Quantitative Verification: Formal Guarantees for Timeliness, Reliability and Performance

Computerised systems appear in almost all aspects of our daily lives, often in safety-critical scenarios such as embedded control systems in cars and aircraft or medical devices such as pacemakers and sensors. We are thus increasingly reliant on these systems working correctly, despite often operating in unpredictable or unreliable environments. Designers of such devices need ways to guarantee that they will operate in a reliable and efficient manner. Quantitative verification is a technique for analysing quantitative aspects of a system's design, such as timeliness, reliability or performance. It applies formal methods, based on a rigorous analysis of a mathematical model of the system, to automatically prove certain precisely specified properties, e.g. ``the airbag will always deploy within 20 milliseconds after a crash'' or ``the probability of both sensors failing simultaneously is less than 0.001''. The ability to formally guarantee quantitative properties of this kind is beneficial across a wide range of application domains. For example, in safety-critical systems, it may be essential to establish credible bounds on the probability with which certain failures or combinations of failures can occur. In embedded control systems, it is often important to comply with strict constraints on timing or resources. More generally, being able to derive guarantees on precisely specified levels of performance or efficiency is a valuable tool in the design of, for example, wireless networking protocols, robotic systems or power management algorithms, to name but a few. This report gives a short introduction to quantitative verification, focusing in particular on a widely used technique called model checking, and its generalisation to the analysis of quantitative aspects of a system such as timing, probabilistic behaviour or resource usage. The intended audience is industrial designers and developers of systems such as those highlighted above who could benefit from the application of quantitative verification,but lack expertise in formal verification or modelling

Innovation search fields with Lead Users

Close orientation with the market is essential for innovation success! Although both academics and market research practitioners would generally agree with this statement, alignment with the needs of the customer often results in conservative innovation strategies. Due to their focus on what is currently on offer in the marketplace, customers primarily demand small, step-wise developments - so-called incremental innovations. This dilemma can be overcome through with the help of particularly advanced customers (Lead Users). The Lead User method aids companies in capitalizing on the innovative potential of these highly qualified customers. A case study with the German firm, Johnson & Johnson Medical GmbH, demonstrated that Breakthrough Innovations are achievable this way. -- Kundenorientierung ist entscheidend für den Innovationserfolg! Obwohl dem Wissenschaftler und Praktiker in der Marktforschung grundsätzlich zustimmen dürften, ist mit der konsequenten Ausrichtung auf die Kundenbedürfnisse gleichzeitig der Nachteil einer konservativen Innovationspolitik verbunden. Kunden fördern durch ihre Fixierung auf aktuelle Marktangebot primär kleine Weiterentwicklungen, d.h. inkrementale Innovationen. Dieses Dilemma kann mit Hilfe besonders fortschrittlicher Kunden (Lead User) überwunden werden. Die Lead User Methode hilft Unternehmen dabei, das innovative Potential dieser hochqualifizierten Kunden zu nutzen. Eine Fallanwendung mit der Johnson&Johnson Medical GmbH demonstriert, wie auf diese Weise Ansätze für radikale Innovationen erarbeitet werden können.Produktentwicklung,Produktinnovation,Marktforschung,Lead User

Feedback Control Goes Wireless: Guaranteed Stability over Low-power Multi-hop Networks

Closing feedback loops fast and over long distances is key to emerging applications; for example, robot motion control and swarm coordination require update intervals of tens of milliseconds. Low-power wireless technology is preferred for its low cost, small form factor, and flexibility, especially if the devices support multi-hop communication. So far, however, feedback control over wireless multi-hop networks has only been shown for update intervals on the order of seconds. This paper presents a wireless embedded system that tames imperfections impairing control performance (e.g., jitter and message loss), and a control design that exploits the essential properties of this system to provably guarantee closed-loop stability for physical processes with linear time-invariant dynamics. Using experiments on a cyber-physical testbed with 20 wireless nodes and multiple cart-pole systems, we are the first to demonstrate and evaluate feedback control and coordination over wireless multi-hop networks for update intervals of 20 to 50 milliseconds.Comment: Accepted final version to appear in: 10th ACM/IEEE International Conference on Cyber-Physical Systems (with CPS-IoT Week 2019) (ICCPS '19), April 16--18, 2019, Montreal, QC, Canad