Context-Aware Software

With the advent of PDAs (Personal Digital Assistants), smart phones, and other forms of mobile and ubiquitous computers, our computing resources are increasingly moving off of our desktops and into our everyday lives. However, the software and user interfaces for these devices are generally very similar to that of their desktop counterparts, despite the radically different and dynamic environments that they face. We propose that to better assist their users, such devices should be able to sense, react to, and utilise, the user's current environment or context. That is, they should become context-aware. In this thesis we investigate context-awareness at three levels: user interfaces, applications, and supporting architectures/frameworks. To promote the use of context-awareness, and to aid its deployment in software, we have developed two supporting frameworks. The first is an application-oriented framework called stick-e notes. Based on an electronic version of the common Post-It Note, stick-e notes enable the attachment of any electronic resource (e.g. a text file, movie, Java program, etc.) to any type of context (e.g. location, temperature, time, etc.). The second framework we devised seeks to provide a more universal support for the capture, manipulation, and representation of context information. We call it the Context Information Service (CIS). It fills a similar role in context-aware software development as GUI libraries do in user interface development. Our applications research explored how context-awareness can be exploited in real environments with real users. In particular, we developed a suite of PDA-based context-aware tools for fieldworkers. These were used extensively by a group of ecologists in Africa to record observations of giraffe and rhinos in a remote Kenyan game reserve. These tools also provided the foundations for our HCI work, in which we developed the concept of the Minimal Attention User Interface (MAUI). The aim of the MAUI is to reduce the attention required by the user in operating a device by carefully selecting input/output modes that are harmonious to their tasks and environment. To evaluate our ideas and applications a field study was conducted in which over forty volunteers used our system for data collection activities over the course of a summer season at the Kenyan game reserve. The PDA-based tools were unanimously preferred to the paper-based alternatives, and the context-aware features were cited as particular reasons for preferring them. In summary, this thesis presents two frameworks to support context-aware software, a set of applications demonstrating how context-awareness can be utilised in the ''real world'', and a set of HCI guidelines and principles that help in creating user interfaces that fit to their context of use

CLOSER: A Collaborative Locality-aware Overlay SERvice

Current Peer-to-Peer (P2P) file sharing systems make use of a considerable percentage of Internet Service Providers (ISPs) bandwidth. This paper presents the Collaborative Locality-aware Overlay SERvice (CLOSER), an architecture that aims at lessening the usage of expensive international links by exploiting traffic locality (i.e., a resource is downloaded from the inside of the ISP whenever possible). The paper proves the effectiveness of CLOSER by analysis and simulation, also comparing this architecture with existing solutions for traffic locality in P2P systems. While savings on international links can be attractive for ISPs, it is necessary to offer some features that can be of interest for users to favor a wide adoption of the application. For this reason, CLOSER also introduces a privacy module that may arouse the users' interest and encourage them to switch to the new architectur

Sensing and visualizing spatial relations of mobile devices

Location information can be used to enhance interaction with mobile devices. While many location systems require instrumentation of the environment, we present a system that allows devices to measure their spatial relations in a true peer-to-peer fashion. The system is based on custom sensor hardware implemented as USB dongle, and computes spatial relations in real-time. In extension of this system we propose a set of spatialized widgets for incorporation of spatial relations in the user interface. The use of these widgets is illustrated in a number of applications, showing how spatial relations can be employed to support and streamline interaction with mobile devices

Context-aware Dynamic Discovery and Configuration of 'Things' in Smart Environments

The Internet of Things (IoT) is a dynamic global information network consisting of Internet-connected objects, such as RFIDs, sensors, actuators, as well as other instruments and smart appliances that are becoming an integral component of the future Internet. Currently, such Internet-connected objects or `things' outnumber both people and computers connected to the Internet and their population is expected to grow to 50 billion in the next 5 to 10 years. To be able to develop IoT applications, such `things' must become dynamically integrated into emerging information networks supported by architecturally scalable and economically feasible Internet service delivery models, such as cloud computing. Achieving such integration through discovery and configuration of `things' is a challenging task. Towards this end, we propose a Context-Aware Dynamic Discovery of {Things} (CADDOT) model. We have developed a tool SmartLink, that is capable of discovering sensors deployed in a particular location despite their heterogeneity. SmartLink helps to establish the direct communication between sensor hardware and cloud-based IoT middleware platforms. We address the challenge of heterogeneity using a plug in architecture. Our prototype tool is developed on an Android platform. Further, we employ the Global Sensor Network (GSN) as the IoT middleware for the proof of concept validation. The significance of the proposed solution is validated using a test-bed that comprises 52 Arduino-based Libelium sensors.Comment: Big Data and Internet of Things: A Roadmap for Smart Environments, Studies in Computational Intelligence book series, Springer Berlin Heidelberg, 201