Enabling High-Level Application Development in the Internet of Things

International audienceThe sensor networking field is evolving into the Internet of Things~(IoT), owing in large part to the increased availability of consumer sensing devices, including modern smart phones. However, application development in the IoT still remains challenging, since it involves dealing with several related issues, such as lack of proper identification of roles of various stakeholders, as well as lack of suitable (high-level) abstractions to address the large scale and heterogeneity in IoT systems. Although the software engineering community has proposed several approaches to address the above in the general case, existing approaches for IoT application development only cover limited subsets of above mentioned challenges. In this paper, we propose a multi-stage model-driven approach for IoT application development based on a precise definition of the role to be played by each stakeholder involved in the process -- domain expert, application designer, application developer, device developer, and network manager. The abstractions provided to each stakeholder are further customized using the inputs provided in the earlier stages by other stakeholders. We have also implemented code-generation and task-mapping techniques to support our approach. Our initial evaluation based on two realistic scenarios shows that the use of our techniques/framework succeeds in improving productivity in the IoT application development process

The Fog Development Kit: A Platform for the Development and Management of Fog Systems

With the rise of the Internet of Things (IoT), fog computing has emerged to help traditional cloud computing in meeting scalability demands. Fog computing makes it possible to fulfill real-time requirements of applications by bringing more processing, storage, and control power geographically closer to end-devices. How- ever, since fog computing is a relatively new field, there is no standard platform for research and development in a realistic environment, and this dramatically inhibits innovation and development of fog-based applications. In response to these challenges, we propose the Fog Development Kit (FDK). By providing high-level interfaces for allocating computing and networking resources, the FDK abstracts the complexities of fog computing from developers and enables the rapid development of fog systems. In addition to supporting application development on a physical deployment, the FDK supports the use of emulation tools (e.g., GNS3 and Mininet) to create realistic environments, allowing fog application prototypes to be built with zero additional costs and enabling seamless portability to a physical infrastructure. Using a physical testbed and various kinds of applications running on it, we verify the operation and study the performance of the FDK. Specifically, we demonstrate that resource allocations are appropriately enforced and guaranteed, even amidst extreme network congestion. We also present simulation-based scalability analysis of the FDK versus the number of switches, the number of end-devices, and the number of fog-devices

Application of Internet of Things in Health Care

The paper focuses on the continuously growing area of Internet of Things and its application to health care. We discuss several important aspects, namely quality, and relevance of data acquired. We illustrate IoT by a case study of diabetes mellitus personalised treatment. Modern type 1 diabetes mellitus therapy is now unimaginable without intensive glycaemia monitoring. In the last decade the possibility of real time continuous glucose monitoring (RT-CGMS) was realised along with integration to some types of insulin pump. Currently the research focuses on continuous glucose monitoring systems that have following advantages: non-invasiveness, high customer acceptance; comfort in use; ease in use; accuracy; long-term measurement up to 4 weeks; calibrating unit integrated; alerts for low or highs of glucose level; enabling higher lifestyle flexibility, e.g. physical activity, food, medication; wireless data and energy transmission; infection risk is minimised. Obviously several sensors are necessary to acquire the contextual data, in particular vital parameters, physical activity, and stress. All measured data must be collected and evaluated in parallel. The aim is to identify the mutual relations in measured parameters, the differences among patients and finally the most important parameters for development of personalised data models

Development of low cost spectrum qualifier for new iot technologies

With the evolution of radio technologies during the last decades, the companies are replacing equipment with individual components with particular functions by systems where most signals are treated digitally through digital signal processing techniques. With this, engineers can develop many applications at the software level, enabling new analyses to exists. With the growth of the internet of things, companies are deploying new solutions around the world. Most of these solutions are wireless applications that use the unlicensed frequency spectrum band, which increases the density of wireless devices in a location. In environments with numerous wireless equipment transmitting simultaneously, it is essential to detect how busy the frequency spectrum is before deploying a new solution. A spectrum analyzer can analyze this, but the cost of acquiring suitable equipment can be very high. Besides that, these devices only allow users to analyze the frequency spectrum, not the technology itself, packet loss, data rate, and coverage, without purchasing expensive software licenses. This thesis presents the development of a software-defined radio application capable of evaluating the performance of radio technologies, such as Bluetooth or Wi-SUN, and shows their behavior in a noisy environment