Integrating IoT and IoS with a Component-Based approach

International audienceThere is a growing interest in leveraging Service Oriented Architectures (SOA) in domains such as home automation, automotive, mobile phones or e-Health. With the basic idea (supported in e.g. OSGi) that components provide services, it makes it possible to smoothly integrate the Internet of Things (IoT) with the Internet of Services (IoS). The paradigm of the IoS indeed offers interesting capabilities in terms of dynamicity and interoperability. However in domains that involve ``things'' (e.g. appliances), there is still a strong need for loose coupling and a proper separation between types and instances that are well-known in Component-Based approaches but that typical SOA fail to provide. This paper presents how we can still get the best of both worlds by augmenting SOA with a Component-Based approach. We illustrate our approach with a case study from the domain of home automation

MagicPairing: Apple's Take on Securing Bluetooth Peripherals

Device pairing in large Internet of Things (IoT) deployments is a challenge for device manufacturers and users. Bluetooth offers a comparably smooth trust on first use pairing experience. Bluetooth, though, is well-known for security flaws in the pairing process. In this paper, we analyze how Apple improves the security of Bluetooth pairing while still maintaining its usability and specification compliance. The proprietary protocol that resides on top of Bluetooth is called MagicPairing. It enables the user to pair a device once with Apple's ecosystem and then seamlessly use it with all their other Apple devices. We analyze both, the security properties provided by this protocol, as well as its implementations. In general, MagicPairing could be adapted by other IoT vendors to improve Bluetooth security. Even though the overall protocol is well-designed, we identified multiple vulnerabilities within Apple's implementations with over-the-air and in-process fuzzing

Special Session on Industry 4.0

No abstract available

The Internet of Simulation, a Specialisation of the Internet of Things with Simulation and Workflow as a Service (SIM/WFaaS)

Abstract: A trend seen in many industries is the increasing reliance on modelling and simulation to facilitate design, decision making and training. Previously, these models would operate in isolation but now there is a growing need to integrate and connect simulations together for co-simulation. In addition, the 21st century has seen the expansion of the Internet of Things (IoT) enabling the interconnectivity of smart devices across the Internet. In this paper we propose that an important, and often overlooked, domain of IoT is that of modelling and simulation. Expanding IoT to encompass interconnected simulations enables the potential for an Internet of Simulation whereby models and simulations are exposed to the wider internet and can be accessed on an "as-a-service" basis. The proposed IoS would need to manage simulation across heterogeneous infrastructures, temporal and causal aspects of simulations, as well as variations in data structures. Via the proposed Simulation as a Service (SIMaaS) and Workflow as a Service (WFaaS) constructs in IoS, highly complex simulation integration could be performed automatically, resulting in high fidelity system level simulations. Additionally, the potential for faster than real-time simulation afforded by IoS opens the possibility of connecting IoS to existing IoT infrastructure via a real-time bridge to facilitate decision making based on live data

Block-Based Development of Mobile Learning Experiences for the Internet of Things

The Internet of Things enables experts of given domains to create smart user experiences for interacting with the environment. However, development of such experiences requires strong programming skills, which are challenging to develop for non-technical users. This paper presents several extensions to the block-based programming language used in App Inventor to make the creation of mobile apps for smart learning experiences less challenging. Such apps are used to process and graphically represent data streams from sensors by applying map-reduce operations. A workshop with students without previous experience with Internet of Things (IoT) and mobile app programming was conducted to evaluate the propositions. As a result, students were able to create small IoT apps that ingest, process and visually represent data in a simpler form as using App Inventor's standard features. Besides, an experimental study was carried out in a mobile app development course with academics of diverse disciplines. Results showed it was faster and easier for novice programmers to develop the proposed app using new stream processing blocks.Spanish National Research Agency (AEI) - ERDF fund

Identifying smart design attributes for Industry 4.0 customization using a clustering Genetic Algorithm

Industry 4.0 aims at achieving mass customization at a mass production cost. A key component to realizing this is accurate prediction of customer needs and wants, which is however a challenging issue due to the lack of smart analytics tools. This paper investigates this issue in depth and then develops a predictive analytic framework for integrating cloud computing, big data analysis, business informatics, communication technologies, and digital industrial production systems. Computational intelligence in the form of a cluster k-means approach is used to manage relevant big data for feeding potential customer needs and wants to smart designs for targeted productivity and customized mass production. The identification of patterns from big data is achieved with cluster k-means and with the selection of optimal attributes using genetic algorithms. A car customization case study shows how it may be applied and where to assign new clusters with growing knowledge of customer needs and wants. This approach offer a number of features suitable to smart design in realizing Industry 4.0