary. Hence, the task of processing the data is pushed to the network edges introducing the concept of Edge Computing. Processing the information closer to the source of data (e.g., on gateways and on edge micro-servers) not only reduces the huge workload of central cloud, also decreases the latency for real-time applications by avoiding the unreliable and unpredictable network latency to communicate with the central cloud

Rethinking the improvisation of digital health technology: A niche construction perspective

Paid open accessThe COVID-19 pandemic has sent shock waves through healthcare organisations and catalysed an impromptu digital shift, creating a demand for telemedicine and other digital health technologies. Under such conditions, improvisation, adaptation, and innovation emerge as core dimensions to an organisation’s capacity to generate a response to crisis. This paper integrates a process perspective on the radical improvisation of a digital health technology and investigates how the radical improvisation of a digital health technology emerges and develops during a health crisis. Through a combination of supporting case evidence and literature, a multi-phase conceptual process model anchored in the crisis management cycle and illustrating the radical improvisation of digital health technology is developed and proposed. We conclude with discussion on the long-term implications of radical improvisation and crisis learning, with possible theoretical explanation using niche construction theory, and providing suggestions for future information systems and crisis management research.publishedVersio